From df678e566f976c46b86af16d4e93e7279e3f3d71 Mon Sep 17 00:00:00 2001 From: David Tesar Date: Tue, 25 Jun 2019 18:34:42 -0700 Subject: [PATCH 001/113] Pipeline to use container --- azure-pipelines.yml | 18 ++---------------- 1 file changed, 2 insertions(+), 16 deletions(-) diff --git a/azure-pipelines.yml b/azure-pipelines.yml index c3815408..7578824f 100644 --- a/azure-pipelines.yml +++ b/azure-pipelines.yml @@ -1,9 +1,7 @@ pool: vmImage: 'Ubuntu 16.04' -#Your build pipeline references a secret variable named ‘sp_username’. Create or edit the build pipeline for this YAML file, define the variable on the Variables tab, and then select the option to make it secret. See https://go.microsoft.com/fwlink/?linkid=865972 -#Your build pipeline references a secret variable named ‘sp_password’. Create or edit the build pipeline for this YAML file, define the variable on the Variables tab, and then select the option to make it secret. See https://go.microsoft.com/fwlink/?linkid=865972 -#Your build pipeline references a secret variable named ‘sp_tenantid’. Create or edit the build pipeline for this YAML file, define the variable on the Variables tab, and then select the option to make it secret. See https://go.microsoft.com/fwlink/?linkid=865972 -#Your build pipeline references a secret variable named ‘subscription_id’. Create or edit the build pipeline for this YAML file, define the variable on the Variables tab, and then select the option to make it secret. See https://go.microsoft.com/fwlink/?linkid=865972 + +container: dtzar/conda3mlops variables: - group: AzureKeyVaultSecrets @@ -14,18 +12,6 @@ trigger: - develop steps: -- task: UsePythonVersion@0 - inputs: - versionSpec: '3.6' - architecture: 'x64' - -- task: Bash@3 - displayName: 'Install Requirements' - inputs: - targetType: filePath - filePath: 'environment_setup/install_requirements.sh' - workingDirectory: 'environment_setup' - - script: | az login --service-principal -u $(spidentity) -p $(spsecret) --tenant $(sptenant) From 9cbcf8252c3900e7fb6186ea5dd03af021271134 Mon Sep 17 00:00:00 2001 From: David Tesar Date: Tue, 25 Jun 2019 19:01:28 -0700 Subject: [PATCH 002/113] Add Dockerfile --- environment_setup/Dockerfile | 7 +++++++ 1 file changed, 7 insertions(+) create mode 100644 environment_setup/Dockerfile diff --git a/environment_setup/Dockerfile b/environment_setup/Dockerfile new file mode 100644 index 00000000..d199b243 --- /dev/null +++ b/environment_setup/Dockerfile @@ -0,0 +1,7 @@ +FROM conda/miniconda3 + +COPY . /setup + +RUN ["apt", "update"] +RUN apt install gcc -y && pip install -r /setup/requirements.txt +RUN pip install azure-cli==2.0.65 && pip install --upgrade azureml-sdk[cli] \ No newline at end of file From c93bea3ea4388638839c2503f76b8445bed433e2 Mon Sep 17 00:00:00 2001 From: David Tesar Date: Tue, 25 Jun 2019 19:04:42 -0700 Subject: [PATCH 003/113] add latest tag --- azure-pipelines.yml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/azure-pipelines.yml b/azure-pipelines.yml index 7578824f..787fa327 100644 --- a/azure-pipelines.yml +++ b/azure-pipelines.yml @@ -1,7 +1,7 @@ pool: vmImage: 'Ubuntu 16.04' -container: dtzar/conda3mlops +container: dtzar/conda3mlops:latest variables: - group: AzureKeyVaultSecrets From d14c4b1150ea2c226c0ef2438151039377cf8e6c Mon Sep 17 00:00:00 2001 From: David Tesar Date: Tue, 25 Jun 2019 19:08:39 -0700 Subject: [PATCH 004/113] Add docker image build pipeline --- environment_setup/docker-image-pipeline.yml | 32 +++++++++++++++++++++ 1 file changed, 32 insertions(+) create mode 100644 environment_setup/docker-image-pipeline.yml diff --git a/environment_setup/docker-image-pipeline.yml b/environment_setup/docker-image-pipeline.yml new file mode 100644 index 00000000..2ee943f1 --- /dev/null +++ b/environment_setup/docker-image-pipeline.yml @@ -0,0 +1,32 @@ +resources: +- repo: self + +queue: + name: Hosted Ubuntu 1604 + +trigger: + branches: + include: + - master + + paths: + include: + - environment_setup/* + +steps: + +- task: Docker@2 + displayName: Login to Docker Hub + inputs: + command: login + containerRegistry: msftDockerHub + +- task: Docker@2 + displayName: 'Build and push an image' + inputs: + command: buildAndPush + repository: dtzar/conda3mlops + buildContext: '$(Build.SourcesDirectory)/environment_setup' + tags: | + $(Build.BuildNumber) + latest \ No newline at end of file From 634cdfa9430ca859aa6b298991df9fb715a47e89 Mon Sep 17 00:00:00 2001 From: Eugene Fedorenko Date: Mon, 29 Jul 2019 14:49:42 -0700 Subject: [PATCH 005/113] new dockerfile --- Dockerfile | 13 +++++++++++++ environment_setup/Dockerfile | 14 ++++++++++---- environment_setup/requirements.txt | 19 ++++++++++++++----- 3 files changed, 37 insertions(+), 9 deletions(-) create mode 100644 Dockerfile diff --git a/Dockerfile b/Dockerfile new file mode 100644 index 00000000..e65c7ca5 --- /dev/null +++ b/Dockerfile @@ -0,0 +1,13 @@ +FROM conda/miniconda3 + +LABEL org.label-schema.vendor = "Microsoft" \ + org.label-schema.url = "dockerhub" \ + org.label-schema.vcs-url = "https://github.com/microsoft/MLOpsPython" + + + +COPY environment_setup/requirements.txt /setup/ + +RUN apt-get update && apt-get install gcc -y && pip install --upgrade -r /setup/requirements.txt + +CMD ["python"] \ No newline at end of file diff --git a/environment_setup/Dockerfile b/environment_setup/Dockerfile index d199b243..e65c7ca5 100644 --- a/environment_setup/Dockerfile +++ b/environment_setup/Dockerfile @@ -1,7 +1,13 @@ FROM conda/miniconda3 -COPY . /setup +LABEL org.label-schema.vendor = "Microsoft" \ + org.label-schema.url = "dockerhub" \ + org.label-schema.vcs-url = "https://github.com/microsoft/MLOpsPython" -RUN ["apt", "update"] -RUN apt install gcc -y && pip install -r /setup/requirements.txt -RUN pip install azure-cli==2.0.65 && pip install --upgrade azureml-sdk[cli] \ No newline at end of file + + +COPY environment_setup/requirements.txt /setup/ + +RUN apt-get update && apt-get install gcc -y && pip install --upgrade -r /setup/requirements.txt + +CMD ["python"] \ No newline at end of file diff --git a/environment_setup/requirements.txt b/environment_setup/requirements.txt index b3c2a14c..25a4b815 100644 --- a/environment_setup/requirements.txt +++ b/environment_setup/requirements.txt @@ -1,5 +1,14 @@ -scipy==1.0.0 -scikit-learn==0.19.1 -numpy==1.14.5 -pandas==0.23.1 -pytest==4.3.0 \ No newline at end of file +#numpy==1.17.0 +#scipy==1.2.2 +#scikit-learn==0.19.1 +#pandas==0.23.1 +pytest==4.3.0 +flake8==3.7.8 +flake8_formatter_junit_xml==0.0.6 +requests>=2.22 +python-dotenv>=0.10.3 +azureml>=0.2 +azureml-core>=1.0 +azureml-pipeline>=1.0 +azure-cli==2.0.46 +azureml-sdk[cli] From 70c444dbee1b7ab94437da819200bea387278ec6 Mon Sep 17 00:00:00 2001 From: Taylor Rockey Date: Mon, 29 Jul 2019 16:30:04 -0700 Subject: [PATCH 006/113] added .env.example. Started replacing parameters --- .env.example | 20 ++++++++++++++++++++ aml_service/00-WorkSpace.py | 20 ++++++++++++-------- aml_service/01-Experiment.py | 6 ++++-- aml_service/02-AttachTrainingVM.py | 10 ++++++---- aml_service/03-AttachAmlCluster.py | 19 +++++++++---------- aml_service/04-AmlPipelines.py | 3 ++- docs/getting_started.md | 5 +++++ environment_setup/requirements.txt | 3 ++- 8 files changed, 60 insertions(+), 26 deletions(-) create mode 100644 .env.example diff --git a/.env.example b/.env.example new file mode 100644 index 00000000..af213b8b --- /dev/null +++ b/.env.example @@ -0,0 +1,20 @@ +# Azure Subscription Variables +WORKSPACE_NAME = '' +RESOURCE_GROUP = '' +SUBSCRIPTION_ID = '' +LOCATION = '' + +# Azure ML Workspace Variables +EXPERIMENT_NAME = '' +SCRIPT_FOLDER = './' +# Remote VM Config +REMOTE_VM_NAME = '' +REMOTE_VM_USERNAME = '' +REMOTE_VM_PASSWORD = '' +REMOTE_VM_IP = '' +# AML Compute Cluster Config +AML_CLUSTER_NAME = '' +AML_CLUSTER_VM_SIZE = '' +AML_CLUSTER_MAX_NODES = '' +AML_CLUSTER_MIN_NODES = '' +AML_CLUSTER_PRIORITY = 'lowpriority' diff --git a/aml_service/00-WorkSpace.py b/aml_service/00-WorkSpace.py index f234ed4c..7538fe1c 100644 --- a/aml_service/00-WorkSpace.py +++ b/aml_service/00-WorkSpace.py @@ -24,19 +24,20 @@ POSSIBILITY OF SUCH DAMAGE. """ from azureml.core import Workspace -import os, json, sys +import os +import json import azureml.core from azureml.core.authentication import AzureCliAuthentication +from dotenv import load_dotenv + +load_dotenv() print("SDK Version:", azureml.core.VERSION) -# print('current dir is ' +os.curdir) -with open("aml_config/config.json") as f: - config = json.load(f) -workspace_name = config["workspace_name"] -resource_group = config["resource_group"] -subscription_id = config["subscription_id"] -location = config["location"] +workspace_name = os.environ.get('WORKSPACE_NAME') +resource_group = os.environ.get('RESOURCE_GROUP') +subscription_id = os.environ.get('SUBSCRIPTION_ID') +location = os.environ.get('LOCATION') cli_auth = AzureCliAuthentication() @@ -60,5 +61,8 @@ auth=cli_auth, ) +# Save the details of this workspace to config +ws.write_config() + # print Workspace details print(ws.name, ws.resource_group, ws.location, ws.subscription_id, sep="\n") diff --git a/aml_service/01-Experiment.py b/aml_service/01-Experiment.py index b3543e1c..3bb5a9cf 100644 --- a/aml_service/01-Experiment.py +++ b/aml_service/01-Experiment.py @@ -27,14 +27,16 @@ from azureml.core import Experiment from azureml.core import Workspace from azureml.core.authentication import AzureCliAuthentication +from dotenv import load_dotenv cli_auth = AzureCliAuthentication() def getExperiment(): + load_dotenv() ws = Workspace.from_config(auth=cli_auth) - script_folder = "." - experiment_name = "devops-ai-demo" + script_folder = os.environ.get('SCRIPT_FOLDER') + experiment_name = os.environ.get('EXPERIMENT_NAME') exp = Experiment(workspace=ws, name=experiment_name) print(exp.name, exp.workspace.name, sep="\n") return exp diff --git a/aml_service/02-AttachTrainingVM.py b/aml_service/02-AttachTrainingVM.py index 3fc11c25..3f703a7e 100644 --- a/aml_service/02-AttachTrainingVM.py +++ b/aml_service/02-AttachTrainingVM.py @@ -34,8 +34,10 @@ from azureml.core.compute import DsvmCompute from azureml.core.compute_target import ComputeTargetException from azureml.core.authentication import AzureCliAuthentication +from dotenv import load_dotenv cli_auth = AzureCliAuthentication() +load_dotenv() # Get workspace ws = Workspace.from_config(auth=cli_auth) @@ -44,10 +46,10 @@ with open("aml_config/security_config.json") as f: config = json.load(f) -remote_vm_name = config["remote_vm_name"] -remote_vm_username = config["remote_vm_username"] -remote_vm_password = config["remote_vm_password"] -remote_vm_ip = config["remote_vm_ip"] +remote_vm_name = os.environ.get('REMOTE_VM_NAME') +remote_vm_username = os.environ.get('REMOTE_VM_USERNAME') +remote_vm_password = os.environ.get('REMOTE_VM_PASSWORD') +remote_vm_ip = os.environ.get('REMOTE_VM_IP') try: dsvm_compute = RemoteCompute.attach( diff --git a/aml_service/03-AttachAmlCluster.py b/aml_service/03-AttachAmlCluster.py index 1ba3f127..b77336f8 100644 --- a/aml_service/03-AttachAmlCluster.py +++ b/aml_service/03-AttachAmlCluster.py @@ -28,17 +28,16 @@ from azureml.core.compute import ComputeTarget, AmlCompute from azureml.core.compute_target import ComputeTargetException from azureml.core.authentication import AzureCliAuthentication -import os, json +import os +from dotenv import load_dotenv cli_auth = AzureCliAuthentication() +load_dotenv() + # Get workspace ws = Workspace.from_config(auth=cli_auth) -# Read the New VM Config -with open("aml_config/security_config.json") as f: - config = json.load(f) - -aml_cluster_name = config["aml_cluster_name"] +aml_cluster_name = os.environ.get('AML_CLUSTER_NAME') # un-comment the below lines if you want to put AML Compute under Vnet. Also update /aml_config/security_config.json # vnet_resourcegroup_name = config['vnet_resourcegroup_name'] @@ -51,10 +50,10 @@ print("Found existing cluster, use it.") except ComputeTargetException: compute_config = AmlCompute.provisioning_configuration( - vm_size="STANDARD_D2_V2", - vm_priority="dedicated", - min_nodes=1, - max_nodes=3, + vm_size=os.environ.get('AML_CLUSTER_VM_SIZE'), + vm_priority=os.environ.get('AML_CLUSTER_PRIORITY'), + min_nodes=int(os.environ.get('AML_CLUSTER_MIN_NODES')), + max_nodes=int(os.environ.get('AML_CLUSTER_MAX_NODES')), idle_seconds_before_scaledown="300", # #Uncomment the below lines for VNet support # vnet_resourcegroup_name=vnet_resourcegroup_name, diff --git a/aml_service/04-AmlPipelines.py b/aml_service/04-AmlPipelines.py index 44d389e5..4b79d131 100644 --- a/aml_service/04-AmlPipelines.py +++ b/aml_service/04-AmlPipelines.py @@ -26,6 +26,7 @@ import os, json, requests, datetime import argparse +from dotenv import load_dotenv from azureml.core import Workspace, Experiment, Datastore from azureml.core.runconfig import RunConfiguration, CondaDependencies from azureml.data.data_reference import DataReference @@ -41,7 +42,7 @@ print("Pipeline SDK-specific imports completed") cli_auth = AzureCliAuthentication() - +load_dotenv() parser = argparse.ArgumentParser("Pipeline") parser.add_argument( diff --git a/docs/getting_started.md b/docs/getting_started.md index 35232d3e..bc64aed4 100644 --- a/docs/getting_started.md +++ b/docs/getting_started.md @@ -26,6 +26,11 @@ Please make note the following values after creating a service principal, we wil **Note:** You must have sufficient permissions to register an application with your Azure AD tenant, and assign the application to a role in your Azure subscription. Contact your subscription adminstator if you don't have the permissions. Normally a subscription admin can create a Service principal and can provide you the details. +### 3(b). Configure local development environment variables + +For local development, this project makes use of [python-dotenv](https://pypi.org/project/python-dotenv/). This pip package allows you to use a `.env` file to manage your environment variables at runtime. + +The .env.example file is a template. To run this code locally, create a file in the root of this project titled `.env`, and add in the key-value pairs for each of the environment variables found in the `.env.example`, as well as any environment variables needed for your custom scripts that will run on the build agent. ### 4. Store secret in Key Vault and link it as variable group in Azure DevOps to be used by piplines. Our pipeline require the following variables to autheticate with Azure. diff --git a/environment_setup/requirements.txt b/environment_setup/requirements.txt index b3c2a14c..21a652c8 100644 --- a/environment_setup/requirements.txt +++ b/environment_setup/requirements.txt @@ -2,4 +2,5 @@ scipy==1.0.0 scikit-learn==0.19.1 numpy==1.14.5 pandas==0.23.1 -pytest==4.3.0 \ No newline at end of file +pytest==4.3.0 +python-dotenv==0.10.3 \ No newline at end of file From e2290971083a6fb6de9264eb462bf9e71a4a60d0 Mon Sep 17 00:00:00 2001 From: Eugene Fedorenko Date: Tue, 30 Jul 2019 09:38:05 -0700 Subject: [PATCH 007/113] Pipeline building a docker image --- environment_setup/docker-image-pipeline.yml | 29 +++++++++------------ 1 file changed, 13 insertions(+), 16 deletions(-) diff --git a/environment_setup/docker-image-pipeline.yml b/environment_setup/docker-image-pipeline.yml index 2ee943f1..600fc271 100644 --- a/environment_setup/docker-image-pipeline.yml +++ b/environment_setup/docker-image-pipeline.yml @@ -13,20 +13,17 @@ trigger: include: - environment_setup/* -steps: - -- task: Docker@2 - displayName: Login to Docker Hub - inputs: - command: login - containerRegistry: msftDockerHub +variables: + containerRegistry: $[coalesce(variables['acrServiceConnection'], 'acrconnection')] + imageName: $[coalesce(variables['imageName'], 'mlopspython')] -- task: Docker@2 - displayName: 'Build and push an image' - inputs: - command: buildAndPush - repository: dtzar/conda3mlops - buildContext: '$(Build.SourcesDirectory)/environment_setup' - tags: | - $(Build.BuildNumber) - latest \ No newline at end of file +steps: + - task: Docker@2 + displayName: Build and Push + inputs: + command: buildAndPush + containerRegistry: '$(containerRegistry)' + repository: '$(imageName)' + tags: 'latest' + buildContext: '$(Build.SourcesDirectory)' + dockerFile: '$(Build.SourcesDirectory)/environment_setup/Dockerfile' From 176319a31930500d855b0a1183f32de2c567ce07 Mon Sep 17 00:00:00 2001 From: Eugene Fedorenko Date: Tue, 30 Jul 2019 10:08:19 -0700 Subject: [PATCH 008/113] Update docker-image-pipeline.yml --- environment_setup/docker-image-pipeline.yml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/environment_setup/docker-image-pipeline.yml b/environment_setup/docker-image-pipeline.yml index 600fc271..37637ba6 100644 --- a/environment_setup/docker-image-pipeline.yml +++ b/environment_setup/docker-image-pipeline.yml @@ -15,7 +15,7 @@ trigger: variables: containerRegistry: $[coalesce(variables['acrServiceConnection'], 'acrconnection')] - imageName: $[coalesce(variables['imageName'], 'mlopspython')] + imageName: $[coalesce(variables['imageName'], 'public/mlops/mlopspython')] steps: - task: Docker@2 From 6d8704081ae92a8c26e4f83646fb95ef7a006bcd Mon Sep 17 00:00:00 2001 From: Eugene Fedorenko Date: Tue, 30 Jul 2019 11:12:56 -0700 Subject: [PATCH 009/113] Pipeline building an image --- Dockerfile | 13 ------------- azure-pipelines.yml | 4 +++- environment_setup/docker-image-pipeline.yml | 2 +- environment_setup/requirements.txt | 7 ------- 4 files changed, 4 insertions(+), 22 deletions(-) delete mode 100644 Dockerfile diff --git a/Dockerfile b/Dockerfile deleted file mode 100644 index e65c7ca5..00000000 --- a/Dockerfile +++ /dev/null @@ -1,13 +0,0 @@ -FROM conda/miniconda3 - -LABEL org.label-schema.vendor = "Microsoft" \ - org.label-schema.url = "dockerhub" \ - org.label-schema.vcs-url = "https://github.com/microsoft/MLOpsPython" - - - -COPY environment_setup/requirements.txt /setup/ - -RUN apt-get update && apt-get install gcc -y && pip install --upgrade -r /setup/requirements.txt - -CMD ["python"] \ No newline at end of file diff --git a/azure-pipelines.yml b/azure-pipelines.yml index 787fa327..b1ae0a5d 100644 --- a/azure-pipelines.yml +++ b/azure-pipelines.yml @@ -1,7 +1,9 @@ pool: vmImage: 'Ubuntu 16.04' -container: dtzar/conda3mlops:latest +container: + image: mlopscr.azurecr.io/public/mlops/mlopspython:latest + endpoint: acrconnection variables: - group: AzureKeyVaultSecrets diff --git a/environment_setup/docker-image-pipeline.yml b/environment_setup/docker-image-pipeline.yml index 600fc271..c88884d8 100644 --- a/environment_setup/docker-image-pipeline.yml +++ b/environment_setup/docker-image-pipeline.yml @@ -15,7 +15,7 @@ trigger: variables: containerRegistry: $[coalesce(variables['acrServiceConnection'], 'acrconnection')] - imageName: $[coalesce(variables['imageName'], 'mlopspython')] + imageName: $[coalesce(variables['agentImageName'], 'public/mlops/mlopspython')] steps: - task: Docker@2 diff --git a/environment_setup/requirements.txt b/environment_setup/requirements.txt index 25a4b815..bbd03023 100644 --- a/environment_setup/requirements.txt +++ b/environment_setup/requirements.txt @@ -1,12 +1,5 @@ -#numpy==1.17.0 -#scipy==1.2.2 -#scikit-learn==0.19.1 -#pandas==0.23.1 pytest==4.3.0 -flake8==3.7.8 -flake8_formatter_junit_xml==0.0.6 requests>=2.22 -python-dotenv>=0.10.3 azureml>=0.2 azureml-core>=1.0 azureml-pipeline>=1.0 From 53c61276dc7bc3592341599e0b9b22f8466e39ad Mon Sep 17 00:00:00 2001 From: Eugene Fedorenko Date: Tue, 30 Jul 2019 11:15:29 -0700 Subject: [PATCH 010/113] resolving conflicts --- environment_setup/docker-image-pipeline.yml | 4 ---- 1 file changed, 4 deletions(-) diff --git a/environment_setup/docker-image-pipeline.yml b/environment_setup/docker-image-pipeline.yml index 9e2fdcd0..c88884d8 100644 --- a/environment_setup/docker-image-pipeline.yml +++ b/environment_setup/docker-image-pipeline.yml @@ -15,11 +15,7 @@ trigger: variables: containerRegistry: $[coalesce(variables['acrServiceConnection'], 'acrconnection')] -<<<<<<< HEAD imageName: $[coalesce(variables['agentImageName'], 'public/mlops/mlopspython')] -======= - imageName: $[coalesce(variables['imageName'], 'public/mlops/mlopspython')] ->>>>>>> 176319a31930500d855b0a1183f32de2c567ce07 steps: - task: Docker@2 From a8716655d51371ac062cd23b376245dffc84fb0e Mon Sep 17 00:00:00 2001 From: Taylor Rockey Date: Tue, 30 Jul 2019 14:42:33 -0700 Subject: [PATCH 011/113] Additional env updates - no deployment tested --- .env.example | 14 +++++++++ aml_service/04-AmlPipelines.py | 22 ++++++------- aml_service/05-TriggerAmlPipeline.py | 47 ++++++++++++++++------------ aml_service/10-TrainOnLocal.py | 8 +++-- aml_service/11-TrainOnLocalEnv.py | 12 ++++--- aml_service/12-TrainOnVM.py | 12 ++++--- aml_service/15-EvaluateModel.py | 14 ++++----- aml_service/20-RegisterModel.py | 8 +++-- aml_service/30-CreateScoringImage.py | 17 ++++------ aml_service/50-deployOnAci.py | 14 +++++---- aml_service/51-deployOnAks.py | 14 +++------ 11 files changed, 100 insertions(+), 82 deletions(-) diff --git a/.env.example b/.env.example index af213b8b..0a0a28a7 100644 --- a/.env.example +++ b/.env.example @@ -7,6 +7,7 @@ LOCATION = '' # Azure ML Workspace Variables EXPERIMENT_NAME = '' SCRIPT_FOLDER = './' +BLOB_STORE_NAME = '' # Remote VM Config REMOTE_VM_NAME = '' REMOTE_VM_USERNAME = '' @@ -18,3 +19,16 @@ AML_CLUSTER_VM_SIZE = '' AML_CLUSTER_MAX_NODES = '' AML_CLUSTER_MIN_NODES = '' AML_CLUSTER_PRIORITY = 'lowpriority' +# Training Config +MODEL_NAME = '' +# AML Pipeline Config +TRAINING_PIPELINE_NAME = '' +PIPELINE_CONDA_PATH = 'aml_config/conda_dependencies.yml' +# Image config +IMAGE_NAME = '' +IMAGE_DESCRIPTION = '' +IMAGE_VERSION = '' +# ACI Config +ACI_CPU_CORES = '' +ACI_MEM_GB = '' +ACI_DESCRIPTION = '' \ No newline at end of file diff --git a/aml_service/04-AmlPipelines.py b/aml_service/04-AmlPipelines.py index 4b79d131..1a0147a8 100644 --- a/aml_service/04-AmlPipelines.py +++ b/aml_service/04-AmlPipelines.py @@ -58,25 +58,23 @@ # Get workspace -ws = Workspace.from_config(path="aml_config/config.json", auth=cli_auth) -def_blob_store = Datastore(ws, "workspaceblobstore") +ws = Workspace.from_config(auth=cli_auth) +blob_store_name = os.environ['BLOB_STORE_NAME'] +def_blob_store = Datastore(ws, blob_store_name) # Get AML Compute name and Experiment Name -with open("aml_config/security_config.json") as f: - config = json.load(f) +experiment_name = os.environ['EXPERIMENT_NAME'] +aml_cluster_name = os.environ['AML_CLUSTER_NAME'] +aml_pipeline_name = os.environ['TRAINING_PIPELINE_NAME'] +default_model_name = os.environ['MODEL_NAME'] +model_name = PipelineParameter(name="model_name", default_value=default_model_name) -experiment_name = config["experiment_name"] -aml_cluster_name = config["aml_cluster_name"] -aml_pipeline_name = "training-pipeline" -#model_name = config["model_name"] -model_name = PipelineParameter(name="model_name", default_value="sklearn_regression_model.pkl") - -source_directory = "code" +source_directory = os.environ.get('TRAINING_CODE_SOURCE_DIR', 'code') # Run Config # Declare packages dependencies required in the pipeline (these can also be expressed as a YML file) # cd = CondaDependencies.create(pip_packages=["azureml-defaults", 'tensorflow==1.8.0']) -cd = CondaDependencies("aml_config/conda_dependencies.yml") +cd = CondaDependencies(os.environ['PIPELINE_CONDA_PATH']) run_config = RunConfiguration(conda_dependencies=cd) aml_compute = ws.compute_targets[aml_cluster_name] diff --git a/aml_service/05-TriggerAmlPipeline.py b/aml_service/05-TriggerAmlPipeline.py index 66838a62..299bf476 100644 --- a/aml_service/05-TriggerAmlPipeline.py +++ b/aml_service/05-TriggerAmlPipeline.py @@ -27,31 +27,38 @@ import os, json, requests, datetime, sys import argparse from azureml.core.authentication import AzureCliAuthentication +from azureml.core import Workspace, Experiment +from azureml.pipeline.core import Pipeline, PublishedPipeline +from dotenv import load_dotenv -try: - with open("aml_config/pipeline_config.json") as f: - config = json.load(f) - with open("aml_config/security_config.json") as f: - security_config = json.load(f) -except: - print("No pipeline config found") - sys.exit(0) +load_dotenv() # Run a published pipeline cli_auth = AzureCliAuthentication() aad_token = cli_auth.get_authentication_header() -rest_endpoint1 = config["rest_endpoint"] -experiment_name = config["experiment_name"] -model_name = security_config["model_name"] +pipeline_name = os.environ['TRAINING_PIPELINE_NAME'] +experiment_name = os.environ['EXPERIMENT_NAME'] +model_name = os.environ['MODEL_NAME'] + +ws = Workspace.from_config() +experiment = Experiment(ws, experiment_name) +published_pipelines = PublishedPipeline.get_all(ws) +for p in published_pipelines: + if(p.name == pipeline_name): + pipeline = p -print(rest_endpoint1) +try: + if pipeline is not None: + pipeline_run = experiment.submit( + pipeline, + pipeline_parameters={'model_name': model_name} + ) -response = requests.post( - rest_endpoint1, headers=aad_token, - json={"ExperimentName": experiment_name, - "ParameterAssignments": {"model_name":model_name}} -) + run_id = pipeline_run.run_id + print(run_id) + print("Pipeline run initiated") + else: + raise FileNotFoundError -run_id = response.json()["Id"] -print(run_id) -print("Pipeline run initiated") +except FileNotFoundError: + print('No pipeline with that name found') diff --git a/aml_service/10-TrainOnLocal.py b/aml_service/10-TrainOnLocal.py index d7c71b3b..be5d3e47 100644 --- a/aml_service/10-TrainOnLocal.py +++ b/aml_service/10-TrainOnLocal.py @@ -23,7 +23,8 @@ ARISING IN ANY WAY OUT OF THE USE OF THE SOFTWARE CODE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. """ - +import os +from dotenv import load_dotenv from azureml.core.runconfig import RunConfiguration from azureml.core import Workspace from azureml.core import Experiment @@ -32,12 +33,13 @@ from azureml.core.authentication import AzureCliAuthentication cli_auth = AzureCliAuthentication() +load_dotenv() # Get workspace ws = Workspace.from_config(auth=cli_auth) # Attach Experiment -experiment_name = "devops-ai-demo" +experiment_name = os.environ['EXPERIMENT_NAME'] exp = Experiment(workspace=ws, name=experiment_name) print(exp.name, exp.workspace.name, sep="\n") @@ -47,7 +49,7 @@ print("Submitting an experiment.") src = ScriptRunConfig( - source_directory="./code", + source_directory=os.environ['SCRIPT_FOLDER'], script="training/train.py", run_config=run_config_user_managed, ) diff --git a/aml_service/11-TrainOnLocalEnv.py b/aml_service/11-TrainOnLocalEnv.py index 544a9d93..1cea04ed 100644 --- a/aml_service/11-TrainOnLocalEnv.py +++ b/aml_service/11-TrainOnLocalEnv.py @@ -25,7 +25,9 @@ """ ## Create a new Conda environment on local and train the model ## System-managed environment - +import os +import json +from dotenv import load_dotenv from azureml.core.conda_dependencies import CondaDependencies from azureml.core.runconfig import RunConfiguration from azureml.core import Workspace @@ -35,12 +37,12 @@ from azureml.core.authentication import AzureCliAuthentication cli_auth = AzureCliAuthentication() - +load_dotenv() # Get workspace ws = Workspace.from_config(auth=cli_auth) # Attach Experiment -experiment_name = "devops-ai-demo" +experiment_name = os.environ['EXPERIMENT_NAME'] exp = Experiment(workspace=ws, name=experiment_name) print(exp.name, exp.workspace.name, sep="\n") @@ -57,9 +59,9 @@ print("Submitting an experiment to new conda virtual env") src = ScriptRunConfig( - source_directory="./code", + source_directory=os.environ['SCRIPT_FOLDER'], script="training/train.py", - run_config=run_config_user_managed, + run_config=run_config_system_managed, ) run = exp.submit(src) diff --git a/aml_service/12-TrainOnVM.py b/aml_service/12-TrainOnVM.py index 788ffd15..18db4090 100644 --- a/aml_service/12-TrainOnVM.py +++ b/aml_service/12-TrainOnVM.py @@ -24,6 +24,7 @@ POSSIBILITY OF SUCH DAMAGE. """ import os, json +from dotenv import load_dotenv from azureml.core import Workspace from azureml.core import Experiment from azureml.core.compute import RemoteCompute @@ -33,18 +34,17 @@ from azureml.core.authentication import AzureCliAuthentication cli_auth = AzureCliAuthentication() +load_dotenv() # Get workspace ws = Workspace.from_config(auth=cli_auth) # Read the New VM Config -with open("aml_config/security_config.json") as f: - config = json.load(f) -remote_vm_name = config["remote_vm_name"] +remote_vm_name = os.environ['REMOTE_VM_NAME'] # Attach Experiment -experiment_name = "devops-ai-demo" +experiment_name = os.environ['EXPERIMENT_NAME'] exp = Experiment(workspace=ws, name=experiment_name) print(exp.name, exp.workspace.name, sep="\n") @@ -57,7 +57,9 @@ src = ScriptRunConfig( - source_directory="./code", script="training/train.py", run_config=run_config + source_directory=os.environ['SCRIPT_FOLDER'], + script="training/train.py", + run_config=run_config ) run = exp.submit(src) diff --git a/aml_service/15-EvaluateModel.py b/aml_service/15-EvaluateModel.py index 4d266a98..81511a85 100644 --- a/aml_service/15-EvaluateModel.py +++ b/aml_service/15-EvaluateModel.py @@ -24,6 +24,7 @@ POSSIBILITY OF SUCH DAMAGE. """ import os, json +from dotenv import load_dotenv from azureml.core import Workspace from azureml.core import Experiment from azureml.core.model import Model @@ -32,7 +33,7 @@ from azureml.core.authentication import AzureCliAuthentication cli_auth = AzureCliAuthentication() - +load_dotenv() # Get workspace ws = Workspace.from_config(auth=cli_auth) @@ -41,13 +42,13 @@ # Add golden data set on which all the model performance can be evaluated # Get the latest run_id -with open("aml_config/run_id.json") as f: - config = json.load(f) - -new_model_run_id = config["run_id"] -experiment_name = config["experiment_name"] +experiment_name = os.environ["EXPERIMENT_NAME"] exp = Experiment(workspace=ws, name=experiment_name) +runs = exp.get_runs() +new_model_run = next(runs) +new_model_run_id = new_model_run.id + try: # Get most recently registered model, we assume that is the model in production. Download this model and compare it with the recently trained model by running test with same data set. @@ -64,7 +65,6 @@ # Get the run history for both production model and newly trained model and compare mse production_model_run = Run(exp, run_id=production_model_run_id) - new_model_run = Run(exp, run_id=new_model_run_id) production_model_mse = production_model_run.get_metrics().get("mse") new_model_mse = new_model_run.get_metrics().get("mse") diff --git a/aml_service/20-RegisterModel.py b/aml_service/20-RegisterModel.py index bd9a7bbc..009575cc 100644 --- a/aml_service/20-RegisterModel.py +++ b/aml_service/20-RegisterModel.py @@ -24,6 +24,7 @@ POSSIBILITY OF SUCH DAMAGE. """ import os, json, sys +from dotenv import load_dotenv from azureml.core import Workspace from azureml.core import Run from azureml.core import Experiment @@ -33,7 +34,7 @@ from azureml.core.authentication import AzureCliAuthentication cli_auth = AzureCliAuthentication() - +load_dotenv() # Get workspace ws = Workspace.from_config(auth=cli_auth) @@ -49,7 +50,7 @@ sys.exit(0) run_id = config["run_id"] -experiment_name = config["experiment_name"] +experiment_name = os.environ['EXPERIMENT_NAME'] exp = Experiment(workspace=ws, name=experiment_name) run = Run(experiment=exp, run_id=run_id) @@ -60,12 +61,13 @@ os.makedirs(model_local_dir, exist_ok=True) # Download Model to Project root directory -model_name = "sklearn_regression_model.pkl" +model_name = os.environ['MODEL_NAME'] run.download_file( name="./outputs/" + model_name, output_file_path="./model/" + model_name ) print("Downloaded model {} to Project root directory".format(model_name)) os.chdir("./model") +# TODO: Parameterize tagging model = Model.register( model_path=model_name, # this points to a local file model_name=model_name, # this is the name the model is registered as diff --git a/aml_service/30-CreateScoringImage.py b/aml_service/30-CreateScoringImage.py index 4c7597e1..d0b3dc56 100644 --- a/aml_service/30-CreateScoringImage.py +++ b/aml_service/30-CreateScoringImage.py @@ -24,13 +24,14 @@ POSSIBILITY OF SUCH DAMAGE. """ import os, json, sys +from dotenv import load_dotenv from azureml.core import Workspace from azureml.core.image import ContainerImage, Image from azureml.core.model import Model from azureml.core.authentication import AzureCliAuthentication cli_auth = AzureCliAuthentication() - +load_dotenv() # Get workspace ws = Workspace.from_config(auth=cli_auth) @@ -56,26 +57,20 @@ # ) # ) -try: - with open("aml_config/security_config.json") as f: - security_config = json.load(f) -except: - print("No Security Config found") - sys.exit(0) - # Run a published pipeline #model_name = "sklearn_regression_model.pkl" -model_name = security_config["model_name"] +model_name = os.environ['MODEL_NAME'] model = Model(ws, name=model_name) os.chdir("./code/scoring") -image_name = "diabetes-model-score" +image_name = os.environ['IMAGE_NAME'] +# TODO: Parameterize tagging image_config = ContainerImage.image_configuration( execution_script="score.py", runtime="python", conda_file="conda_dependencies.yml", - description="Image with ridge regression model", + description=os.environ['IMAGE_DESCRIPTION'], tags={"area": "diabetes", "type": "regression"}, ) diff --git a/aml_service/50-deployOnAci.py b/aml_service/50-deployOnAci.py index 00313380..aab7602a 100644 --- a/aml_service/50-deployOnAci.py +++ b/aml_service/50-deployOnAci.py @@ -24,6 +24,7 @@ POSSIBILITY OF SUCH DAMAGE. """ import os, json, datetime, sys +from dotenv import load_dotenv from operator import attrgetter from azureml.core import Workspace from azureml.core.model import Model @@ -33,6 +34,7 @@ from azureml.core.authentication import AzureCliAuthentication cli_auth = AzureCliAuthentication() +load_dotenv() # Get workspace ws = Workspace.from_config(auth=cli_auth) # Get the Image to deploy details try: @@ -44,8 +46,8 @@ sys.exit(0) -image_name = config["image_name"] -image_version = config["image_version"] +image_name = os.environ["IMAGE_NAME"] +image_version = int(os.environ['IMAGE_VERSION']) images = Image.list(workspace=ws) image, = (m for m in images if m.version == image_version and m.name == image_name) @@ -58,12 +60,12 @@ # image = max(images, key=attrgetter('version')) # print('From Max Version, Image used to deploy webservice on ACI: {}\nImage Version: {}\nImage Location = {}'.format(image.name, image.version, image.image_location)) - +# TODO: parameterize tagging aciconfig = AciWebservice.deploy_configuration( - cpu_cores=1, - memory_gb=1, + cpu_cores=int(os.environ['ACI_CPU_CORES']), + memory_gb=int(os.environ['ACI_MEM_GB']), tags={"area": "diabetes", "type": "regression"}, - description="A sample description", + description=os.environ['ACI_DESCRIPTION'], ) aci_service_name = "aciwebservice" + datetime.datetime.now().strftime("%m%d%H") diff --git a/aml_service/51-deployOnAks.py b/aml_service/51-deployOnAks.py index 379ea90c..1ad50990 100644 --- a/aml_service/51-deployOnAks.py +++ b/aml_service/51-deployOnAks.py @@ -24,6 +24,7 @@ POSSIBILITY OF SUCH DAMAGE. """ import os, json, datetime, sys +from dotenv import load_dotenv from operator import attrgetter from azureml.core import Workspace from azureml.core.model import Model @@ -33,20 +34,13 @@ from azureml.core.authentication import AzureCliAuthentication cli_auth = AzureCliAuthentication() +load_dotenv() # Get workspace ws = Workspace.from_config(auth=cli_auth) # Get the Image to deploy details -try: - with open("aml_config/image.json") as f: - config = json.load(f) -except: - print("No new model, thus no deployment on ACI") - # raise Exception('No new model to register as production model perform better') - sys.exit(0) - -image_name = config["image_name"] -image_version = config["image_version"] +image_name = os.environ['IMAGE_NAME'] +image_version = os.environ["IMAGE_VERSION"] images = Image.list(workspace=ws) image, = (m for m in images if m.version == image_version and m.name == image_name) From 23f17d8849a923950da7b2d122357854f3119e09 Mon Sep 17 00:00:00 2001 From: Eugene Fedorenko Date: Tue, 30 Jul 2019 16:03:56 -0700 Subject: [PATCH 012/113] iac pipelines --- .../arm-templates/cloud-environment.json | 123 ++++++++++++++++++ environment_setup/iac-create-environment.yml | 31 +++++ environment_setup/iac-remove-environment.yml | 27 ++++ 3 files changed, 181 insertions(+) create mode 100644 environment_setup/arm-templates/cloud-environment.json create mode 100644 environment_setup/iac-create-environment.yml create mode 100644 environment_setup/iac-remove-environment.yml diff --git a/environment_setup/arm-templates/cloud-environment.json b/environment_setup/arm-templates/cloud-environment.json new file mode 100644 index 00000000..8fd905cb --- /dev/null +++ b/environment_setup/arm-templates/cloud-environment.json @@ -0,0 +1,123 @@ +{ + "$schema": "https://schema.management.azure.com/schemas/2015-01-01/deploymentTemplate.json#", + "contentVersion": "1.0.0.0", + "parameters": { + "baseName": { + "type": "string", + "maxLength": 10, + "minLength": 3, + "metadata": { + "description": "The base name to use as prefix to create all the resources." + } + }, + "location": { + "type": "string", + "defaultValue": "eastus", + "allowedValues": [ + "eastus", + "eastus2", + "southcentralus", + "southeastasia", + "westcentralus", + "westeurope", + "westus2" + ], + "metadata": { + "description": "Specifies the location for all resources." + } + } + }, + "variables": { + "amlWorkspaceName": "[concat(parameters('baseName'),'-AML-WS')]", + "storageAccountName": "[concat(toLower(parameters('baseName')), 'amlsa')]", + "storageAccountType": "Standard_LRS", + "keyVaultName": "[concat(parameters('baseName'),'-AML-KV')]", + "tenantId": "[subscription().tenantId]", + "applicationInsightsName": "[concat(parameters('baseName'),'-AML-AI')]", + "containerRegistryName": "[concat(toLower(parameters('baseName')),'amlcr')]" + }, + "resources": [ + { + "type": "Microsoft.Storage/storageAccounts", + "apiVersion": "2018-07-01", + "name": "[variables('storageAccountName')]", + "location": "[parameters('location')]", + "sku": { + "name": "[variables('storageAccountType')]" + }, + "kind": "StorageV2", + "properties": { + "encryption": { + "services": { + "blob": { + "enabled": true + }, + "file": { + "enabled": true + } + }, + "keySource": "Microsoft.Storage" + }, + "supportsHttpsTrafficOnly": true + } + }, + { + "type": "Microsoft.KeyVault/vaults", + "apiVersion": "2018-02-14", + "name": "[variables('keyVaultName')]", + "location": "[parameters('location')]", + "properties": { + "tenantId": "[variables('tenantId')]", + "sku": { + "name": "standard", + "family": "A" + }, + "accessPolicies": [] + } + }, + { + "type": "Microsoft.Insights/components", + "apiVersion": "2015-05-01", + "name": "[variables('applicationInsightsName')]", + "location": "[if(or(equals(parameters('location'),'eastus2'),equals(parameters('location'),'westcentralus')),'southcentralus',parameters('location'))]", + "kind": "web", + "properties": { + "Application_Type": "web" + } + }, + { + "type": "Microsoft.ContainerRegistry/registries", + "apiVersion": "2017-10-01", + "name": "[variables('containerRegistryName')]", + "location": "[parameters('location')]", + "sku": { + "name": "Standard" + }, + "properties": { + "adminUserEnabled": true + } + }, + { + "type": "Microsoft.MachineLearningServices/workspaces", + "apiVersion": "2018-11-19", + "name": "[variables('amlWorkspaceName')]", + "location": "[parameters('location')]", + "dependsOn": [ + "[resourceId('Microsoft.Storage/storageAccounts', variables('storageAccountName'))]", + "[resourceId('Microsoft.KeyVault/vaults', variables('keyVaultName'))]", + "[resourceId('Microsoft.Insights/components', variables('applicationInsightsName'))]", + "[resourceId('Microsoft.ContainerRegistry/registries', variables('containerRegistryName'))]" + ], + "identity": { + "type": "systemAssigned" + }, + "properties": { + "friendlyName": "[variables('amlWorkspaceName')]", + "keyVault": "[resourceId('Microsoft.KeyVault/vaults',variables('keyVaultName'))]", + "applicationInsights": "[resourceId('Microsoft.Insights/components',variables('applicationInsightsName'))]", + "containerRegistry": "[resourceId('Microsoft.ContainerRegistry/registries',variables('containerRegistryName'))]", + "storageAccount": "[resourceId('Microsoft.Storage/storageAccounts/',variables('storageAccountName'))]" + } + } + ] +} \ No newline at end of file diff --git a/environment_setup/iac-create-environment.yml b/environment_setup/iac-create-environment.yml new file mode 100644 index 00000000..fffaf066 --- /dev/null +++ b/environment_setup/iac-create-environment.yml @@ -0,0 +1,31 @@ +trigger: + branches: + include: + - master + paths: + include: + - environment_setup/arm-templates/* + +pool: + vmImage: 'ubuntu-latest' + +variables: + baseName: $[coalesce(variables['baseNameOverride'], 'mlops')] + location: $[coalesce(variables['locationOverride'], 'centralus')] + azuresub: $[coalesce(variables['azuresubOverride'], 'davete02_sub')] + + +steps: +- task: AzureResourceGroupDeployment@2 + inputs: + azureSubscription: $(azuresub) + action: 'Create Or Update Resource Group' + resourceGroupName: '$(baseName)-AML-RG' + location: $(location) + templateLocation: 'Linked artifact' + csmFile: '$(Build.SourcesDirectory)/environment_setup/arm-templates/cloud-environment.json' + overrideParameters: '-baseName $(baseName)' + deploymentMode: 'Incremental' + displayName: 'Deploy MLOps resources to Azure' + + \ No newline at end of file diff --git a/environment_setup/iac-remove-environment.yml b/environment_setup/iac-remove-environment.yml new file mode 100644 index 00000000..aaf6f060 --- /dev/null +++ b/environment_setup/iac-remove-environment.yml @@ -0,0 +1,27 @@ +trigger: + branches: + include: + - master + paths: + include: + - environment_setup/arm-templates/* + +pool: + vmImage: 'ubuntu-latest' + +variables: + baseName: $[coalesce(variables['baseNameOverride'], 'mlops')] + location: $[coalesce(variables['locationOverride'], 'centralus')] + azuresub: $[coalesce(variables['azuresubOverride'], 'davete02_sub')] + + +steps: +- task: AzureResourceGroupDeployment@2 + inputs: + azureSubscription: $(azuresub) + action: 'DeleteRG' + resourceGroupName: '$(baseName)-AML-RG' + location: $(location) + displayName: 'Delete resources in Azure' + + \ No newline at end of file From 791e1b54b9100a7766153edbd3ae63bd655970a5 Mon Sep 17 00:00:00 2001 From: Eugene Fedorenko Date: Wed, 31 Jul 2019 11:59:11 -0700 Subject: [PATCH 013/113] URL to the image on Dockerhub --- environment_setup/Dockerfile | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/environment_setup/Dockerfile b/environment_setup/Dockerfile index e65c7ca5..b6b3be6a 100644 --- a/environment_setup/Dockerfile +++ b/environment_setup/Dockerfile @@ -1,7 +1,7 @@ FROM conda/miniconda3 LABEL org.label-schema.vendor = "Microsoft" \ - org.label-schema.url = "dockerhub" \ + org.label-schema.url = "https://hub.docker.com/r/microsoft/mlopspython" \ org.label-schema.vcs-url = "https://github.com/microsoft/MLOpsPython" From b327ac4afef64ad8ffde3f80326060b9ce789f5a Mon Sep 17 00:00:00 2001 From: sushantdivate Date: Thu, 1 Aug 2019 14:46:12 -0700 Subject: [PATCH 014/113] intial repo --- aml_pipelines/model_train_pipeline.py | 121 +++++++++++++++++ aml_service/{ => archived}/00-WorkSpace.py | 0 aml_service/{ => archived}/01-Experiment.py | 0 .../{ => archived}/02-AttachTrainingVM.py | 0 .../{ => archived}/03-AttachAmlCluster.py | 0 aml_service/{ => archived}/04-AmlPipelines.py | 0 .../{ => archived}/05-TriggerAmlPipeline.py | 0 aml_service/{ => archived}/10-TrainOnLocal.py | 0 .../{ => archived}/11-TrainOnLocalEnv.py | 0 aml_service/{ => archived}/12-TrainOnVM.py | 0 .../{ => archived}/15-EvaluateModel.py | 0 .../{ => archived}/20-RegisterModel.py | 0 .../{ => archived}/30-CreateScoringImage.py | 0 .../{ => archived}/34-GetScoringImageName.py | 0 aml_service/{ => archived}/50-deployOnAci.py | 0 aml_service/{ => archived}/51-deployOnAks.py | 0 .../{ => archived}/60-AciWebserviceTest.py | 0 .../{ => archived}/61-AksWebserviceTest.py | 0 aml_service/{ => archived}/helper/azcli.py | 0 aml_service/attach_compute.py | 46 +++++++ aml_service/register_model.py | 61 +++++++++ aml_service/workspace.py | 29 +++++ azdo_pipelines/base-pipeline.yml | 25 ++++ azdo_pipelines/build-train.yml | 36 +++++ azdo_pipelines/ci-build-score.yml | 19 +++ azdo_pipelines/ci-build.yml | 14 ++ .../docker-builder-image-pipeline.yml | 17 +++ azdo_pipelines/iac-pipeline-arm.yml | 35 +++++ azdo_pipelines/pr-build-score.yml | 18 +++ azdo_pipelines/pr-build-train.yml | 19 +++ .../docker-builder-image-template.yml | 10 ++ environment_setup/requirements.txt | 5 - iac/arm-templates/cloud-environment.json | 123 ++++++++++++++++++ requirements.txt | 10 ++ 34 files changed, 583 insertions(+), 5 deletions(-) create mode 100644 aml_pipelines/model_train_pipeline.py rename aml_service/{ => archived}/00-WorkSpace.py (100%) rename aml_service/{ => archived}/01-Experiment.py (100%) rename aml_service/{ => archived}/02-AttachTrainingVM.py (100%) rename aml_service/{ => archived}/03-AttachAmlCluster.py (100%) rename aml_service/{ => archived}/04-AmlPipelines.py (100%) rename aml_service/{ => archived}/05-TriggerAmlPipeline.py (100%) rename aml_service/{ => archived}/10-TrainOnLocal.py (100%) rename aml_service/{ => archived}/11-TrainOnLocalEnv.py (100%) rename aml_service/{ => archived}/12-TrainOnVM.py (100%) rename aml_service/{ => archived}/15-EvaluateModel.py (100%) rename aml_service/{ => archived}/20-RegisterModel.py (100%) rename aml_service/{ => archived}/30-CreateScoringImage.py (100%) rename aml_service/{ => archived}/34-GetScoringImageName.py (100%) rename aml_service/{ => archived}/50-deployOnAci.py (100%) rename aml_service/{ => archived}/51-deployOnAks.py (100%) rename aml_service/{ => archived}/60-AciWebserviceTest.py (100%) rename aml_service/{ => archived}/61-AksWebserviceTest.py (100%) rename aml_service/{ => archived}/helper/azcli.py (100%) create mode 100644 aml_service/attach_compute.py create mode 100644 aml_service/register_model.py create mode 100644 aml_service/workspace.py create mode 100644 azdo_pipelines/base-pipeline.yml create mode 100644 azdo_pipelines/build-train.yml create mode 100644 azdo_pipelines/ci-build-score.yml create mode 100644 azdo_pipelines/ci-build.yml create mode 100644 azdo_pipelines/docker-builder-image-pipeline.yml create mode 100644 azdo_pipelines/iac-pipeline-arm.yml create mode 100644 azdo_pipelines/pr-build-score.yml create mode 100644 azdo_pipelines/pr-build-train.yml create mode 100644 azdo_pipelines/templates/docker-builder-image-template.yml delete mode 100644 environment_setup/requirements.txt create mode 100644 iac/arm-templates/cloud-environment.json create mode 100644 requirements.txt diff --git a/aml_pipelines/model_train_pipeline.py b/aml_pipelines/model_train_pipeline.py new file mode 100644 index 00000000..6c88aab7 --- /dev/null +++ b/aml_pipelines/model_train_pipeline.py @@ -0,0 +1,121 @@ + +from azureml.core.authentication import AzureCliAuthentication +from azureml.core.compute import ComputeTarget +from azureml.pipeline.core.graph import PipelineParameter +from azureml.pipeline.core import PublishedPipeline +from azureml.pipeline.steps import PythonScriptStep +from azureml.pipeline.core import Pipeline, PipelineData, StepSequence +from azureml.data.data_reference import DataReference +from azureml.core.runconfig import RunConfiguration, CondaDependencies +from azureml.core import Workspace, Experiment, Datastore +import argparse +import datetime +import requests +import json +import os +import sys +sys.path.append(os.path.abspath("./aml_service")) # NOQA: E402 +from workspace import get_workspace +from attach_compute import get_compute + + +def main(): + load_dotenv() + workspace_name = os.environ.get("AML_WORKSPACE_NAME") + resource_group = os.environ.get("RESOURCE_GROUP") + subscription_id = os.environ.get("SUBSCRIPTION_ID") + tenant_id = os.environ.get("TENANT_ID") + app_id = os.environ.get("SP_APP_ID") + app_secret = os.environ.get("SP_APP_SECRET") + sources_directory_train = os.environ.get("SOURCES_DIR_Train") + vm_size_cpu = os.environ.get("AML_COMPUTE_CLUSTER_CPU_SKU") + compute_name_cpu = os.environ.get("AML_COMPUTE_CLUSTER_NAME") + experiment_name = os.environ.get("EXPERIMENT_NAME") + + # Get Azure machine learning workspace + aml_workspace = get_workspace( + workspace_name, + resource_group, + subscription_id, + tenant_id, + app_id, + app_secret) + print(aml_workspace) + + # Get Azure machine learning cluster + aml_compute_cpu = get_compute( + aml_workspace, + compute_name_cpu, + vm_size_cpu) + if aml_compute_cpu is not None: + print(aml_compute_cpu) + + # working + + # run_config = RunConfiguration(conda_dependencies=CondaDependencies.create( + # conda_packages=['numpy', 'pandas', + # 'scikit-learn', 'tensorflow', 'keras'], + # pip_packages=['azure', 'azureml-core', + # 'azure-storage', + # 'azure-storage-blob']) + # ) + # #run_config.environment.docker.enabled = True + + # Create python script step to run the training/scoring main script + train_step = PythonScriptStep( + name="Train Model", + script_name="training/train.py", + compute_target=aml_compute, + source_directory=source_directory, + arguments=[ + "--config_suffix", config_suffix, + "--json_config", jsonconfigs, + "--model_name", model_name, + ], + runconfig=run_config, + # inputs=[jsonconfigs], + outputs=[jsonconfigs], + allow_reuse=False, + ) + print("Step Train created") + + evaluate_step = PythonScriptStep( + name="Evaluate Model ", + script_name="evaluate/evaluate_model.py", + compute_target=aml_compute, + source_directory=source_directory, + arguments=[ + "--config_suffix", config_suffix, + "--json_config", jsonconfigs, + ], + runconfig=run_config, + inputs=[jsonconfigs], + # outputs=[jsonconfigs], + allow_reuse=False, + ) + print("Step Evaluate created") + + register_model_step = PythonScriptStep( + name="Register New Trained Model", + script_name="register/register_model.py", + compute_target=aml_compute, + source_directory=source_directory, + arguments=[ + "--config_suffix", config_suffix, + "--json_config", jsonconfigs, + "--model_name", model_name, + ], + runconfig=run_config, + inputs=[jsonconfigs], + # outputs=[jsonconfigs], + allow_reuse=False, + ) + print("Step register model created") + + evaluate_step.run_after(train_step) + register_model_step.run_after(evaluate_step) + steps = [register_model_step] + + train_pipeline = Pipeline(workspace=aml_workspace, steps=steps) + train_pipeline.validate() + pipeline_run = train_pipeline.submit(experiment_name=experiment_name) diff --git a/aml_service/00-WorkSpace.py b/aml_service/archived/00-WorkSpace.py similarity index 100% rename from aml_service/00-WorkSpace.py rename to aml_service/archived/00-WorkSpace.py diff --git a/aml_service/01-Experiment.py b/aml_service/archived/01-Experiment.py similarity index 100% rename from aml_service/01-Experiment.py rename to aml_service/archived/01-Experiment.py diff --git a/aml_service/02-AttachTrainingVM.py b/aml_service/archived/02-AttachTrainingVM.py similarity index 100% rename from aml_service/02-AttachTrainingVM.py rename to aml_service/archived/02-AttachTrainingVM.py diff --git a/aml_service/03-AttachAmlCluster.py b/aml_service/archived/03-AttachAmlCluster.py similarity index 100% rename from aml_service/03-AttachAmlCluster.py rename to aml_service/archived/03-AttachAmlCluster.py diff --git a/aml_service/04-AmlPipelines.py b/aml_service/archived/04-AmlPipelines.py similarity index 100% rename from aml_service/04-AmlPipelines.py rename to aml_service/archived/04-AmlPipelines.py diff --git a/aml_service/05-TriggerAmlPipeline.py b/aml_service/archived/05-TriggerAmlPipeline.py similarity index 100% rename from aml_service/05-TriggerAmlPipeline.py rename to aml_service/archived/05-TriggerAmlPipeline.py diff --git a/aml_service/10-TrainOnLocal.py b/aml_service/archived/10-TrainOnLocal.py similarity index 100% rename from aml_service/10-TrainOnLocal.py rename to aml_service/archived/10-TrainOnLocal.py diff --git a/aml_service/11-TrainOnLocalEnv.py b/aml_service/archived/11-TrainOnLocalEnv.py similarity index 100% rename from aml_service/11-TrainOnLocalEnv.py rename to aml_service/archived/11-TrainOnLocalEnv.py diff --git a/aml_service/12-TrainOnVM.py b/aml_service/archived/12-TrainOnVM.py similarity index 100% rename from aml_service/12-TrainOnVM.py rename to aml_service/archived/12-TrainOnVM.py diff --git a/aml_service/15-EvaluateModel.py b/aml_service/archived/15-EvaluateModel.py similarity index 100% rename from aml_service/15-EvaluateModel.py rename to aml_service/archived/15-EvaluateModel.py diff --git a/aml_service/20-RegisterModel.py b/aml_service/archived/20-RegisterModel.py similarity index 100% rename from aml_service/20-RegisterModel.py rename to aml_service/archived/20-RegisterModel.py diff --git a/aml_service/30-CreateScoringImage.py b/aml_service/archived/30-CreateScoringImage.py similarity index 100% rename from aml_service/30-CreateScoringImage.py rename to aml_service/archived/30-CreateScoringImage.py diff --git a/aml_service/34-GetScoringImageName.py b/aml_service/archived/34-GetScoringImageName.py similarity index 100% rename from aml_service/34-GetScoringImageName.py rename to aml_service/archived/34-GetScoringImageName.py diff --git a/aml_service/50-deployOnAci.py b/aml_service/archived/50-deployOnAci.py similarity index 100% rename from aml_service/50-deployOnAci.py rename to aml_service/archived/50-deployOnAci.py diff --git a/aml_service/51-deployOnAks.py b/aml_service/archived/51-deployOnAks.py similarity index 100% rename from aml_service/51-deployOnAks.py rename to aml_service/archived/51-deployOnAks.py diff --git a/aml_service/60-AciWebserviceTest.py b/aml_service/archived/60-AciWebserviceTest.py similarity index 100% rename from aml_service/60-AciWebserviceTest.py rename to aml_service/archived/60-AciWebserviceTest.py diff --git a/aml_service/61-AksWebserviceTest.py b/aml_service/archived/61-AksWebserviceTest.py similarity index 100% rename from aml_service/61-AksWebserviceTest.py rename to aml_service/archived/61-AksWebserviceTest.py diff --git a/aml_service/helper/azcli.py b/aml_service/archived/helper/azcli.py similarity index 100% rename from aml_service/helper/azcli.py rename to aml_service/archived/helper/azcli.py diff --git a/aml_service/attach_compute.py b/aml_service/attach_compute.py new file mode 100644 index 00000000..ff9d0ebd --- /dev/null +++ b/aml_service/attach_compute.py @@ -0,0 +1,46 @@ +import os +from dotenv import load_dotenv +from azureml.core import Workspace +from azureml.core.compute import AmlCompute +from azureml.core.compute import ComputeTarget +from azureml.exceptions import ComputeTargetException + + +def get_compute( + workspace: Workspace, + compute_name: str, + vm_size: str +): + # Load the environment variables from .env in case this script + # is called outside an existing process + load_dotenv() + # Verify that cluster does not exist already + try: + if compute_name in workspace.compute_targets: + compute_target = workspace.compute_targets[compute_name] + if compute_target and type(compute_target) is AmlCompute: + print('Found existing compute target ' + compute_name + + ' so using it.') + else: + compute_config = AmlCompute.provisioning_configuration( + vm_size=vm_size, + vm_priority=os.environ.get("AML_CLUSTER_PRIORITY", + 'lowpriority'), + min_nodes=int(os.environ.get("AML_CLUSTER_MIN_NODES", 0)), + max_nodes=int(os.environ.get("AML_CLUSTER_MAX_NODES", 4)), + idle_seconds_before_scaledown="300" + # #Uncomment the below lines for VNet support + # vnet_resourcegroup_name=vnet_resourcegroup_name, + # vnet_name=vnet_name, + # subnet_name=subnet_name + ) + compute_target = ComputeTarget.create(workspace, compute_name, + compute_config) + compute_target.wait_for_completion( + show_output=True, + min_node_count=None, + timeout_in_minutes=10) + return compute_target + except ComputeTargetException: + print('An error occurred trying to provision compute.') + exit() diff --git a/aml_service/register_model.py b/aml_service/register_model.py new file mode 100644 index 00000000..eb2d7878 --- /dev/null +++ b/aml_service/register_model.py @@ -0,0 +1,61 @@ +import sys +import os.path +import argparse +from dotenv import load_dotenv +from azureml.core import Workspace +from azureml.core.model import Model +from azureml.core.authentication import ServicePrincipalAuthentication + +# Load the environment variables from .env in case this script +# is called outside an existing process +load_dotenv() + +PARSER = argparse.ArgumentParser() +PARSER.add_argument('--TENANT_ID') +PARSER.add_argument('--APP_ID') +PARSER.add_argument('--APP_SECRET') +PARSER.add_argument('--MODEL_PATH') +PARSER.add_argument('--MODEL_NAME') +PARSER.add_argument('--AZUREML_ARM_WORKSPACE_NAME') +PARSER.add_argument('--AZUREML_ARM_SUBSCRIPTION') +PARSER.add_argument('--AZUREML_ARM_RESOURCEGROUP') + + +ARGS = PARSER.parse_args() +TENANT_ID = ARGS.TENANT_ID +APP_ID = ARGS.APP_ID +APP_SECRET = ARGS.APP_SECRET +MODEL_PATH = ARGS.MODEL_PATH +MODEL_NAME = ARGS.MODEL_NAME +WORKSPACE_NAME = ARGS.AZUREML_ARM_WORKSPACE_NAME +SUBSCRIPTION_ID = ARGS.AZUREML_ARM_SUBSCRIPTION +RESOURCE_GROUP = ARGS.AZUREML_ARM_RESOURCEGROUP + + +if os.path.isfile(MODEL_PATH) is False: + print("The given model path %s is invalid" % (MODEL_PATH)) + sys.exit(1) + +SP_AUTH = ServicePrincipalAuthentication( + tenant_id=TENANT_ID, + service_principal_id=APP_ID, + service_principal_password=APP_SECRET) + +WORKSPACE = Workspace.get( + WORKSPACE_NAME, + SP_AUTH, + SUBSCRIPTION_ID, + RESOURCE_GROUP +) + +try: + MODEL = Model.register( + model_path=MODEL_PATH, + model_name=MODEL_NAME, + description="Pepsi Forecasting Model", + workspace=WORKSPACE) + + print("Model registered successfully. ID: " + MODEL.id) +except Exception as caught_error: + print("Error while registering the model: " + str(caught_error)) + sys.exit(1) diff --git a/aml_service/workspace.py b/aml_service/workspace.py new file mode 100644 index 00000000..08d1f67d --- /dev/null +++ b/aml_service/workspace.py @@ -0,0 +1,29 @@ +import sys +from azureml.core import Workspace +from azureml.core.authentication import ServicePrincipalAuthentication + + +def get_workspace( + name: str, + resource_group: str, + subscription_id: str, + tenant_id: str, + app_id: str, + app_secret: str): + service_principal = ServicePrincipalAuthentication( + tenant_id=tenant_id, + service_principal_id=app_id, + service_principal_password=app_secret) + + try: + aml_workspace = Workspace.get( + name=name, + subscription_id=subscription_id, + resource_group=resource_group, + auth=service_principal) + + return aml_workspace + except Exception as caught_exception: + print("Error while retrieving Workspace...") + print(str(caught_exception)) + sys.exit(1) diff --git a/azdo_pipelines/base-pipeline.yml b/azdo_pipelines/base-pipeline.yml new file mode 100644 index 00000000..d2f6ae7d --- /dev/null +++ b/azdo_pipelines/base-pipeline.yml @@ -0,0 +1,25 @@ +parameters: + requirementsPath: 'requirements.txt' + pipelineType: 'train' + +steps: +- script: | + flake8 --output-file=$(Build.BinariesDirectory)/flake8_amlservice_testresults.xml aml_service + flake8 --output-file=$(Build.BinariesDirectory)/flake8_tests_testresults.xml tests + workingDirectory: '$(Build.SourcesDirectory)/Code' + displayName: 'Run code quality tests' + enabled: 'true' + +- script: | + pytest --junitxml=$(Build.BinariesDirectory)/unittest-results.xml $(Build.SourcesDirectory)/Code/tests/unit/${{parameters.pipelineType}} + displayName: 'Run unit tests' + enabled: 'true' + +- task: PublishTestResults@2 + condition: succeededOrFailed() + inputs: + testResultsFiles: '$(Build.BinariesDirectory)/*_testresults.xml' + testRunTitle: 'Unit tests' + failTaskOnFailedTests: true + displayName: 'Publish unit test results' + enabled: 'true' diff --git a/azdo_pipelines/build-train.yml b/azdo_pipelines/build-train.yml new file mode 100644 index 00000000..87a33d5b --- /dev/null +++ b/azdo_pipelines/build-train.yml @@ -0,0 +1,36 @@ +pr: none +trigger: + branches: + include: + - master + +pool: + vmImage: 'ubuntu-latest' + + +container: + image: $(FULL_AGENT_IMAGE_NAME) + endpoint: acrconnection + + +variables: + SOURCES_DIR: $[coalesce(variables['SOURCES_DIR_OVERRIDE'], '$(Build.SourcesDirectory)/Code/src/train')] + TRAIN_SCRIPT_PATH: $[coalesce(variables['TRAIN_SCRIPT_PATH_OVERRIDE'], 'src/train/train.py')] + + +steps: +- template: base-pipeline.yml + parameters: + requirementsPath: 'requirements.txt' + +- bash: | + # Invoke the Python training pipeline + + python3 $(Build.SourcesDirectory)/Code/aml_service/pipelines/train_pipeline.py + failOnStderr: 'false' + env: + SOURCES_DIR: '$(Build.SourcesDirectory)' + SP_APP_SECRET: '$(SP_APP_SECRET)' + BLOB_STORAGE_Key: '$(BLOB_STORAGE_Key)' + displayName: 'Train model using AML with Remote Compute' + enabled: 'true' \ No newline at end of file diff --git a/azdo_pipelines/ci-build-score.yml b/azdo_pipelines/ci-build-score.yml new file mode 100644 index 00000000..61e7ba79 --- /dev/null +++ b/azdo_pipelines/ci-build-score.yml @@ -0,0 +1,19 @@ +pr: +- master + +pool: + vmImage: 'ubuntu-latest' + +container: + image: $(FULL_AGENT_IMAGE_NAME) + endpoint: acrconnection + + +steps: +- template: base-pipeline.yml + parameters: + requirementsPath: 'requirements.txt' + pipelineType: 'score' + +- publish: $(Build.SourcesDirectory)/Code/src/score + artifact: 'scoring_pipeline' diff --git a/azdo_pipelines/ci-build.yml b/azdo_pipelines/ci-build.yml new file mode 100644 index 00000000..a1ff4d9c --- /dev/null +++ b/azdo_pipelines/ci-build.yml @@ -0,0 +1,14 @@ +pr: +- master + +pool: + vmImage: 'ubuntu-latest' + +container: + image: $(FULL_AGENT_IMAGE_NAME) + endpoint: acrconnection + +steps: +- template: base-pipeline.yml + parameters: + requirementsPath: 'requirements.txt' \ No newline at end of file diff --git a/azdo_pipelines/docker-builder-image-pipeline.yml b/azdo_pipelines/docker-builder-image-pipeline.yml new file mode 100644 index 00000000..00dafc9b --- /dev/null +++ b/azdo_pipelines/docker-builder-image-pipeline.yml @@ -0,0 +1,17 @@ +trigger: none +pr: + branches: + include: + - master + +pool: + vmImage: 'ubuntu-latest' + +variables: + baseName: $[coalesce(variables['baseNameOverride'], 'pepsiml')] + containerRegistry: $[coalesce(variables['acrServiceConnection'], 'acrconnection')] + imageName: $[coalesce(variables['builderImageName'], 'mlopsbuildagent')] + + +steps: + - template: templates/docker-builder-image-template.yml diff --git a/azdo_pipelines/iac-pipeline-arm.yml b/azdo_pipelines/iac-pipeline-arm.yml new file mode 100644 index 00000000..dfc075da --- /dev/null +++ b/azdo_pipelines/iac-pipeline-arm.yml @@ -0,0 +1,35 @@ +trigger: + branches: + include: + - master + paths: + include: + - iac/arm-templates/* + +pool: + vmImage: 'ubuntu-latest' + +variables: + baseName: $[coalesce(variables['baseNameOverride'], 'pepsiml')] + location: $[coalesce(variables['locationOverride'], 'centralus')] + azuresub: $[coalesce(variables['azuresubOverride'], 'davete02_TED')] + containerRegistry: $[coalesce(variables['acrServiceConnection'], 'acrconnection')] + imageName: $[coalesce(variables['builderImageName'], 'mlopsbuildagent')] + + +steps: +- task: AzureResourceGroupDeployment@2 + inputs: + azureSubscription: $(azuresub) + action: 'Create Or Update Resource Group' + resourceGroupName: '$(baseName)-AML-RG' + location: $(location) + templateLocation: 'Linked artifact' + csmFile: '$(Build.SourcesDirectory)/Code/iac/arm-templates/cloud-environment.json' + overrideParameters: '-baseName $(baseName)' + deploymentMode: 'Incremental' + displayName: 'Deploy MLOps resources to Azure' + +- template: templates/docker-builder-image-template.yml + + \ No newline at end of file diff --git a/azdo_pipelines/pr-build-score.yml b/azdo_pipelines/pr-build-score.yml new file mode 100644 index 00000000..855044d7 --- /dev/null +++ b/azdo_pipelines/pr-build-score.yml @@ -0,0 +1,18 @@ +trigger: none +pr: + branches: + include: + - master + +pool: + vmImage: 'ubuntu-latest' + +container: + image: $(FULL_AGENT_IMAGE_NAME) + endpoint: acrconnection + +steps: +- template: base-pipeline.yml + parameters: + requirementsPath: 'requirements.txt' + pipelineType: 'score' \ No newline at end of file diff --git a/azdo_pipelines/pr-build-train.yml b/azdo_pipelines/pr-build-train.yml new file mode 100644 index 00000000..607ea133 --- /dev/null +++ b/azdo_pipelines/pr-build-train.yml @@ -0,0 +1,19 @@ +trigger: none +pr: + branches: + include: + - master + +pool: + vmImage: 'ubuntu-latest' + + +container: + image: $(FULL_AGENT_IMAGE_NAME) + endpoint: acrconnection + + +steps: +- template: base-pipeline.yml + parameters: + requirementsPath: 'requirements.txt' \ No newline at end of file diff --git a/azdo_pipelines/templates/docker-builder-image-template.yml b/azdo_pipelines/templates/docker-builder-image-template.yml new file mode 100644 index 00000000..0640ff50 --- /dev/null +++ b/azdo_pipelines/templates/docker-builder-image-template.yml @@ -0,0 +1,10 @@ +steps: + - task: Docker@2 + displayName: Build and Push + inputs: + command: buildAndPush + containerRegistry: '$(containerRegistry)' + repository: '$(imageName)' + tags: 'latest' + buildContext: '$(Build.SourcesDirectory)/Code' + dockerFile: '$(Build.SourcesDirectory)/Code/build_agent/Dockerfile' \ No newline at end of file diff --git a/environment_setup/requirements.txt b/environment_setup/requirements.txt deleted file mode 100644 index b3c2a14c..00000000 --- a/environment_setup/requirements.txt +++ /dev/null @@ -1,5 +0,0 @@ -scipy==1.0.0 -scikit-learn==0.19.1 -numpy==1.14.5 -pandas==0.23.1 -pytest==4.3.0 \ No newline at end of file diff --git a/iac/arm-templates/cloud-environment.json b/iac/arm-templates/cloud-environment.json new file mode 100644 index 00000000..8fd905cb --- /dev/null +++ b/iac/arm-templates/cloud-environment.json @@ -0,0 +1,123 @@ +{ + "$schema": "https://schema.management.azure.com/schemas/2015-01-01/deploymentTemplate.json#", + "contentVersion": "1.0.0.0", + "parameters": { + "baseName": { + "type": "string", + "maxLength": 10, + "minLength": 3, + "metadata": { + "description": "The base name to use as prefix to create all the resources." + } + }, + "location": { + "type": "string", + "defaultValue": "eastus", + "allowedValues": [ + "eastus", + "eastus2", + "southcentralus", + "southeastasia", + "westcentralus", + "westeurope", + "westus2" + ], + "metadata": { + "description": "Specifies the location for all resources." + } + } + }, + "variables": { + "amlWorkspaceName": "[concat(parameters('baseName'),'-AML-WS')]", + "storageAccountName": "[concat(toLower(parameters('baseName')), 'amlsa')]", + "storageAccountType": "Standard_LRS", + "keyVaultName": "[concat(parameters('baseName'),'-AML-KV')]", + "tenantId": "[subscription().tenantId]", + "applicationInsightsName": "[concat(parameters('baseName'),'-AML-AI')]", + "containerRegistryName": "[concat(toLower(parameters('baseName')),'amlcr')]" + }, + "resources": [ + { + "type": "Microsoft.Storage/storageAccounts", + "apiVersion": "2018-07-01", + "name": "[variables('storageAccountName')]", + "location": "[parameters('location')]", + "sku": { + "name": "[variables('storageAccountType')]" + }, + "kind": "StorageV2", + "properties": { + "encryption": { + "services": { + "blob": { + "enabled": true + }, + "file": { + "enabled": true + } + }, + "keySource": "Microsoft.Storage" + }, + "supportsHttpsTrafficOnly": true + } + }, + { + "type": "Microsoft.KeyVault/vaults", + "apiVersion": "2018-02-14", + "name": "[variables('keyVaultName')]", + "location": "[parameters('location')]", + "properties": { + "tenantId": "[variables('tenantId')]", + "sku": { + "name": "standard", + "family": "A" + }, + "accessPolicies": [] + } + }, + { + "type": "Microsoft.Insights/components", + "apiVersion": "2015-05-01", + "name": "[variables('applicationInsightsName')]", + "location": "[if(or(equals(parameters('location'),'eastus2'),equals(parameters('location'),'westcentralus')),'southcentralus',parameters('location'))]", + "kind": "web", + "properties": { + "Application_Type": "web" + } + }, + { + "type": "Microsoft.ContainerRegistry/registries", + "apiVersion": "2017-10-01", + "name": "[variables('containerRegistryName')]", + "location": "[parameters('location')]", + "sku": { + "name": "Standard" + }, + "properties": { + "adminUserEnabled": true + } + }, + { + "type": "Microsoft.MachineLearningServices/workspaces", + "apiVersion": "2018-11-19", + "name": "[variables('amlWorkspaceName')]", + "location": "[parameters('location')]", + "dependsOn": [ + "[resourceId('Microsoft.Storage/storageAccounts', variables('storageAccountName'))]", + "[resourceId('Microsoft.KeyVault/vaults', variables('keyVaultName'))]", + "[resourceId('Microsoft.Insights/components', variables('applicationInsightsName'))]", + "[resourceId('Microsoft.ContainerRegistry/registries', variables('containerRegistryName'))]" + ], + "identity": { + "type": "systemAssigned" + }, + "properties": { + "friendlyName": "[variables('amlWorkspaceName')]", + "keyVault": "[resourceId('Microsoft.KeyVault/vaults',variables('keyVaultName'))]", + "applicationInsights": "[resourceId('Microsoft.Insights/components',variables('applicationInsightsName'))]", + "containerRegistry": "[resourceId('Microsoft.ContainerRegistry/registries',variables('containerRegistryName'))]", + "storageAccount": "[resourceId('Microsoft.Storage/storageAccounts/',variables('storageAccountName'))]" + } + } + ] +} \ No newline at end of file diff --git a/requirements.txt b/requirements.txt new file mode 100644 index 00000000..f92f52ab --- /dev/null +++ b/requirements.txt @@ -0,0 +1,10 @@ +scipy==1.0.0 +scikit-learn==0.19.1 +numpy==1.14.5 +pandas==0.23.1 +pytest==4.3.0 +requests>=2.22 #.0 +azureml>=0.2 #.7 +azureml-core>=1.0 #.45 +azureml-pipeline>=1.0 #.45 +python-dotenv>=0.10.3 From 34e6af7e575cf28511c4336d1dea1474acff3866 Mon Sep 17 00:00:00 2001 From: Eugene Fedorenko Date: Thu, 1 Aug 2019 16:25:41 -0700 Subject: [PATCH 015/113] first yry --- aml_pipelines/garbage.py | 122 +++++++++++++++++++++ aml_pipelines/model_train_pipeline.py | 133 +++++++++-------------- azdo_pipelines/build-train.yml | 4 +- iac/arm-templates/cloud-environment.json | 123 --------------------- 4 files changed, 174 insertions(+), 208 deletions(-) create mode 100644 aml_pipelines/garbage.py delete mode 100644 iac/arm-templates/cloud-environment.json diff --git a/aml_pipelines/garbage.py b/aml_pipelines/garbage.py new file mode 100644 index 00000000..49e2d188 --- /dev/null +++ b/aml_pipelines/garbage.py @@ -0,0 +1,122 @@ + +from azureml.core.authentication import AzureCliAuthentication +from azureml.core.compute import ComputeTarget +from azureml.pipeline.core.graph import PipelineParameter +from azureml.pipeline.core import PublishedPipeline +from azureml.pipeline.steps import PythonScriptStep +from azureml.pipeline.core import Pipeline, PipelineData, StepSequence +from azureml.data.data_reference import DataReference +from azureml.core.runconfig import RunConfiguration, CondaDependencies +from azureml.core import Workspace, Experiment, Datastore +import argparse +import datetime +import requests +import json +import os +import sys +sys.path.append(os.path.abspath("./aml_service")) # NOQA: E402 +from workspace import get_workspace +from attach_compute import get_compute + + +def main(): + load_dotenv() + workspace_name = os.environ.get("AML_WORKSPACE_NAME") + resource_group = os.environ.get("RESOURCE_GROUP") + subscription_id = os.environ.get("SUBSCRIPTION_ID") + tenant_id = os.environ.get("TENANT_ID") + app_id = os.environ.get("SP_APP_ID") + app_secret = os.environ.get("SP_APP_SECRET") + sources_directory_train = os.environ.get("SOURCES_DIR_Train") + vm_size_cpu = os.environ.get("AML_COMPUTE_CLUSTER_CPU_SKU") + compute_name_cpu = os.environ.get("AML_COMPUTE_CLUSTER_NAME") + experiment_name = os.environ.get("EXPERIMENT_NAME") + + # Get Azure machine learning workspace + aml_workspace = get_workspace( + workspace_name, + resource_group, + subscription_id, + tenant_id, + app_id, + app_secret) + print(aml_workspace) + + # Get Azure machine learning cluster + aml_compute_cpu = get_compute( + aml_workspace, + compute_name_cpu, + vm_size_cpu) + if aml_compute_cpu is not None: + print(aml_compute_cpu) + + # working + + # run_config = RunConfiguration(conda_dependencies=CondaDependencies.create( + # conda_packages=['numpy', 'pandas', + # 'scikit-learn', 'tensorflow', 'keras'], + # pip_packages=['azure', 'azureml-core', + # 'azure-storage', + # 'azure-storage-blob']) + # ) + # #run_config.environment.docker.enabled = True + + # Create python script step to run the training/scoring main script + + """ train_step = PythonScriptStep( + name="Train Model", + script_name="training/train.py", + compute_target=aml_compute, + source_directory=source_directory, + arguments=[ + "--config_suffix", config_suffix, + "--json_config", jsonconfigs, + "--model_name", model_name, + ], + runconfig=run_config, + # inputs=[jsonconfigs], + outputs=[jsonconfigs], + allow_reuse=False, + ) + print("Step Train created") + + evaluate_step = PythonScriptStep( + name="Evaluate Model ", + script_name="evaluate/evaluate_model.py", + compute_target=aml_compute, + source_directory=source_directory, + arguments=[ + "--config_suffix", config_suffix, + "--json_config", jsonconfigs, + ], + runconfig=run_config, + inputs=[jsonconfigs], + # outputs=[jsonconfigs], + allow_reuse=False, + ) + print("Step Evaluate created") + + register_model_step = PythonScriptStep( + name="Register New Trained Model", + script_name="register/register_model.py", + compute_target=aml_compute, + source_directory=source_directory, + arguments=[ + "--config_suffix", config_suffix, + "--json_config", jsonconfigs, + "--model_name", model_name, + ], + runconfig=run_config, + inputs=[jsonconfigs], + # outputs=[jsonconfigs], + allow_reuse=False, + ) + print("Step register model created") + + evaluate_step.run_after(train_step) + register_model_step.run_after(evaluate_step) + steps = [register_model_step] + + train_pipeline = Pipeline(workspace=aml_workspace, steps=steps) + train_pipeline.validate() + pipeline_run = train_pipeline.submit(experiment_name=experiment_name) """ diff --git a/aml_pipelines/model_train_pipeline.py b/aml_pipelines/model_train_pipeline.py index 6c88aab7..a2592578 100644 --- a/aml_pipelines/model_train_pipeline.py +++ b/aml_pipelines/model_train_pipeline.py @@ -1,4 +1,3 @@ - from azureml.core.authentication import AzureCliAuthentication from azureml.core.compute import ComputeTarget from azureml.pipeline.core.graph import PipelineParameter @@ -14,12 +13,12 @@ import json import os import sys +from dotenv import load_dotenv sys.path.append(os.path.abspath("./aml_service")) # NOQA: E402 from workspace import get_workspace from attach_compute import get_compute - -def main(): +def main(): load_dotenv() workspace_name = os.environ.get("AML_WORKSPACE_NAME") resource_group = os.environ.get("RESOURCE_GROUP") @@ -27,95 +26,63 @@ def main(): tenant_id = os.environ.get("TENANT_ID") app_id = os.environ.get("SP_APP_ID") app_secret = os.environ.get("SP_APP_SECRET") - sources_directory_train = os.environ.get("SOURCES_DIR_Train") + sources_directory_train = os.environ.get("SOURCES_DIR_TRAIN") vm_size_cpu = os.environ.get("AML_COMPUTE_CLUSTER_CPU_SKU") compute_name_cpu = os.environ.get("AML_COMPUTE_CLUSTER_NAME") experiment_name = os.environ.get("EXPERIMENT_NAME") # Get Azure machine learning workspace - aml_workspace = get_workspace( - workspace_name, - resource_group, - subscription_id, - tenant_id, - app_id, - app_secret) - print(aml_workspace) + #aml_workspace = get_workspace( + # workspace_name, + # resource_group, + # subscription_id, + # tenant_id, + # app_id, + # app_secret) + #print(aml_workspace) # Get Azure machine learning cluster - aml_compute_cpu = get_compute( - aml_workspace, - compute_name_cpu, - vm_size_cpu) - if aml_compute_cpu is not None: - print(aml_compute_cpu) - - # working - - # run_config = RunConfiguration(conda_dependencies=CondaDependencies.create( - # conda_packages=['numpy', 'pandas', - # 'scikit-learn', 'tensorflow', 'keras'], - # pip_packages=['azure', 'azureml-core', - # 'azure-storage', - # 'azure-storage-blob']) - # ) - # #run_config.environment.docker.enabled = True + #aml_compute_cpu = get_compute( + # aml_workspace, + # compute_name_cpu, + # vm_size_cpu) + #if aml_compute_cpu is not None: + # print(aml_compute_cpu) - # Create python script step to run the training/scoring main script - train_step = PythonScriptStep( - name="Train Model", - script_name="training/train.py", - compute_target=aml_compute, - source_directory=source_directory, - arguments=[ - "--config_suffix", config_suffix, - "--json_config", jsonconfigs, - "--model_name", model_name, - ], - runconfig=run_config, - # inputs=[jsonconfigs], - outputs=[jsonconfigs], - allow_reuse=False, - ) - print("Step Train created") + run_config = RunConfiguration(conda_dependencies=CondaDependencies.create( + conda_packages=['numpy', 'pandas', + 'scikit-learn', 'tensorflow', 'keras'], + pip_packages=['azure', 'azureml-core', + 'azure-storage', + 'azure-storage-blob']) + ) + run_config.environment.docker.enabled = True - evaluate_step = PythonScriptStep( - name="Evaluate Model ", - script_name="evaluate/evaluate_model.py", - compute_target=aml_compute, - source_directory=source_directory, - arguments=[ - "--config_suffix", config_suffix, - "--json_config", jsonconfigs, - ], - runconfig=run_config, - inputs=[jsonconfigs], - # outputs=[jsonconfigs], - allow_reuse=False, - ) - print("Step Evaluate created") + aml_compute_cpu=None + aml_workspace=None + model_name = PipelineParameter(name="model_name", default_value="sklearn_regression_model.pkl") + def_blob_store = Datastore(aml_workspace, "workspaceblobstore") + jsonconfigs = PipelineData("jsonconfigs", datastore=def_blob_store) + config_suffix = datetime.datetime.now().strftime("%Y%m%d%H") - register_model_step = PythonScriptStep( - name="Register New Trained Model", - script_name="register/register_model.py", - compute_target=aml_compute, - source_directory=source_directory, - arguments=[ - "--config_suffix", config_suffix, - "--json_config", jsonconfigs, - "--model_name", model_name, - ], - runconfig=run_config, - inputs=[jsonconfigs], - # outputs=[jsonconfigs], - allow_reuse=False, - ) - print("Step register model created") + train_step = PythonScriptStep( + name="Train Model", + script_name="training/train.py", + compute_target=aml_compute_cpu, + source_directory=sources_directory_train, + arguments=[ + "--config_suffix", config_suffix, + "--json_config", jsonconfigs, + "--model_name", model_name, + ], + runconfig=run_config, + # inputs=[jsonconfigs], + outputs=[jsonconfigs], + allow_reuse=False, + ) + print("Step Train created") - evaluate_step.run_after(train_step) - register_model_step.run_after(evaluate_step) - steps = [register_model_step] + print("hi") - train_pipeline = Pipeline(workspace=aml_workspace, steps=steps) - train_pipeline.validate() - pipeline_run = train_pipeline.submit(experiment_name=experiment_name) +if __name__ == '__main__': + main() \ No newline at end of file diff --git a/azdo_pipelines/build-train.yml b/azdo_pipelines/build-train.yml index 87a33d5b..5089ce33 100644 --- a/azdo_pipelines/build-train.yml +++ b/azdo_pipelines/build-train.yml @@ -9,7 +9,7 @@ pool: container: - image: $(FULL_AGENT_IMAGE_NAME) + image: pepsimlamlcr.azurecr.io/mlopsbuildagent:latest endpoint: acrconnection @@ -26,7 +26,7 @@ steps: - bash: | # Invoke the Python training pipeline - python3 $(Build.SourcesDirectory)/Code/aml_service/pipelines/train_pipeline.py + python3 $(Build.SourcesDirectory)/Code/aml_pipelines/model_train_pipeline.py failOnStderr: 'false' env: SOURCES_DIR: '$(Build.SourcesDirectory)' diff --git a/iac/arm-templates/cloud-environment.json b/iac/arm-templates/cloud-environment.json deleted file mode 100644 index 8fd905cb..00000000 --- a/iac/arm-templates/cloud-environment.json +++ /dev/null @@ -1,123 +0,0 @@ -{ - "$schema": "https://schema.management.azure.com/schemas/2015-01-01/deploymentTemplate.json#", - "contentVersion": "1.0.0.0", - "parameters": { - "baseName": { - "type": "string", - "maxLength": 10, - "minLength": 3, - "metadata": { - "description": "The base name to use as prefix to create all the resources." - } - }, - "location": { - "type": "string", - "defaultValue": "eastus", - "allowedValues": [ - "eastus", - "eastus2", - "southcentralus", - "southeastasia", - "westcentralus", - "westeurope", - "westus2" - ], - "metadata": { - "description": "Specifies the location for all resources." - } - } - }, - "variables": { - "amlWorkspaceName": "[concat(parameters('baseName'),'-AML-WS')]", - "storageAccountName": "[concat(toLower(parameters('baseName')), 'amlsa')]", - "storageAccountType": "Standard_LRS", - "keyVaultName": "[concat(parameters('baseName'),'-AML-KV')]", - "tenantId": "[subscription().tenantId]", - "applicationInsightsName": "[concat(parameters('baseName'),'-AML-AI')]", - "containerRegistryName": "[concat(toLower(parameters('baseName')),'amlcr')]" - }, - "resources": [ - { - "type": "Microsoft.Storage/storageAccounts", - "apiVersion": "2018-07-01", - "name": "[variables('storageAccountName')]", - "location": "[parameters('location')]", - "sku": { - "name": "[variables('storageAccountType')]" - }, - "kind": "StorageV2", - "properties": { - "encryption": { - "services": { - "blob": { - "enabled": true - }, - "file": { - "enabled": true - } - }, - "keySource": "Microsoft.Storage" - }, - "supportsHttpsTrafficOnly": true - } - }, - { - "type": "Microsoft.KeyVault/vaults", - "apiVersion": "2018-02-14", - "name": "[variables('keyVaultName')]", - "location": "[parameters('location')]", - "properties": { - "tenantId": "[variables('tenantId')]", - "sku": { - "name": "standard", - "family": "A" - }, - "accessPolicies": [] - } - }, - { - "type": "Microsoft.Insights/components", - "apiVersion": "2015-05-01", - "name": "[variables('applicationInsightsName')]", - "location": "[if(or(equals(parameters('location'),'eastus2'),equals(parameters('location'),'westcentralus')),'southcentralus',parameters('location'))]", - "kind": "web", - "properties": { - "Application_Type": "web" - } - }, - { - "type": "Microsoft.ContainerRegistry/registries", - "apiVersion": "2017-10-01", - "name": "[variables('containerRegistryName')]", - "location": "[parameters('location')]", - "sku": { - "name": "Standard" - }, - "properties": { - "adminUserEnabled": true - } - }, - { - "type": "Microsoft.MachineLearningServices/workspaces", - "apiVersion": "2018-11-19", - "name": "[variables('amlWorkspaceName')]", - "location": "[parameters('location')]", - "dependsOn": [ - "[resourceId('Microsoft.Storage/storageAccounts', variables('storageAccountName'))]", - "[resourceId('Microsoft.KeyVault/vaults', variables('keyVaultName'))]", - "[resourceId('Microsoft.Insights/components', variables('applicationInsightsName'))]", - "[resourceId('Microsoft.ContainerRegistry/registries', variables('containerRegistryName'))]" - ], - "identity": { - "type": "systemAssigned" - }, - "properties": { - "friendlyName": "[variables('amlWorkspaceName')]", - "keyVault": "[resourceId('Microsoft.KeyVault/vaults',variables('keyVaultName'))]", - "applicationInsights": "[resourceId('Microsoft.Insights/components',variables('applicationInsightsName'))]", - "containerRegistry": "[resourceId('Microsoft.ContainerRegistry/registries',variables('containerRegistryName'))]", - "storageAccount": "[resourceId('Microsoft.Storage/storageAccounts/',variables('storageAccountName'))]" - } - } - ] -} \ No newline at end of file From 792611f38667f8c07d7b13360876d7b37982ca16 Mon Sep 17 00:00:00 2001 From: Eugene Fedorenko Date: Thu, 1 Aug 2019 16:29:59 -0700 Subject: [PATCH 016/113] Update build-train.yml for Azure Pipelines --- azdo_pipelines/build-train.yml | 4 ---- 1 file changed, 4 deletions(-) diff --git a/azdo_pipelines/build-train.yml b/azdo_pipelines/build-train.yml index 5089ce33..1d5d0c48 100644 --- a/azdo_pipelines/build-train.yml +++ b/azdo_pipelines/build-train.yml @@ -19,10 +19,6 @@ variables: steps: -- template: base-pipeline.yml - parameters: - requirementsPath: 'requirements.txt' - - bash: | # Invoke the Python training pipeline From 18bbb53f49f5c0e17ec9659312c868a72de5f137 Mon Sep 17 00:00:00 2001 From: Eugene Fedorenko Date: Thu, 1 Aug 2019 16:33:16 -0700 Subject: [PATCH 017/113] Update build-train.yml for Azure Pipelines --- azdo_pipelines/build-train.yml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/azdo_pipelines/build-train.yml b/azdo_pipelines/build-train.yml index 1d5d0c48..b8d2ab5d 100644 --- a/azdo_pipelines/build-train.yml +++ b/azdo_pipelines/build-train.yml @@ -10,7 +10,7 @@ pool: container: image: pepsimlamlcr.azurecr.io/mlopsbuildagent:latest - endpoint: acrconnection + endpoint: acrbackupconnection variables: From d99d87300b98afac97f48c754b802c94d25ac811 Mon Sep 17 00:00:00 2001 From: Eugene Fedorenko Date: Thu, 1 Aug 2019 16:34:44 -0700 Subject: [PATCH 018/113] fix --- aml_pipelines/model_train_pipeline.py | 30 +++++++++++++-------------- 1 file changed, 14 insertions(+), 16 deletions(-) diff --git a/aml_pipelines/model_train_pipeline.py b/aml_pipelines/model_train_pipeline.py index a2592578..9acd5c7b 100644 --- a/aml_pipelines/model_train_pipeline.py +++ b/aml_pipelines/model_train_pipeline.py @@ -32,22 +32,22 @@ def main(): experiment_name = os.environ.get("EXPERIMENT_NAME") # Get Azure machine learning workspace - #aml_workspace = get_workspace( - # workspace_name, - # resource_group, - # subscription_id, - # tenant_id, - # app_id, - # app_secret) - #print(aml_workspace) + aml_workspace = get_workspace( + workspace_name, + resource_group, + subscription_id, + tenant_id, + app_id, + app_secret) + print(aml_workspace) # Get Azure machine learning cluster - #aml_compute_cpu = get_compute( - # aml_workspace, - # compute_name_cpu, - # vm_size_cpu) - #if aml_compute_cpu is not None: - # print(aml_compute_cpu) + aml_compute_cpu = get_compute( + aml_workspace, + compute_name_cpu, + vm_size_cpu) + if aml_compute_cpu is not None: + print(aml_compute_cpu) run_config = RunConfiguration(conda_dependencies=CondaDependencies.create( conda_packages=['numpy', 'pandas', @@ -58,8 +58,6 @@ def main(): ) run_config.environment.docker.enabled = True - aml_compute_cpu=None - aml_workspace=None model_name = PipelineParameter(name="model_name", default_value="sklearn_regression_model.pkl") def_blob_store = Datastore(aml_workspace, "workspaceblobstore") jsonconfigs = PipelineData("jsonconfigs", datastore=def_blob_store) From 370ea668eaffb1528b60d6b03f7d7025a833aeac Mon Sep 17 00:00:00 2001 From: Eugene Fedorenko Date: Thu, 1 Aug 2019 16:35:39 -0700 Subject: [PATCH 019/113] fix --- azdo_pipelines/build-train.yml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/azdo_pipelines/build-train.yml b/azdo_pipelines/build-train.yml index b8d2ab5d..e5eb5c36 100644 --- a/azdo_pipelines/build-train.yml +++ b/azdo_pipelines/build-train.yml @@ -22,7 +22,7 @@ steps: - bash: | # Invoke the Python training pipeline - python3 $(Build.SourcesDirectory)/Code/aml_pipelines/model_train_pipeline.py + python3 $(Build.SourcesDirectory)/aml_pipelines/model_train_pipeline.py failOnStderr: 'false' env: SOURCES_DIR: '$(Build.SourcesDirectory)' From 4b60faa8e6701485e363fa2a8b7312431bcb4cb9 Mon Sep 17 00:00:00 2001 From: Eugene Fedorenko Date: Thu, 1 Aug 2019 17:59:46 -0700 Subject: [PATCH 020/113] looks like working --- aml_pipelines/model_train_pipeline.py | 42 ++++++++++++++++++++++++++- 1 file changed, 41 insertions(+), 1 deletion(-) diff --git a/aml_pipelines/model_train_pipeline.py b/aml_pipelines/model_train_pipeline.py index 9acd5c7b..5c91f550 100644 --- a/aml_pipelines/model_train_pipeline.py +++ b/aml_pipelines/model_train_pipeline.py @@ -80,7 +80,47 @@ def main(): ) print("Step Train created") - print("hi") + evaluate_step = PythonScriptStep( + name="Evaluate Model ", + script_name="evaluate/evaluate_model.py", + compute_target=aml_compute_cpu, + source_directory=sources_directory_train, + arguments=[ + "--config_suffix", config_suffix, + "--json_config", jsonconfigs, + ], + runconfig=run_config, + inputs=[jsonconfigs], + # outputs=[jsonconfigs], + allow_reuse=False, + ) + print("Step Evaluate created") + + register_model_step = PythonScriptStep( + name="Register New Trained Model", + script_name="register/register_model.py", + compute_target=aml_compute_cpu, + source_directory=sources_directory_train, + arguments=[ + "--config_suffix", config_suffix, + "--json_config", jsonconfigs, + "--model_name", model_name, + ], + runconfig=run_config, + inputs=[jsonconfigs], + # outputs=[jsonconfigs], + allow_reuse=False, + ) + print("Step register model created") + + evaluate_step.run_after(train_step) + register_model_step.run_after(evaluate_step) + steps = [register_model_step] + + train_pipeline = Pipeline(workspace=aml_workspace, steps=steps) + train_pipeline.validate() + pipeline_run = train_pipeline.submit(experiment_name=experiment_name) + if __name__ == '__main__': main() \ No newline at end of file From 21dfdb075c64963390a40d64416016025d92b174 Mon Sep 17 00:00:00 2001 From: Taylor Rockey Date: Mon, 5 Aug 2019 10:42:04 -0700 Subject: [PATCH 021/113] added static path to workspace from config --- aml_config/config.json | 7 +------ aml_service/00-WorkSpace.py | 2 +- aml_service/01-Experiment.py | 5 ++++- aml_service/02-AttachTrainingVM.py | 5 ++++- aml_service/03-AttachAmlCluster.py | 7 +++++-- aml_service/04-AmlPipelines.py | 10 ++++++++-- aml_service/10-TrainOnLocal.py | 5 ++++- aml_service/11-TrainOnLocalEnv.py | 5 ++++- aml_service/12-TrainOnVM.py | 5 ++++- aml_service/15-EvaluateModel.py | 5 ++++- aml_service/20-RegisterModel.py | 5 ++++- aml_service/30-CreateScoringImage.py | 5 ++++- aml_service/34-GetScoringImageName.py | 5 ++++- aml_service/51-deployOnAks.py | 5 ++++- aml_service/60-AciWebserviceTest.py | 5 ++++- aml_service/61-AksWebserviceTest.py | 5 ++++- code/register/register_model.py | 5 ++++- code/scoring/create_scoring_image.py | 5 ++++- environment_setup/requirements.txt | 4 +++- 19 files changed, 74 insertions(+), 26 deletions(-) diff --git a/aml_config/config.json b/aml_config/config.json index 7105ecf7..eb5d0991 100644 --- a/aml_config/config.json +++ b/aml_config/config.json @@ -1,6 +1 @@ -{ - "subscription_id": "<>", - "resource_group": "DevOps_AzureML_Demo", - "workspace_name": "AzureML_Demo_ws", - "location": "southcentralus" -} +{"Id": null, "Scope": "/subscriptions/4e3d57a1-3ed9-45f6-b033-e2bc8285fed3/resourceGroups/mlopstesting/providers/Microsoft.MachineLearningServices/workspaces/trmlops"} \ No newline at end of file diff --git a/aml_service/00-WorkSpace.py b/aml_service/00-WorkSpace.py index 7538fe1c..8c2c3a57 100644 --- a/aml_service/00-WorkSpace.py +++ b/aml_service/00-WorkSpace.py @@ -62,7 +62,7 @@ ) # Save the details of this workspace to config -ws.write_config() +ws.write_config(path='./') # print Workspace details print(ws.name, ws.resource_group, ws.location, ws.subscription_id, sep="\n") diff --git a/aml_service/01-Experiment.py b/aml_service/01-Experiment.py index 3bb5a9cf..d39caa45 100644 --- a/aml_service/01-Experiment.py +++ b/aml_service/01-Experiment.py @@ -34,7 +34,10 @@ def getExperiment(): load_dotenv() - ws = Workspace.from_config(auth=cli_auth) + ws = Workspace.from_config(auth=cli_auth, path='./') + + + script_folder = os.environ.get('SCRIPT_FOLDER') experiment_name = os.environ.get('EXPERIMENT_NAME') exp = Experiment(workspace=ws, name=experiment_name) diff --git a/aml_service/02-AttachTrainingVM.py b/aml_service/02-AttachTrainingVM.py index 3f703a7e..e43c73bd 100644 --- a/aml_service/02-AttachTrainingVM.py +++ b/aml_service/02-AttachTrainingVM.py @@ -40,7 +40,10 @@ load_dotenv() # Get workspace -ws = Workspace.from_config(auth=cli_auth) +ws = Workspace.from_config(auth=cli_auth, path='./') + + + # Read the New VM Config with open("aml_config/security_config.json") as f: diff --git a/aml_service/03-AttachAmlCluster.py b/aml_service/03-AttachAmlCluster.py index b77336f8..5dcd1e00 100644 --- a/aml_service/03-AttachAmlCluster.py +++ b/aml_service/03-AttachAmlCluster.py @@ -35,7 +35,10 @@ load_dotenv() # Get workspace -ws = Workspace.from_config(auth=cli_auth) +ws = Workspace.from_config(auth=cli_auth, path='./') + + + aml_cluster_name = os.environ.get('AML_CLUSTER_NAME') @@ -62,4 +65,4 @@ ) cpu_cluster = ComputeTarget.create(ws, aml_cluster_name, compute_config) -cpu_cluster.wait_for_completion(show_output=True) + cpu_cluster.wait_for_completion(show_output=True) diff --git a/aml_service/04-AmlPipelines.py b/aml_service/04-AmlPipelines.py index 1a0147a8..248520d8 100644 --- a/aml_service/04-AmlPipelines.py +++ b/aml_service/04-AmlPipelines.py @@ -58,9 +58,15 @@ # Get workspace -ws = Workspace.from_config(auth=cli_auth) +ws = Workspace.from_config(auth=cli_auth, path='./') + + + blob_store_name = os.environ['BLOB_STORE_NAME'] -def_blob_store = Datastore(ws, blob_store_name) +if blob_store_name is not None: + def_blob_store = Datastore(ws, blob_store_name) +else: + def_blob_store = Datastore.get_default(ws) # Get AML Compute name and Experiment Name experiment_name = os.environ['EXPERIMENT_NAME'] diff --git a/aml_service/10-TrainOnLocal.py b/aml_service/10-TrainOnLocal.py index be5d3e47..1a122481 100644 --- a/aml_service/10-TrainOnLocal.py +++ b/aml_service/10-TrainOnLocal.py @@ -36,7 +36,10 @@ load_dotenv() # Get workspace -ws = Workspace.from_config(auth=cli_auth) +ws = Workspace.from_config(auth=cli_auth, path='./') + + + # Attach Experiment experiment_name = os.environ['EXPERIMENT_NAME'] diff --git a/aml_service/11-TrainOnLocalEnv.py b/aml_service/11-TrainOnLocalEnv.py index 1cea04ed..98f3d6db 100644 --- a/aml_service/11-TrainOnLocalEnv.py +++ b/aml_service/11-TrainOnLocalEnv.py @@ -39,7 +39,10 @@ cli_auth = AzureCliAuthentication() load_dotenv() # Get workspace -ws = Workspace.from_config(auth=cli_auth) +ws = Workspace.from_config(auth=cli_auth, path='./') + + + # Attach Experiment experiment_name = os.environ['EXPERIMENT_NAME'] diff --git a/aml_service/12-TrainOnVM.py b/aml_service/12-TrainOnVM.py index 18db4090..4e69d019 100644 --- a/aml_service/12-TrainOnVM.py +++ b/aml_service/12-TrainOnVM.py @@ -36,7 +36,10 @@ cli_auth = AzureCliAuthentication() load_dotenv() # Get workspace -ws = Workspace.from_config(auth=cli_auth) +ws = Workspace.from_config(auth=cli_auth, path='./') + + + # Read the New VM Config diff --git a/aml_service/15-EvaluateModel.py b/aml_service/15-EvaluateModel.py index 81511a85..90b1cfcd 100644 --- a/aml_service/15-EvaluateModel.py +++ b/aml_service/15-EvaluateModel.py @@ -35,7 +35,10 @@ cli_auth = AzureCliAuthentication() load_dotenv() # Get workspace -ws = Workspace.from_config(auth=cli_auth) +ws = Workspace.from_config(auth=cli_auth, path='./') + + + # Paramaterize the matrics on which the models should be compared diff --git a/aml_service/20-RegisterModel.py b/aml_service/20-RegisterModel.py index 009575cc..e04cd992 100644 --- a/aml_service/20-RegisterModel.py +++ b/aml_service/20-RegisterModel.py @@ -36,7 +36,10 @@ cli_auth = AzureCliAuthentication() load_dotenv() # Get workspace -ws = Workspace.from_config(auth=cli_auth) +ws = Workspace.from_config(auth=cli_auth, path='./') + + + # Get the latest evaluation result try: diff --git a/aml_service/30-CreateScoringImage.py b/aml_service/30-CreateScoringImage.py index d0b3dc56..e51c8828 100644 --- a/aml_service/30-CreateScoringImage.py +++ b/aml_service/30-CreateScoringImage.py @@ -33,7 +33,10 @@ cli_auth = AzureCliAuthentication() load_dotenv() # Get workspace -ws = Workspace.from_config(auth=cli_auth) +ws = Workspace.from_config(auth=cli_auth, path='./') + + + # Get the latest model details diff --git a/aml_service/34-GetScoringImageName.py b/aml_service/34-GetScoringImageName.py index b5f3a764..5b647603 100644 --- a/aml_service/34-GetScoringImageName.py +++ b/aml_service/34-GetScoringImageName.py @@ -30,7 +30,10 @@ cli_auth = AzureCliAuthentication() # Get workspace -ws = Workspace.from_config(auth=cli_auth) +ws = Workspace.from_config(auth=cli_auth, path='./') + + + # Get the latest image details latest_image = ws.images diff --git a/aml_service/51-deployOnAks.py b/aml_service/51-deployOnAks.py index 1ad50990..42e68d56 100644 --- a/aml_service/51-deployOnAks.py +++ b/aml_service/51-deployOnAks.py @@ -36,7 +36,10 @@ cli_auth = AzureCliAuthentication() load_dotenv() # Get workspace -ws = Workspace.from_config(auth=cli_auth) +ws = Workspace.from_config(auth=cli_auth, path='./') + + + # Get the Image to deploy details image_name = os.environ['IMAGE_NAME'] diff --git a/aml_service/60-AciWebserviceTest.py b/aml_service/60-AciWebserviceTest.py index a8c40f69..588ae541 100644 --- a/aml_service/60-AciWebserviceTest.py +++ b/aml_service/60-AciWebserviceTest.py @@ -35,7 +35,10 @@ cli_auth = AzureCliAuthentication() # Get workspace -ws = Workspace.from_config(auth=cli_auth) +ws = Workspace.from_config(auth=cli_auth, path='./') + + + # Get the ACI Details try: with open("aml_config/aci_webservice.json") as f: diff --git a/aml_service/61-AksWebserviceTest.py b/aml_service/61-AksWebserviceTest.py index f22982e0..8c1b6dab 100644 --- a/aml_service/61-AksWebserviceTest.py +++ b/aml_service/61-AksWebserviceTest.py @@ -34,7 +34,10 @@ cli_auth = AzureCliAuthentication() # Get workspace -ws = Workspace.from_config(auth=cli_auth) +ws = Workspace.from_config(auth=cli_auth, path='./') + + + # Get the AKS Details try: diff --git a/code/register/register_model.py b/code/register/register_model.py index c7d38b82..7308ac73 100644 --- a/code/register/register_model.py +++ b/code/register/register_model.py @@ -36,7 +36,10 @@ cli_auth = AzureCliAuthentication() # Get workspace -# ws = Workspace.from_config(auth=cli_auth) +# ws = Workspace.from_config(auth=cli_auth, path='./') + + + run = Run.get_context() exp = run.experiment ws = run.experiment.workspace diff --git a/code/scoring/create_scoring_image.py b/code/scoring/create_scoring_image.py index 1aafade1..f50650c1 100644 --- a/code/scoring/create_scoring_image.py +++ b/code/scoring/create_scoring_image.py @@ -37,7 +37,10 @@ if "OfflineRun" in run.id: print("offline run") # Get workspace - ws = Workspace.from_config(auth=cli_auth) + ws = Workspace.from_config(auth=cli_auth, path='./') + + + else: exp = run.experiment ws = run.experiment.workspace diff --git a/environment_setup/requirements.txt b/environment_setup/requirements.txt index 21a652c8..c56f7e14 100644 --- a/environment_setup/requirements.txt +++ b/environment_setup/requirements.txt @@ -3,4 +3,6 @@ scikit-learn==0.19.1 numpy==1.14.5 pandas==0.23.1 pytest==4.3.0 -python-dotenv==0.10.3 \ No newline at end of file +python-dotenv==0.10.3 +azureml-sdk +azure-cli \ No newline at end of file From 42c724e2a3c7c8f3ebc59a670408b0b0400824d6 Mon Sep 17 00:00:00 2001 From: Eugene Fedorenko Date: Mon, 5 Aug 2019 13:50:58 -0700 Subject: [PATCH 022/113] fix --- azdo_pipelines/build-train.yml | 4 ++-- azdo_pipelines/iac-pipeline-arm.yml | 35 ----------------------------- 2 files changed, 2 insertions(+), 37 deletions(-) delete mode 100644 azdo_pipelines/iac-pipeline-arm.yml diff --git a/azdo_pipelines/build-train.yml b/azdo_pipelines/build-train.yml index e5eb5c36..54199204 100644 --- a/azdo_pipelines/build-train.yml +++ b/azdo_pipelines/build-train.yml @@ -21,8 +21,8 @@ variables: steps: - bash: | # Invoke the Python training pipeline - - python3 $(Build.SourcesDirectory)/aml_pipelines/model_train_pipeline.py + echo $SP_APP_SECRET + #python3 $(Build.SourcesDirectory)/aml_pipelines/model_train_pipeline.py failOnStderr: 'false' env: SOURCES_DIR: '$(Build.SourcesDirectory)' diff --git a/azdo_pipelines/iac-pipeline-arm.yml b/azdo_pipelines/iac-pipeline-arm.yml deleted file mode 100644 index dfc075da..00000000 --- a/azdo_pipelines/iac-pipeline-arm.yml +++ /dev/null @@ -1,35 +0,0 @@ -trigger: - branches: - include: - - master - paths: - include: - - iac/arm-templates/* - -pool: - vmImage: 'ubuntu-latest' - -variables: - baseName: $[coalesce(variables['baseNameOverride'], 'pepsiml')] - location: $[coalesce(variables['locationOverride'], 'centralus')] - azuresub: $[coalesce(variables['azuresubOverride'], 'davete02_TED')] - containerRegistry: $[coalesce(variables['acrServiceConnection'], 'acrconnection')] - imageName: $[coalesce(variables['builderImageName'], 'mlopsbuildagent')] - - -steps: -- task: AzureResourceGroupDeployment@2 - inputs: - azureSubscription: $(azuresub) - action: 'Create Or Update Resource Group' - resourceGroupName: '$(baseName)-AML-RG' - location: $(location) - templateLocation: 'Linked artifact' - csmFile: '$(Build.SourcesDirectory)/Code/iac/arm-templates/cloud-environment.json' - overrideParameters: '-baseName $(baseName)' - deploymentMode: 'Incremental' - displayName: 'Deploy MLOps resources to Azure' - -- template: templates/docker-builder-image-template.yml - - \ No newline at end of file From cd874feb9b4e507f5c8ea647ea34f1e40da4dac8 Mon Sep 17 00:00:00 2001 From: Eugene Fedorenko Date: Mon, 5 Aug 2019 13:54:45 -0700 Subject: [PATCH 023/113] Update build-train.yml for Azure Pipelines --- azdo_pipelines/build-train.yml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/azdo_pipelines/build-train.yml b/azdo_pipelines/build-train.yml index 54199204..dca0f034 100644 --- a/azdo_pipelines/build-train.yml +++ b/azdo_pipelines/build-train.yml @@ -26,7 +26,7 @@ steps: failOnStderr: 'false' env: SOURCES_DIR: '$(Build.SourcesDirectory)' - SP_APP_SECRET: '$(SP_APP_SECRET)' + SP_APP_SECRET: $(SP_APP_SECRET) BLOB_STORAGE_Key: '$(BLOB_STORAGE_Key)' displayName: 'Train model using AML with Remote Compute' enabled: 'true' \ No newline at end of file From 851d65373ec52db138ed43fd044367e9c03ad0cc Mon Sep 17 00:00:00 2001 From: Eugene Fedorenko Date: Mon, 5 Aug 2019 13:58:11 -0700 Subject: [PATCH 024/113] Update build-train.yml for Azure Pipelines --- azdo_pipelines/build-train.yml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/azdo_pipelines/build-train.yml b/azdo_pipelines/build-train.yml index dca0f034..350ca628 100644 --- a/azdo_pipelines/build-train.yml +++ b/azdo_pipelines/build-train.yml @@ -26,7 +26,7 @@ steps: failOnStderr: 'false' env: SOURCES_DIR: '$(Build.SourcesDirectory)' - SP_APP_SECRET: $(SP_APP_SECRET) + SP_APP_SECRET: $(SP_APP_SECRET1) BLOB_STORAGE_Key: '$(BLOB_STORAGE_Key)' displayName: 'Train model using AML with Remote Compute' enabled: 'true' \ No newline at end of file From ab405671db8a359b4d8e00be59f773088a452a2f Mon Sep 17 00:00:00 2001 From: Eugene Fedorenko Date: Mon, 5 Aug 2019 14:00:15 -0700 Subject: [PATCH 025/113] Update build-train.yml for Azure Pipelines --- azdo_pipelines/build-train.yml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/azdo_pipelines/build-train.yml b/azdo_pipelines/build-train.yml index 350ca628..8a2c7180 100644 --- a/azdo_pipelines/build-train.yml +++ b/azdo_pipelines/build-train.yml @@ -26,7 +26,7 @@ steps: failOnStderr: 'false' env: SOURCES_DIR: '$(Build.SourcesDirectory)' - SP_APP_SECRET: $(SP_APP_SECRET1) + SP_APP_SECRET: 'HI' BLOB_STORAGE_Key: '$(BLOB_STORAGE_Key)' displayName: 'Train model using AML with Remote Compute' enabled: 'true' \ No newline at end of file From 5db8b1d6e338a09096fc18cf43f5810cfda55798 Mon Sep 17 00:00:00 2001 From: Eugene Fedorenko Date: Mon, 5 Aug 2019 14:02:30 -0700 Subject: [PATCH 026/113] Update build-train.yml for Azure Pipelines --- azdo_pipelines/build-train.yml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/azdo_pipelines/build-train.yml b/azdo_pipelines/build-train.yml index 8a2c7180..0a5b2479 100644 --- a/azdo_pipelines/build-train.yml +++ b/azdo_pipelines/build-train.yml @@ -26,7 +26,7 @@ steps: failOnStderr: 'false' env: SOURCES_DIR: '$(Build.SourcesDirectory)' - SP_APP_SECRET: 'HI' + SP_APP_SECRET: '$(RESOURCE_GROUP)' BLOB_STORAGE_Key: '$(BLOB_STORAGE_Key)' displayName: 'Train model using AML with Remote Compute' enabled: 'true' \ No newline at end of file From 8b26198abeb1fd262bb21d083b622bb2b7cbcaeb Mon Sep 17 00:00:00 2001 From: Eugene Fedorenko Date: Mon, 5 Aug 2019 14:04:32 -0700 Subject: [PATCH 027/113] Update build-train.yml for Azure Pipelines --- azdo_pipelines/build-train.yml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/azdo_pipelines/build-train.yml b/azdo_pipelines/build-train.yml index 0a5b2479..d4246b12 100644 --- a/azdo_pipelines/build-train.yml +++ b/azdo_pipelines/build-train.yml @@ -26,7 +26,7 @@ steps: failOnStderr: 'false' env: SOURCES_DIR: '$(Build.SourcesDirectory)' - SP_APP_SECRET: '$(RESOURCE_GROUP)' + SP_APP_SECRET: $RESOURCE_GROUP BLOB_STORAGE_Key: '$(BLOB_STORAGE_Key)' displayName: 'Train model using AML with Remote Compute' enabled: 'true' \ No newline at end of file From c9c10d2c5cee68f6ca2f78e0410b7dcd110cae77 Mon Sep 17 00:00:00 2001 From: Eugene Fedorenko Date: Mon, 5 Aug 2019 14:07:01 -0700 Subject: [PATCH 028/113] Update build-train.yml for Azure Pipelines --- azdo_pipelines/build-train.yml | 3 +-- 1 file changed, 1 insertion(+), 2 deletions(-) diff --git a/azdo_pipelines/build-train.yml b/azdo_pipelines/build-train.yml index d4246b12..844b7f43 100644 --- a/azdo_pipelines/build-train.yml +++ b/azdo_pipelines/build-train.yml @@ -25,8 +25,7 @@ steps: #python3 $(Build.SourcesDirectory)/aml_pipelines/model_train_pipeline.py failOnStderr: 'false' env: - SOURCES_DIR: '$(Build.SourcesDirectory)' - SP_APP_SECRET: $RESOURCE_GROUP + SOURCES_DIR: '$(Build.SourcesDirectory)' BLOB_STORAGE_Key: '$(BLOB_STORAGE_Key)' displayName: 'Train model using AML with Remote Compute' enabled: 'true' \ No newline at end of file From 61854b1d61f4330ef0e88e2f1918e6e01a56d2f6 Mon Sep 17 00:00:00 2001 From: Eugene Fedorenko Date: Mon, 5 Aug 2019 14:12:43 -0700 Subject: [PATCH 029/113] Update build-train.yml for Azure Pipelines --- azdo_pipelines/build-train.yml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/azdo_pipelines/build-train.yml b/azdo_pipelines/build-train.yml index 844b7f43..7e407483 100644 --- a/azdo_pipelines/build-train.yml +++ b/azdo_pipelines/build-train.yml @@ -21,7 +21,7 @@ variables: steps: - bash: | # Invoke the Python training pipeline - echo $SP_APP_SECRET + echo $SOURCES_DIR #python3 $(Build.SourcesDirectory)/aml_pipelines/model_train_pipeline.py failOnStderr: 'false' env: From aff1b46e5f6d76c7dfd2051e86803c6ef5867bc6 Mon Sep 17 00:00:00 2001 From: Eugene Fedorenko Date: Mon, 5 Aug 2019 14:24:02 -0700 Subject: [PATCH 030/113] Update build-train.yml for Azure Pipelines --- azdo_pipelines/build-train.yml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/azdo_pipelines/build-train.yml b/azdo_pipelines/build-train.yml index 7e407483..0ed8409a 100644 --- a/azdo_pipelines/build-train.yml +++ b/azdo_pipelines/build-train.yml @@ -21,7 +21,7 @@ variables: steps: - bash: | # Invoke the Python training pipeline - echo $SOURCES_DIR + printenv #python3 $(Build.SourcesDirectory)/aml_pipelines/model_train_pipeline.py failOnStderr: 'false' env: From d2334a5e7fd20889b2f05d732072eb9ca121a719 Mon Sep 17 00:00:00 2001 From: Eugene Fedorenko Date: Mon, 5 Aug 2019 14:37:40 -0700 Subject: [PATCH 031/113] Update build-train.yml for Azure Pipelines --- azdo_pipelines/build-train.yml | 8 +++++--- 1 file changed, 5 insertions(+), 3 deletions(-) diff --git a/azdo_pipelines/build-train.yml b/azdo_pipelines/build-train.yml index 0ed8409a..03358d1d 100644 --- a/azdo_pipelines/build-train.yml +++ b/azdo_pipelines/build-train.yml @@ -7,15 +7,17 @@ trigger: pool: vmImage: 'ubuntu-latest' - container: image: pepsimlamlcr.azurecr.io/mlopsbuildagent:latest endpoint: acrbackupconnection variables: - SOURCES_DIR: $[coalesce(variables['SOURCES_DIR_OVERRIDE'], '$(Build.SourcesDirectory)/Code/src/train')] - TRAIN_SCRIPT_PATH: $[coalesce(variables['TRAIN_SCRIPT_PATH_OVERRIDE'], 'src/train/train.py')] +- group: my-variable-group +- name: SOURCES_DIR + value: $[coalesce(variables['SOURCES_DIR_OVERRIDE'], '$(Build.SourcesDirectory)/Code/src/train')] +- name: SOURCES_DIR + value: $[coalesce(variables['TRAIN_SCRIPT_PATH_OVERRIDE'], 'src/train/train.py')] steps: From 5c8ca997cf7b5d6f2753c55bfed3603ecbf63c53 Mon Sep 17 00:00:00 2001 From: Eugene Fedorenko Date: Mon, 5 Aug 2019 14:38:08 -0700 Subject: [PATCH 032/113] Update build-train.yml for Azure Pipelines --- azdo_pipelines/build-train.yml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/azdo_pipelines/build-train.yml b/azdo_pipelines/build-train.yml index 03358d1d..101dba03 100644 --- a/azdo_pipelines/build-train.yml +++ b/azdo_pipelines/build-train.yml @@ -13,7 +13,7 @@ container: variables: -- group: my-variable-group +- group: devopsforai-aml-vg - name: SOURCES_DIR value: $[coalesce(variables['SOURCES_DIR_OVERRIDE'], '$(Build.SourcesDirectory)/Code/src/train')] - name: SOURCES_DIR From 1740c253e537aa39d00c874c5ae057e8e62cdae8 Mon Sep 17 00:00:00 2001 From: Eugene Fedorenko Date: Mon, 5 Aug 2019 14:47:24 -0700 Subject: [PATCH 033/113] Update build-train.yml for Azure Pipelines --- azdo_pipelines/build-train.yml | 3 ++- 1 file changed, 2 insertions(+), 1 deletion(-) diff --git a/azdo_pipelines/build-train.yml b/azdo_pipelines/build-train.yml index 101dba03..b2fc1b9d 100644 --- a/azdo_pipelines/build-train.yml +++ b/azdo_pipelines/build-train.yml @@ -24,10 +24,11 @@ steps: - bash: | # Invoke the Python training pipeline printenv - #python3 $(Build.SourcesDirectory)/aml_pipelines/model_train_pipeline.py + python3 $(Build.SourcesDirectory)/aml_pipelines/model_train_pipeline.py failOnStderr: 'false' env: SOURCES_DIR: '$(Build.SourcesDirectory)' BLOB_STORAGE_Key: '$(BLOB_STORAGE_Key)' + SP_APP_SECRET: '$(SP_APP_SECRET)' displayName: 'Train model using AML with Remote Compute' enabled: 'true' \ No newline at end of file From 0365a75c9b5beb5a9461a5214f5ead969c1f5f0f Mon Sep 17 00:00:00 2001 From: Eugene Fedorenko Date: Mon, 5 Aug 2019 15:08:19 -0700 Subject: [PATCH 034/113] src dirs to variables --- aml_pipelines/model_train_pipeline.py | 9 ++++++--- azdo_pipelines/build-train.yml | 6 ------ 2 files changed, 6 insertions(+), 9 deletions(-) diff --git a/aml_pipelines/model_train_pipeline.py b/aml_pipelines/model_train_pipeline.py index 5c91f550..9280c9cb 100644 --- a/aml_pipelines/model_train_pipeline.py +++ b/aml_pipelines/model_train_pipeline.py @@ -27,6 +27,9 @@ def main(): app_id = os.environ.get("SP_APP_ID") app_secret = os.environ.get("SP_APP_SECRET") sources_directory_train = os.environ.get("SOURCES_DIR_TRAIN") + train_script_path = os.environ.get("TRAIN_SCRIPT_PATH") + evaluate_script_path = os.environ.get("EVALUATE_SCRIPT_PATH") + register_script_path = os.environ.get("REGISTER_SCRIPT_PATH") vm_size_cpu = os.environ.get("AML_COMPUTE_CLUSTER_CPU_SKU") compute_name_cpu = os.environ.get("AML_COMPUTE_CLUSTER_NAME") experiment_name = os.environ.get("EXPERIMENT_NAME") @@ -65,7 +68,7 @@ def main(): train_step = PythonScriptStep( name="Train Model", - script_name="training/train.py", + script_name=train_script_path, compute_target=aml_compute_cpu, source_directory=sources_directory_train, arguments=[ @@ -82,7 +85,7 @@ def main(): evaluate_step = PythonScriptStep( name="Evaluate Model ", - script_name="evaluate/evaluate_model.py", + script_name=evaluate_script_path, compute_target=aml_compute_cpu, source_directory=sources_directory_train, arguments=[ @@ -98,7 +101,7 @@ def main(): register_model_step = PythonScriptStep( name="Register New Trained Model", - script_name="register/register_model.py", + script_name=register_script_path, compute_target=aml_compute_cpu, source_directory=sources_directory_train, arguments=[ diff --git a/azdo_pipelines/build-train.yml b/azdo_pipelines/build-train.yml index b2fc1b9d..c96b3e32 100644 --- a/azdo_pipelines/build-train.yml +++ b/azdo_pipelines/build-train.yml @@ -14,20 +14,14 @@ container: variables: - group: devopsforai-aml-vg -- name: SOURCES_DIR - value: $[coalesce(variables['SOURCES_DIR_OVERRIDE'], '$(Build.SourcesDirectory)/Code/src/train')] -- name: SOURCES_DIR - value: $[coalesce(variables['TRAIN_SCRIPT_PATH_OVERRIDE'], 'src/train/train.py')] steps: - bash: | # Invoke the Python training pipeline - printenv python3 $(Build.SourcesDirectory)/aml_pipelines/model_train_pipeline.py failOnStderr: 'false' env: - SOURCES_DIR: '$(Build.SourcesDirectory)' BLOB_STORAGE_Key: '$(BLOB_STORAGE_Key)' SP_APP_SECRET: '$(SP_APP_SECRET)' displayName: 'Train model using AML with Remote Compute' From 551879eca079c045fbf38ec1eb6de7387a256976 Mon Sep 17 00:00:00 2001 From: Eugene Fedorenko Date: Mon, 5 Aug 2019 15:15:56 -0700 Subject: [PATCH 035/113] nbase pipeline template --- azdo_pipelines/base-pipeline.yml | 11 +++++------ azdo_pipelines/build-train.yml | 3 ++- 2 files changed, 7 insertions(+), 7 deletions(-) diff --git a/azdo_pipelines/base-pipeline.yml b/azdo_pipelines/base-pipeline.yml index d2f6ae7d..5f170b4d 100644 --- a/azdo_pipelines/base-pipeline.yml +++ b/azdo_pipelines/base-pipeline.yml @@ -1,6 +1,5 @@ parameters: - requirementsPath: 'requirements.txt' - pipelineType: 'train' + pipelineType: 'training' steps: - script: | @@ -10,10 +9,10 @@ steps: displayName: 'Run code quality tests' enabled: 'true' -- script: | - pytest --junitxml=$(Build.BinariesDirectory)/unittest-results.xml $(Build.SourcesDirectory)/Code/tests/unit/${{parameters.pipelineType}} - displayName: 'Run unit tests' - enabled: 'true' +#- script: | +# pytest --junitxml=$(Build.BinariesDirectory)/unittest-results.xml $(Build.SourcesDirectory)/Code/tests/unit/${{parameters.pipelineType}} +# displayName: 'Run unit tests' +# enabled: 'true' - task: PublishTestResults@2 condition: succeededOrFailed() diff --git a/azdo_pipelines/build-train.yml b/azdo_pipelines/build-train.yml index c96b3e32..db4799ed 100644 --- a/azdo_pipelines/build-train.yml +++ b/azdo_pipelines/build-train.yml @@ -17,12 +17,13 @@ variables: steps: +- template: base-pipeline.yml + - bash: | # Invoke the Python training pipeline python3 $(Build.SourcesDirectory)/aml_pipelines/model_train_pipeline.py failOnStderr: 'false' env: - BLOB_STORAGE_Key: '$(BLOB_STORAGE_Key)' SP_APP_SECRET: '$(SP_APP_SECRET)' displayName: 'Train model using AML with Remote Compute' enabled: 'true' \ No newline at end of file From 8c90b8a966361d27218b346845d553fde4c13fa2 Mon Sep 17 00:00:00 2001 From: Eugene Fedorenko Date: Mon, 5 Aug 2019 15:19:03 -0700 Subject: [PATCH 036/113] working folder for linting --- azdo_pipelines/base-pipeline.yml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/azdo_pipelines/base-pipeline.yml b/azdo_pipelines/base-pipeline.yml index 5f170b4d..c7ff2143 100644 --- a/azdo_pipelines/base-pipeline.yml +++ b/azdo_pipelines/base-pipeline.yml @@ -5,7 +5,7 @@ steps: - script: | flake8 --output-file=$(Build.BinariesDirectory)/flake8_amlservice_testresults.xml aml_service flake8 --output-file=$(Build.BinariesDirectory)/flake8_tests_testresults.xml tests - workingDirectory: '$(Build.SourcesDirectory)/Code' + workingDirectory: '$(Build.SourcesDirectory)' displayName: 'Run code quality tests' enabled: 'true' From f25addf7c482876a8cc3c67d5c2a5de0486cc8e6 Mon Sep 17 00:00:00 2001 From: Eugene Fedorenko Date: Mon, 5 Aug 2019 17:01:42 -0700 Subject: [PATCH 037/113] correct image name --- azdo_pipelines/build-train.yml | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/azdo_pipelines/build-train.yml b/azdo_pipelines/build-train.yml index db4799ed..d655c915 100644 --- a/azdo_pipelines/build-train.yml +++ b/azdo_pipelines/build-train.yml @@ -8,8 +8,8 @@ pool: vmImage: 'ubuntu-latest' container: - image: pepsimlamlcr.azurecr.io/mlopsbuildagent:latest - endpoint: acrbackupconnection + image: mlopscr.azurecr.io/public/mlops/mlopspython:latest + endpoint: acrconnection variables: From 141257edb49233c26f775cc00371bf23ebbbaff9 Mon Sep 17 00:00:00 2001 From: Eugene Fedorenko Date: Mon, 5 Aug 2019 17:15:18 -0700 Subject: [PATCH 038/113] added flake to requirements --- requirements.txt => environment_setup/requirements.txt | 6 ++---- 1 file changed, 2 insertions(+), 4 deletions(-) rename requirements.txt => environment_setup/requirements.txt (65%) diff --git a/requirements.txt b/environment_setup/requirements.txt similarity index 65% rename from requirements.txt rename to environment_setup/requirements.txt index f92f52ab..53e3a374 100644 --- a/requirements.txt +++ b/environment_setup/requirements.txt @@ -1,10 +1,8 @@ -scipy==1.0.0 -scikit-learn==0.19.1 -numpy==1.14.5 -pandas==0.23.1 pytest==4.3.0 requests>=2.22 #.0 azureml>=0.2 #.7 azureml-core>=1.0 #.45 azureml-pipeline>=1.0 #.45 python-dotenv>=0.10.3 +flake8 +flake8_formatter_junit_xml From d29242e04008449b591b99984a79cae6b63b16b8 Mon Sep 17 00:00:00 2001 From: Eugene Fedorenko Date: Mon, 5 Aug 2019 17:27:22 -0700 Subject: [PATCH 039/113] flake troubleshooting --- azdo_pipelines/base-pipeline.yml | 5 +++-- 1 file changed, 3 insertions(+), 2 deletions(-) diff --git a/azdo_pipelines/base-pipeline.yml b/azdo_pipelines/base-pipeline.yml index c7ff2143..d6d79d49 100644 --- a/azdo_pipelines/base-pipeline.yml +++ b/azdo_pipelines/base-pipeline.yml @@ -3,8 +3,9 @@ parameters: steps: - script: | - flake8 --output-file=$(Build.BinariesDirectory)/flake8_amlservice_testresults.xml aml_service - flake8 --output-file=$(Build.BinariesDirectory)/flake8_tests_testresults.xml tests + printenv + #flake8 --output-file=$(Build.BinariesDirectory)/flake8_amlservice_testresults.xml aml_service + #flake8 --output-file=$(Build.BinariesDirectory)/flake8_tests_testresults.xml tests workingDirectory: '$(Build.SourcesDirectory)' displayName: 'Run code quality tests' enabled: 'true' From bd31cb7781c5119ecd8da2b9b45616a5c8e61978 Mon Sep 17 00:00:00 2001 From: Eugene Fedorenko Date: Mon, 5 Aug 2019 17:32:53 -0700 Subject: [PATCH 040/113] flake troubleshooting --- azdo_pipelines/base-pipeline.yml | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/azdo_pipelines/base-pipeline.yml b/azdo_pipelines/base-pipeline.yml index d6d79d49..b09891ed 100644 --- a/azdo_pipelines/base-pipeline.yml +++ b/azdo_pipelines/base-pipeline.yml @@ -3,8 +3,8 @@ parameters: steps: - script: | - printenv - #flake8 --output-file=$(Build.BinariesDirectory)/flake8_amlservice_testresults.xml aml_service + ls $BUILD_SOURCESDIRECTORY + flake8 --output-file=$(Build.BinariesDirectory)/flake8_amlservice_testresults.xml aml_service #flake8 --output-file=$(Build.BinariesDirectory)/flake8_tests_testresults.xml tests workingDirectory: '$(Build.SourcesDirectory)' displayName: 'Run code quality tests' From d1c494a10516b1c782488b0022c59581734d70ca Mon Sep 17 00:00:00 2001 From: Eugene Fedorenko Date: Mon, 5 Aug 2019 18:13:59 -0700 Subject: [PATCH 041/113] flake troubleshooting --- azdo_pipelines/base-pipeline.yml | 3 ++- 1 file changed, 2 insertions(+), 1 deletion(-) diff --git a/azdo_pipelines/base-pipeline.yml b/azdo_pipelines/base-pipeline.yml index b09891ed..2e1a0d9d 100644 --- a/azdo_pipelines/base-pipeline.yml +++ b/azdo_pipelines/base-pipeline.yml @@ -4,7 +4,8 @@ parameters: steps: - script: | ls $BUILD_SOURCESDIRECTORY - flake8 --output-file=$(Build.BinariesDirectory)/flake8_amlservice_testresults.xml aml_service + flake8 + #flake8 --output-file=$(Build.BinariesDirectory)/flake8_amlservice_testresults.xml aml_service #flake8 --output-file=$(Build.BinariesDirectory)/flake8_tests_testresults.xml tests workingDirectory: '$(Build.SourcesDirectory)' displayName: 'Run code quality tests' From 54dcf260b2df4e634981240c97e92e730f1a80bb Mon Sep 17 00:00:00 2001 From: Eugene Fedorenko Date: Mon, 5 Aug 2019 18:24:26 -0700 Subject: [PATCH 042/113] flake troubleshooting --- azdo_pipelines/base-pipeline.yml | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/azdo_pipelines/base-pipeline.yml b/azdo_pipelines/base-pipeline.yml index 2e1a0d9d..38c9f656 100644 --- a/azdo_pipelines/base-pipeline.yml +++ b/azdo_pipelines/base-pipeline.yml @@ -4,8 +4,8 @@ parameters: steps: - script: | ls $BUILD_SOURCESDIRECTORY - flake8 - #flake8 --output-file=$(Build.BinariesDirectory)/flake8_amlservice_testresults.xml aml_service + flake8 --output-file=$(Build.BinariesDirectory)/flake8_amlservice_testresults.xml aml_service + cat $(Build.BinariesDirectory)/flake8_amlservice_testresults.xml #flake8 --output-file=$(Build.BinariesDirectory)/flake8_tests_testresults.xml tests workingDirectory: '$(Build.SourcesDirectory)' displayName: 'Run code quality tests' From 7e6a2a06878393e87c213fcda373948b0f1a777e Mon Sep 17 00:00:00 2001 From: Eugene Fedorenko Date: Tue, 6 Aug 2019 11:23:06 -0700 Subject: [PATCH 043/113] cleaning up --- aml_config/conda_dependencies.yml | 50 ----- aml_config/config.json | 6 - aml_config/security_config.json | 15 -- aml_service/archived/00-WorkSpace.py | 64 ------ aml_service/archived/01-Experiment.py | 44 ---- aml_service/archived/02-AttachTrainingVM.py | 78 ------- aml_service/archived/03-AttachAmlCluster.py | 66 ------ aml_service/archived/04-AmlPipelines.py | 211 ------------------ aml_service/archived/05-TriggerAmlPipeline.py | 57 ----- aml_service/archived/10-TrainOnLocal.py | 73 ------ aml_service/archived/11-TrainOnLocalEnv.py | 82 ------- aml_service/archived/12-TrainOnVM.py | 80 ------- aml_service/archived/15-EvaluateModel.py | 93 -------- aml_service/archived/20-RegisterModel.py | 92 -------- aml_service/archived/30-CreateScoringImage.py | 111 --------- .../archived/34-GetScoringImageName.py | 44 ---- aml_service/archived/50-deployOnAci.py | 88 -------- aml_service/archived/51-deployOnAks.py | 124 ---------- aml_service/archived/60-AciWebserviceTest.py | 63 ------ aml_service/archived/61-AksWebserviceTest.py | 66 ------ aml_service/archived/helper/azcli.py | 73 ------ azdo_pipelines/base-pipeline.yml | 13 +- azdo_pipelines/build-train.yml | 4 +- 23 files changed, 7 insertions(+), 1590 deletions(-) delete mode 100644 aml_config/conda_dependencies.yml delete mode 100644 aml_config/config.json delete mode 100644 aml_config/security_config.json delete mode 100644 aml_service/archived/00-WorkSpace.py delete mode 100644 aml_service/archived/01-Experiment.py delete mode 100644 aml_service/archived/02-AttachTrainingVM.py delete mode 100644 aml_service/archived/03-AttachAmlCluster.py delete mode 100644 aml_service/archived/04-AmlPipelines.py delete mode 100644 aml_service/archived/05-TriggerAmlPipeline.py delete mode 100644 aml_service/archived/10-TrainOnLocal.py delete mode 100644 aml_service/archived/11-TrainOnLocalEnv.py delete mode 100644 aml_service/archived/12-TrainOnVM.py delete mode 100644 aml_service/archived/15-EvaluateModel.py delete mode 100644 aml_service/archived/20-RegisterModel.py delete mode 100644 aml_service/archived/30-CreateScoringImage.py delete mode 100644 aml_service/archived/34-GetScoringImageName.py delete mode 100644 aml_service/archived/50-deployOnAci.py delete mode 100644 aml_service/archived/51-deployOnAks.py delete mode 100644 aml_service/archived/60-AciWebserviceTest.py delete mode 100644 aml_service/archived/61-AksWebserviceTest.py delete mode 100644 aml_service/archived/helper/azcli.py diff --git a/aml_config/conda_dependencies.yml b/aml_config/conda_dependencies.yml deleted file mode 100644 index 48505e28..00000000 --- a/aml_config/conda_dependencies.yml +++ /dev/null @@ -1,50 +0,0 @@ -# Conda environment specification. The dependencies defined in this file will - -# be automatically provisioned for managed runs. These include runs against - -# the localdocker, remotedocker, and cluster compute targets. - - -# Note that this file is NOT used to automatically manage dependencies for the - -# local compute target. To provision these dependencies locally, run: - -# conda env update --file conda_dependencies.yml - - -# Details about the Conda environment file format: - -# https://conda.io/docs/using/envs.html#create-environment-file-by-hand - - -# For managing Spark packages and configuration, see spark_dependencies.yml. - - -# Version of this configuration file's structure and semantics in AzureML. - -# This directive is stored in a comment to preserve the Conda file structure. - -# [AzureMlVersion] = 2 - - -name: project_environment -dependencies: - # The python interpreter version. - - # Currently Azure ML Workbench only supports 3.5.2 and later. - -- python=3.6.2 - # Required by azureml-defaults, installed separately through Conda to - - # get a prebuilt version and not require build tools for the install. - -- psutil=5.3 - -- pip: - # Required packages for AzureML execution, history, and data preparation. - - azureml-sdk[notebooks] - - pynacl==1.2.1 - - scipy==1.0.0 - - scikit-learn==0.19.1 - - pandas==0.23.1 - - numpy==1.14.5 \ No newline at end of file diff --git a/aml_config/config.json b/aml_config/config.json deleted file mode 100644 index 7105ecf7..00000000 --- a/aml_config/config.json +++ /dev/null @@ -1,6 +0,0 @@ -{ - "subscription_id": "<>", - "resource_group": "DevOps_AzureML_Demo", - "workspace_name": "AzureML_Demo_ws", - "location": "southcentralus" -} diff --git a/aml_config/security_config.json b/aml_config/security_config.json deleted file mode 100644 index 777d0f1b..00000000 --- a/aml_config/security_config.json +++ /dev/null @@ -1,15 +0,0 @@ -{ - "sp_user" : "<>", - "sp_password" : "<>", - "sp_tenant_id" : "<>", - "remote_vm_name" : "<>", - "remote_vm_username" : "<>", - "remote_vm_password" : "<>", - "remote_vm_ip" : "<>", - "experiment_name" : "devops-ai-demo", - "aml_cluster_name" : "aml-compute", - "model_name" : "sklearn_regression_model.pkl", - "vnet_resourcegroup_name" : "<>", - "vnet_name" : "<>", - "subnet_name" : "<>" -} \ No newline at end of file diff --git a/aml_service/archived/00-WorkSpace.py b/aml_service/archived/00-WorkSpace.py deleted file mode 100644 index f234ed4c..00000000 --- a/aml_service/archived/00-WorkSpace.py +++ /dev/null @@ -1,64 +0,0 @@ -""" -Copyright (C) Microsoft Corporation. All rights reserved.​ - ​ -Microsoft Corporation (“Microsoft”) grants you a nonexclusive, perpetual, -royalty-free right to use, copy, and modify the software code provided by us -("Software Code"). You may not sublicense the Software Code or any use of it -(except to your affiliates and to vendors to perform work on your behalf) -through distribution, network access, service agreement, lease, rental, or -otherwise. This license does not purport to express any claim of ownership over -data you may have shared with Microsoft in the creation of the Software Code. -Unless applicable law gives you more rights, Microsoft reserves all other -rights not expressly granted herein, whether by implication, estoppel or -otherwise. ​ - ​ -THE SOFTWARE CODE IS PROVIDED “AS IS”, WITHOUT WARRANTY OF ANY KIND, EXPRESS -OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, -FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL -MICROSOFT OR ITS LICENSORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, -SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, -PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR -BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER -IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -ARISING IN ANY WAY OUT OF THE USE OF THE SOFTWARE CODE, EVEN IF ADVISED OF THE -POSSIBILITY OF SUCH DAMAGE. -""" -from azureml.core import Workspace -import os, json, sys -import azureml.core -from azureml.core.authentication import AzureCliAuthentication - -print("SDK Version:", azureml.core.VERSION) -# print('current dir is ' +os.curdir) -with open("aml_config/config.json") as f: - config = json.load(f) - -workspace_name = config["workspace_name"] -resource_group = config["resource_group"] -subscription_id = config["subscription_id"] -location = config["location"] - -cli_auth = AzureCliAuthentication() - -try: - ws = Workspace.get( - name=workspace_name, - subscription_id=subscription_id, - resource_group=resource_group, - auth=cli_auth, - ) - -except: - # this call might take a minute or two. - print("Creating new workspace") - ws = Workspace.create( - name=workspace_name, - subscription_id=subscription_id, - resource_group=resource_group, - # create_resource_group=True, - location=location, - auth=cli_auth, - ) - -# print Workspace details -print(ws.name, ws.resource_group, ws.location, ws.subscription_id, sep="\n") diff --git a/aml_service/archived/01-Experiment.py b/aml_service/archived/01-Experiment.py deleted file mode 100644 index b3543e1c..00000000 --- a/aml_service/archived/01-Experiment.py +++ /dev/null @@ -1,44 +0,0 @@ -""" -Copyright (C) Microsoft Corporation. All rights reserved.​ - ​ -Microsoft Corporation (“Microsoft”) grants you a nonexclusive, perpetual, -royalty-free right to use, copy, and modify the software code provided by us -("Software Code"). You may not sublicense the Software Code or any use of it -(except to your affiliates and to vendors to perform work on your behalf) -through distribution, network access, service agreement, lease, rental, or -otherwise. This license does not purport to express any claim of ownership over -data you may have shared with Microsoft in the creation of the Software Code. -Unless applicable law gives you more rights, Microsoft reserves all other -rights not expressly granted herein, whether by implication, estoppel or -otherwise. ​ - ​ -THE SOFTWARE CODE IS PROVIDED “AS IS”, WITHOUT WARRANTY OF ANY KIND, EXPRESS -OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, -FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL -MICROSOFT OR ITS LICENSORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, -SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, -PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR -BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER -IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -ARISING IN ANY WAY OUT OF THE USE OF THE SOFTWARE CODE, EVEN IF ADVISED OF THE -POSSIBILITY OF SUCH DAMAGE. -""" -import os -from azureml.core import Experiment -from azureml.core import Workspace -from azureml.core.authentication import AzureCliAuthentication - -cli_auth = AzureCliAuthentication() - - -def getExperiment(): - ws = Workspace.from_config(auth=cli_auth) - script_folder = "." - experiment_name = "devops-ai-demo" - exp = Experiment(workspace=ws, name=experiment_name) - print(exp.name, exp.workspace.name, sep="\n") - return exp - - -if __name__ == "__main__": - exp = getExperiment() diff --git a/aml_service/archived/02-AttachTrainingVM.py b/aml_service/archived/02-AttachTrainingVM.py deleted file mode 100644 index 3fc11c25..00000000 --- a/aml_service/archived/02-AttachTrainingVM.py +++ /dev/null @@ -1,78 +0,0 @@ -""" -Copyright (C) Microsoft Corporation. All rights reserved.​ - ​ -Microsoft Corporation (“Microsoft”) grants you a nonexclusive, perpetual, -royalty-free right to use, copy, and modify the software code provided by us -("Software Code"). You may not sublicense the Software Code or any use of it -(except to your affiliates and to vendors to perform work on your behalf) -through distribution, network access, service agreement, lease, rental, or -otherwise. This license does not purport to express any claim of ownership over -data you may have shared with Microsoft in the creation of the Software Code. -Unless applicable law gives you more rights, Microsoft reserves all other -rights not expressly granted herein, whether by implication, estoppel or -otherwise. ​ - ​ -THE SOFTWARE CODE IS PROVIDED “AS IS”, WITHOUT WARRANTY OF ANY KIND, EXPRESS -OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, -FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL -MICROSOFT OR ITS LICENSORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, -SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, -PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR -BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER -IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -ARISING IN ANY WAY OUT OF THE USE OF THE SOFTWARE CODE, EVEN IF ADVISED OF THE -POSSIBILITY OF SUCH DAMAGE. -""" - -from azureml.core import Workspace -from azureml.core import Run -from azureml.core import Experiment -from azureml.core.conda_dependencies import CondaDependencies -from azureml.core.runconfig import RunConfiguration -import os, json -from azureml.core.compute import RemoteCompute -from azureml.core.compute import DsvmCompute -from azureml.core.compute_target import ComputeTargetException -from azureml.core.authentication import AzureCliAuthentication - -cli_auth = AzureCliAuthentication() - -# Get workspace -ws = Workspace.from_config(auth=cli_auth) - -# Read the New VM Config -with open("aml_config/security_config.json") as f: - config = json.load(f) - -remote_vm_name = config["remote_vm_name"] -remote_vm_username = config["remote_vm_username"] -remote_vm_password = config["remote_vm_password"] -remote_vm_ip = config["remote_vm_ip"] - -try: - dsvm_compute = RemoteCompute.attach( - ws, - name=remote_vm_name, - username=remote_vm_username, - address=remote_vm_ip, - ssh_port=22, - password=remote_vm_password, - ) - dsvm_compute.wait_for_completion(show_output=True) - -except Exception as e: - print("Caught = {}".format(e.message)) - print("Compute config already attached.") - - -## Create VM if not available -# compute_target_name = remote_vm_name - -# try: -# dsvm_compute = DsvmCompute(workspace=ws, name=compute_target_name) -# print('found existing:', dsvm_compute.name) -# except ComputeTargetException: -# print('creating new.') -# dsvm_config = DsvmCompute.provisioning_configuration(vm_size="Standard_D2_v2") -# dsvm_compute = DsvmCompute.create(ws, name=compute_target_name, provisioning_configuration=dsvm_config) -# dsvm_compute.wait_for_completion(show_output=True) diff --git a/aml_service/archived/03-AttachAmlCluster.py b/aml_service/archived/03-AttachAmlCluster.py deleted file mode 100644 index 1ba3f127..00000000 --- a/aml_service/archived/03-AttachAmlCluster.py +++ /dev/null @@ -1,66 +0,0 @@ -""" -Copyright (C) Microsoft Corporation. All rights reserved.​ - -Microsoft Corporation (“Microsoft”) grants you a nonexclusive, perpetual, -royalty-free right to use, copy, and modify the software code provided by us -("Software Code"). You may not sublicense the Software Code or any use of it -(except to your affiliates and to vendors to perform work on your behalf) -through distribution, network access, service agreement, lease, rental, or -otherwise. This license does not purport to express any claim of ownership over -data you may have shared with Microsoft in the creation of the Software Code. -Unless applicable law gives you more rights, Microsoft reserves all other -rights not expressly granted herein, whether by implication, estoppel or -otherwise. ​ - -THE SOFTWARE CODE IS PROVIDED “AS IS”, WITHOUT WARRANTY OF ANY KIND, EXPRESS -OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, -FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL -MICROSOFT OR ITS LICENSORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, -SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, -PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR -BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER -IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -ARISING IN ANY WAY OUT OF THE USE OF THE SOFTWARE CODE, EVEN IF ADVISED OF THE -POSSIBILITY OF SUCH DAMAGE. -""" - -from azureml.core import Workspace -from azureml.core.compute import ComputeTarget, AmlCompute -from azureml.core.compute_target import ComputeTargetException -from azureml.core.authentication import AzureCliAuthentication -import os, json - -cli_auth = AzureCliAuthentication() -# Get workspace -ws = Workspace.from_config(auth=cli_auth) - -# Read the New VM Config -with open("aml_config/security_config.json") as f: - config = json.load(f) - -aml_cluster_name = config["aml_cluster_name"] - -# un-comment the below lines if you want to put AML Compute under Vnet. Also update /aml_config/security_config.json -# vnet_resourcegroup_name = config['vnet_resourcegroup_name'] -# vnet_name = config['vnet_name'] -# subnet_name = config['subnet_name'] - -# Verify that cluster does not exist already -try: - cpu_cluster = ComputeTarget(workspace=ws, name=aml_cluster_name) - print("Found existing cluster, use it.") -except ComputeTargetException: - compute_config = AmlCompute.provisioning_configuration( - vm_size="STANDARD_D2_V2", - vm_priority="dedicated", - min_nodes=1, - max_nodes=3, - idle_seconds_before_scaledown="300", - # #Uncomment the below lines for VNet support - # vnet_resourcegroup_name=vnet_resourcegroup_name, - # vnet_name=vnet_name, - # subnet_name=subnet_name - ) - cpu_cluster = ComputeTarget.create(ws, aml_cluster_name, compute_config) - -cpu_cluster.wait_for_completion(show_output=True) diff --git a/aml_service/archived/04-AmlPipelines.py b/aml_service/archived/04-AmlPipelines.py deleted file mode 100644 index 44d389e5..00000000 --- a/aml_service/archived/04-AmlPipelines.py +++ /dev/null @@ -1,211 +0,0 @@ -""" -Copyright (C) Microsoft Corporation. All rights reserved.​ - ​ -Microsoft Corporation (“Microsoft”) grants you a nonexclusive, perpetual, -royalty-free right to use, copy, and modify the software code provided by us -("Software Code"). You may not sublicense the Software Code or any use of it -(except to your affiliates and to vendors to perform work on your behalf) -through distribution, network access, service agreement, lease, rental, or -otherwise. This license does not purport to express any claim of ownership over -data you may have shared with Microsoft in the creation of the Software Code. -Unless applicable law gives you more rights, Microsoft reserves all other -rights not expressly granted herein, whether by implication, estoppel or -otherwise. ​ - ​ -THE SOFTWARE CODE IS PROVIDED “AS IS”, WITHOUT WARRANTY OF ANY KIND, EXPRESS -OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, -FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL -MICROSOFT OR ITS LICENSORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, -SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, -PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR -BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER -IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -ARISING IN ANY WAY OUT OF THE USE OF THE SOFTWARE CODE, EVEN IF ADVISED OF THE -POSSIBILITY OF SUCH DAMAGE. -""" - -import os, json, requests, datetime -import argparse -from azureml.core import Workspace, Experiment, Datastore -from azureml.core.runconfig import RunConfiguration, CondaDependencies -from azureml.data.data_reference import DataReference -from azureml.pipeline.core import Pipeline, PipelineData, StepSequence -from azureml.pipeline.steps import PythonScriptStep -from azureml.pipeline.core import PublishedPipeline -from azureml.pipeline.core.graph import PipelineParameter -from azureml.core.compute import ComputeTarget - -# from azureml.widgets import RunDetails -from azureml.core.authentication import AzureCliAuthentication - -print("Pipeline SDK-specific imports completed") - -cli_auth = AzureCliAuthentication() - - -parser = argparse.ArgumentParser("Pipeline") -parser.add_argument( - "--pipeline_action", - type=str, - choices=["pipeline-test", "publish"], - help="Determines if pipeline needs to run on small data set \ - or pipeline needs to be republished", - #default="pipeline-test", -) - -args = parser.parse_args() - - -# Get workspace -ws = Workspace.from_config(path="aml_config/config.json", auth=cli_auth) -def_blob_store = Datastore(ws, "workspaceblobstore") - -# Get AML Compute name and Experiment Name -with open("aml_config/security_config.json") as f: - config = json.load(f) - -experiment_name = config["experiment_name"] -aml_cluster_name = config["aml_cluster_name"] -aml_pipeline_name = "training-pipeline" -#model_name = config["model_name"] -model_name = PipelineParameter(name="model_name", default_value="sklearn_regression_model.pkl") - -source_directory = "code" - -# Run Config -# Declare packages dependencies required in the pipeline (these can also be expressed as a YML file) -# cd = CondaDependencies.create(pip_packages=["azureml-defaults", 'tensorflow==1.8.0']) -cd = CondaDependencies("aml_config/conda_dependencies.yml") - -run_config = RunConfiguration(conda_dependencies=cd) -aml_compute = ws.compute_targets[aml_cluster_name] -run_config.environment.docker.enabled = True -run_config.environment.spark.precache_packages = False - -jsonconfigs = PipelineData("jsonconfigs", datastore=def_blob_store) - -# Suffix for all the config files -config_suffix = datetime.datetime.now().strftime("%Y%m%d%H") -print("PipelineData object created") - -# Create python script step to run the training/scoring main script -train = PythonScriptStep( - name="Train New Model", - script_name="training/train.py", - compute_target=aml_compute, - source_directory=source_directory, - arguments=[ - "--config_suffix", config_suffix, - "--json_config", jsonconfigs, - "--model_name", model_name, - ], - runconfig=run_config, - # inputs=[jsonconfigs], - outputs=[jsonconfigs], - allow_reuse=False, -) -print("Step Train created") - -evaluate = PythonScriptStep( - name="Evaluate New Model with Prod Model", - script_name="evaluate/evaluate_model.py", - compute_target=aml_compute, - source_directory=source_directory, - arguments=[ - "--config_suffix", config_suffix, - "--json_config", jsonconfigs, - ], - runconfig=run_config, - inputs=[jsonconfigs], - # outputs=[jsonconfigs], - allow_reuse=False, -) -print("Step Evaluate created") - -register_model = PythonScriptStep( - name="Register New Trained Model", - script_name="register/register_model.py", - compute_target=aml_compute, - source_directory=source_directory, - arguments=[ - "--config_suffix", config_suffix, - "--json_config", jsonconfigs, - "--model_name", model_name, - ], - runconfig=run_config, - inputs=[jsonconfigs], - # outputs=[jsonconfigs], - allow_reuse=False, -) -print("Step register model created") - -# Package model step is moved to Azure DevOps Release Pipeline -# package_model = PythonScriptStep( -# name="Package Model as Scoring Image", -# script_name="scoring/create_scoring_image.py", -# compute_target=aml_compute, -# source_directory=source_directory, -# arguments=["--config_suffix", config_suffix, "--json_config", jsonconfigs], -# runconfig=run_config, -# inputs=[jsonconfigs], -# # outputs=[jsonconfigs], -# allow_reuse=False, -# ) -# print("Packed the model into a Scoring Image") - -# Create Steps dependency such that they run in sequence -evaluate.run_after(train) -register_model.run_after(evaluate) -#package_model.run_after(register_model) - -steps = [register_model] - - -# Build Pipeline -pipeline1 = Pipeline(workspace=ws, steps=steps) -print("Pipeline is built") - -# Validate Pipeline -pipeline1.validate() -print("Pipeline validation complete") - - -# Submit unpublished pipeline with small data set for test -if args.pipeline_action == "pipeline-test": - pipeline_run1 = Experiment(ws, experiment_name).submit( - pipeline1, regenerate_outputs=True - ) - print("Pipeline is submitted for execution") - pipeline_run1.wait_for_completion(show_output=True) - - -# RunDetails(pipeline_run1).show() - - -# Define pipeline parameters -# run_env = PipelineParameter( -# name="dev_flag", -# default_value=True) - -# dbname = PipelineParameter( -# name="dbname", -# default_value='opex') - - -# Publish Pipeline -if args.pipeline_action == "publish": - published_pipeline1 = pipeline1.publish( - name=aml_pipeline_name, description="Model training/retraining pipeline" - ) - print( - "Pipeline is published as rest_endpoint {} ".format( - published_pipeline1.endpoint - ) - ) - # write published pipeline details as build artifact - pipeline_config = {} - pipeline_config["pipeline_name"] = published_pipeline1.name - pipeline_config["rest_endpoint"] = published_pipeline1.endpoint - pipeline_config["experiment_name"] = "published-pipeline-exp" # experiment_name - with open("aml_config/pipeline_config.json", "w") as outfile: - json.dump(pipeline_config, outfile) diff --git a/aml_service/archived/05-TriggerAmlPipeline.py b/aml_service/archived/05-TriggerAmlPipeline.py deleted file mode 100644 index 66838a62..00000000 --- a/aml_service/archived/05-TriggerAmlPipeline.py +++ /dev/null @@ -1,57 +0,0 @@ -""" -Copyright (C) Microsoft Corporation. All rights reserved.​ - ​ -Microsoft Corporation (“Microsoft”) grants you a nonexclusive, perpetual, -royalty-free right to use, copy, and modify the software code provided by us -("Software Code"). You may not sublicense the Software Code or any use of it -(except to your affiliates and to vendors to perform work on your behalf) -through distribution, network access, service agreement, lease, rental, or -otherwise. This license does not purport to express any claim of ownership over -data you may have shared with Microsoft in the creation of the Software Code. -Unless applicable law gives you more rights, Microsoft reserves all other -rights not expressly granted herein, whether by implication, estoppel or -otherwise. ​ - ​ -THE SOFTWARE CODE IS PROVIDED “AS IS”, WITHOUT WARRANTY OF ANY KIND, EXPRESS -OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, -FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL -MICROSOFT OR ITS LICENSORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, -SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, -PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR -BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER -IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -ARISING IN ANY WAY OUT OF THE USE OF THE SOFTWARE CODE, EVEN IF ADVISED OF THE -POSSIBILITY OF SUCH DAMAGE. -""" - -import os, json, requests, datetime, sys -import argparse -from azureml.core.authentication import AzureCliAuthentication - -try: - with open("aml_config/pipeline_config.json") as f: - config = json.load(f) - with open("aml_config/security_config.json") as f: - security_config = json.load(f) -except: - print("No pipeline config found") - sys.exit(0) - -# Run a published pipeline -cli_auth = AzureCliAuthentication() -aad_token = cli_auth.get_authentication_header() -rest_endpoint1 = config["rest_endpoint"] -experiment_name = config["experiment_name"] -model_name = security_config["model_name"] - -print(rest_endpoint1) - -response = requests.post( - rest_endpoint1, headers=aad_token, - json={"ExperimentName": experiment_name, - "ParameterAssignments": {"model_name":model_name}} -) - -run_id = response.json()["Id"] -print(run_id) -print("Pipeline run initiated") diff --git a/aml_service/archived/10-TrainOnLocal.py b/aml_service/archived/10-TrainOnLocal.py deleted file mode 100644 index d7c71b3b..00000000 --- a/aml_service/archived/10-TrainOnLocal.py +++ /dev/null @@ -1,73 +0,0 @@ -""" -Copyright (C) Microsoft Corporation. All rights reserved.​ - ​ -Microsoft Corporation (“Microsoft”) grants you a nonexclusive, perpetual, -royalty-free right to use, copy, and modify the software code provided by us -("Software Code"). You may not sublicense the Software Code or any use of it -(except to your affiliates and to vendors to perform work on your behalf) -through distribution, network access, service agreement, lease, rental, or -otherwise. This license does not purport to express any claim of ownership over -data you may have shared with Microsoft in the creation of the Software Code. -Unless applicable law gives you more rights, Microsoft reserves all other -rights not expressly granted herein, whether by implication, estoppel or -otherwise. ​ - ​ -THE SOFTWARE CODE IS PROVIDED “AS IS”, WITHOUT WARRANTY OF ANY KIND, EXPRESS -OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, -FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL -MICROSOFT OR ITS LICENSORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, -SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, -PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR -BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER -IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -ARISING IN ANY WAY OUT OF THE USE OF THE SOFTWARE CODE, EVEN IF ADVISED OF THE -POSSIBILITY OF SUCH DAMAGE. -""" - -from azureml.core.runconfig import RunConfiguration -from azureml.core import Workspace -from azureml.core import Experiment -from azureml.core import ScriptRunConfig -import json -from azureml.core.authentication import AzureCliAuthentication - -cli_auth = AzureCliAuthentication() - -# Get workspace -ws = Workspace.from_config(auth=cli_auth) - -# Attach Experiment -experiment_name = "devops-ai-demo" -exp = Experiment(workspace=ws, name=experiment_name) -print(exp.name, exp.workspace.name, sep="\n") - -# Editing a run configuration property on-fly. -run_config_user_managed = RunConfiguration() -run_config_user_managed.environment.python.user_managed_dependencies = True - -print("Submitting an experiment.") -src = ScriptRunConfig( - source_directory="./code", - script="training/train.py", - run_config=run_config_user_managed, -) -run = exp.submit(src) - -# Shows output of the run on stdout. -run.wait_for_completion(show_output=True, wait_post_processing=True) - -# Raise exception if run fails -if run.get_status() == "Failed": - raise Exception( - "Training on local failed with following run status: {} and logs: \n {}".format( - run.get_status(), run.get_details_with_logs() - ) - ) - -# Writing the run id to /aml_config/run_id.json - -run_id = {} -run_id["run_id"] = run.id -run_id["experiment_name"] = run.experiment.name -with open("aml_config/run_id.json", "w") as outfile: - json.dump(run_id, outfile) diff --git a/aml_service/archived/11-TrainOnLocalEnv.py b/aml_service/archived/11-TrainOnLocalEnv.py deleted file mode 100644 index 544a9d93..00000000 --- a/aml_service/archived/11-TrainOnLocalEnv.py +++ /dev/null @@ -1,82 +0,0 @@ -""" -Copyright (C) Microsoft Corporation. All rights reserved.​ - ​ -Microsoft Corporation (“Microsoft”) grants you a nonexclusive, perpetual, -royalty-free right to use, copy, and modify the software code provided by us -("Software Code"). You may not sublicense the Software Code or any use of it -(except to your affiliates and to vendors to perform work on your behalf) -through distribution, network access, service agreement, lease, rental, or -otherwise. This license does not purport to express any claim of ownership over -data you may have shared with Microsoft in the creation of the Software Code. -Unless applicable law gives you more rights, Microsoft reserves all other -rights not expressly granted herein, whether by implication, estoppel or -otherwise. ​ - ​ -THE SOFTWARE CODE IS PROVIDED “AS IS”, WITHOUT WARRANTY OF ANY KIND, EXPRESS -OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, -FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL -MICROSOFT OR ITS LICENSORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, -SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, -PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR -BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER -IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -ARISING IN ANY WAY OUT OF THE USE OF THE SOFTWARE CODE, EVEN IF ADVISED OF THE -POSSIBILITY OF SUCH DAMAGE. -""" -## Create a new Conda environment on local and train the model -## System-managed environment - -from azureml.core.conda_dependencies import CondaDependencies -from azureml.core.runconfig import RunConfiguration -from azureml.core import Workspace -from azureml.core import Experiment -from azureml.core import ScriptRunConfig - -from azureml.core.authentication import AzureCliAuthentication - -cli_auth = AzureCliAuthentication() - -# Get workspace -ws = Workspace.from_config(auth=cli_auth) - -# Attach Experiment -experiment_name = "devops-ai-demo" -exp = Experiment(workspace=ws, name=experiment_name) -print(exp.name, exp.workspace.name, sep="\n") - -# Editing a run configuration property on-fly. -run_config_system_managed = RunConfiguration() -# Use a new conda environment that is to be created from the conda_dependencies.yml file -run_config_system_managed.environment.python.user_managed_dependencies = False -# Automatically create the conda environment before the run -run_config_system_managed.prepare_environment = True - -# # add scikit-learn to the conda_dependencies.yml file -# Specify conda dependencies with scikit-learn -# run_config_system_managed.environment.python.conda_dependencies = CondaDependencies.create(conda_packages=['scikit-learn']) - -print("Submitting an experiment to new conda virtual env") -src = ScriptRunConfig( - source_directory="./code", - script="training/train.py", - run_config=run_config_user_managed, -) -run = exp.submit(src) - -# Shows output of the run on stdout. -run.wait_for_completion(show_output=True, wait_post_processing=True) - -# Raise exception if run fails -if run.get_status() == "Failed": - raise Exception( - "Training on local env failed with following run status: {} and logs: \n {}".format( - run.get_status(), run.get_details_with_logs() - ) - ) - -# Writing the run id to /aml_config/run_id.json -run_id = {} -run_id["run_id"] = run.id -run_id["experiment_name"] = run.experiment.name -with open("aml_config/run_id.json", "w") as outfile: - json.dump(run_id, outfile) diff --git a/aml_service/archived/12-TrainOnVM.py b/aml_service/archived/12-TrainOnVM.py deleted file mode 100644 index 788ffd15..00000000 --- a/aml_service/archived/12-TrainOnVM.py +++ /dev/null @@ -1,80 +0,0 @@ -""" -Copyright (C) Microsoft Corporation. All rights reserved.​ - ​ -Microsoft Corporation (“Microsoft”) grants you a nonexclusive, perpetual, -royalty-free right to use, copy, and modify the software code provided by us -("Software Code"). You may not sublicense the Software Code or any use of it -(except to your affiliates and to vendors to perform work on your behalf) -through distribution, network access, service agreement, lease, rental, or -otherwise. This license does not purport to express any claim of ownership over -data you may have shared with Microsoft in the creation of the Software Code. -Unless applicable law gives you more rights, Microsoft reserves all other -rights not expressly granted herein, whether by implication, estoppel or -otherwise. ​ - ​ -THE SOFTWARE CODE IS PROVIDED “AS IS”, WITHOUT WARRANTY OF ANY KIND, EXPRESS -OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, -FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL -MICROSOFT OR ITS LICENSORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, -SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, -PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR -BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER -IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -ARISING IN ANY WAY OUT OF THE USE OF THE SOFTWARE CODE, EVEN IF ADVISED OF THE -POSSIBILITY OF SUCH DAMAGE. -""" -import os, json -from azureml.core import Workspace -from azureml.core import Experiment -from azureml.core.compute import RemoteCompute -from azureml.core.runconfig import RunConfiguration -from azureml.core import ScriptRunConfig -import azureml.core -from azureml.core.authentication import AzureCliAuthentication - -cli_auth = AzureCliAuthentication() -# Get workspace -ws = Workspace.from_config(auth=cli_auth) - - -# Read the New VM Config -with open("aml_config/security_config.json") as f: - config = json.load(f) -remote_vm_name = config["remote_vm_name"] - - -# Attach Experiment -experiment_name = "devops-ai-demo" -exp = Experiment(workspace=ws, name=experiment_name) -print(exp.name, exp.workspace.name, sep="\n") - -run_config = RunConfiguration() -run_config.target = remote_vm_name - -# replace with your path to the python interpreter in the remote VM found earlier -run_config.environment.python.interpreter_path = "/anaconda/envs/myenv/bin/python" -run_config.environment.python.user_managed_dependencies = True - - -src = ScriptRunConfig( - source_directory="./code", script="training/train.py", run_config=run_config -) -run = exp.submit(src) - -# Shows output of the run on stdout. -run.wait_for_completion(show_output=True, wait_post_processing=True) - -# Raise exception if run fails -if run.get_status() == "Failed": - raise Exception( - "Training on local env failed with following run status: {} and logs: \n {}".format( - run.get_status(), run.get_details_with_logs() - ) - ) - -# Writing the run id to /aml_config/run_id.json -run_id = {} -run_id["run_id"] = run.id -run_id["experiment_name"] = run.experiment.name -with open("aml_config/run_id.json", "w") as outfile: - json.dump(run_id, outfile) diff --git a/aml_service/archived/15-EvaluateModel.py b/aml_service/archived/15-EvaluateModel.py deleted file mode 100644 index 4d266a98..00000000 --- a/aml_service/archived/15-EvaluateModel.py +++ /dev/null @@ -1,93 +0,0 @@ -""" -Copyright (C) Microsoft Corporation. All rights reserved.​ - ​ -Microsoft Corporation (“Microsoft”) grants you a nonexclusive, perpetual, -royalty-free right to use, copy, and modify the software code provided by us -("Software Code"). You may not sublicense the Software Code or any use of it -(except to your affiliates and to vendors to perform work on your behalf) -through distribution, network access, service agreement, lease, rental, or -otherwise. This license does not purport to express any claim of ownership over -data you may have shared with Microsoft in the creation of the Software Code. -Unless applicable law gives you more rights, Microsoft reserves all other -rights not expressly granted herein, whether by implication, estoppel or -otherwise. ​ - ​ -THE SOFTWARE CODE IS PROVIDED “AS IS”, WITHOUT WARRANTY OF ANY KIND, EXPRESS -OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, -FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL -MICROSOFT OR ITS LICENSORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, -SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, -PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR -BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER -IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -ARISING IN ANY WAY OUT OF THE USE OF THE SOFTWARE CODE, EVEN IF ADVISED OF THE -POSSIBILITY OF SUCH DAMAGE. -""" -import os, json -from azureml.core import Workspace -from azureml.core import Experiment -from azureml.core.model import Model -import azureml.core -from azureml.core import Run -from azureml.core.authentication import AzureCliAuthentication - -cli_auth = AzureCliAuthentication() - -# Get workspace -ws = Workspace.from_config(auth=cli_auth) - -# Paramaterize the matrics on which the models should be compared - -# Add golden data set on which all the model performance can be evaluated - -# Get the latest run_id -with open("aml_config/run_id.json") as f: - config = json.load(f) - -new_model_run_id = config["run_id"] -experiment_name = config["experiment_name"] -exp = Experiment(workspace=ws, name=experiment_name) - - -try: - # Get most recently registered model, we assume that is the model in production. Download this model and compare it with the recently trained model by running test with same data set. - model_list = Model.list(ws) - production_model = next( - filter( - lambda x: x.created_time == max(model.created_time for model in model_list), - model_list, - ) - ) - production_model_run_id = production_model.tags.get("run_id") - run_list = exp.get_runs() - # production_model_run = next(filter(lambda x: x.id == production_model_run_id, run_list)) - - # Get the run history for both production model and newly trained model and compare mse - production_model_run = Run(exp, run_id=production_model_run_id) - new_model_run = Run(exp, run_id=new_model_run_id) - - production_model_mse = production_model_run.get_metrics().get("mse") - new_model_mse = new_model_run.get_metrics().get("mse") - print( - "Current Production model mse: {}, New trained model mse: {}".format( - production_model_mse, new_model_mse - ) - ) - - promote_new_model = False - if new_model_mse < production_model_mse: - promote_new_model = True - print("New trained model performs better, thus it will be registered") -except: - promote_new_model = True - print("This is the first model to be trained, thus nothing to evaluate for now") - -run_id = {} -run_id["run_id"] = "" -# Writing the run id to /aml_config/run_id.json -if promote_new_model: - run_id["run_id"] = new_model_run_id - -run_id["experiment_name"] = experiment_name -with open("aml_config/run_id.json", "w") as outfile: - json.dump(run_id, outfile) diff --git a/aml_service/archived/20-RegisterModel.py b/aml_service/archived/20-RegisterModel.py deleted file mode 100644 index bd9a7bbc..00000000 --- a/aml_service/archived/20-RegisterModel.py +++ /dev/null @@ -1,92 +0,0 @@ -""" -Copyright (C) Microsoft Corporation. All rights reserved.​ - ​ -Microsoft Corporation (“Microsoft”) grants you a nonexclusive, perpetual, -royalty-free right to use, copy, and modify the software code provided by us -("Software Code"). You may not sublicense the Software Code or any use of it -(except to your affiliates and to vendors to perform work on your behalf) -through distribution, network access, service agreement, lease, rental, or -otherwise. This license does not purport to express any claim of ownership over -data you may have shared with Microsoft in the creation of the Software Code. -Unless applicable law gives you more rights, Microsoft reserves all other -rights not expressly granted herein, whether by implication, estoppel or -otherwise. ​ - ​ -THE SOFTWARE CODE IS PROVIDED “AS IS”, WITHOUT WARRANTY OF ANY KIND, EXPRESS -OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, -FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL -MICROSOFT OR ITS LICENSORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, -SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, -PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR -BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER -IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -ARISING IN ANY WAY OUT OF THE USE OF THE SOFTWARE CODE, EVEN IF ADVISED OF THE -POSSIBILITY OF SUCH DAMAGE. -""" -import os, json, sys -from azureml.core import Workspace -from azureml.core import Run -from azureml.core import Experiment -from azureml.core.model import Model - -from azureml.core.runconfig import RunConfiguration -from azureml.core.authentication import AzureCliAuthentication - -cli_auth = AzureCliAuthentication() - -# Get workspace -ws = Workspace.from_config(auth=cli_auth) - -# Get the latest evaluation result -try: - with open("aml_config/run_id.json") as f: - config = json.load(f) - if not config["run_id"]: - raise Exception("No new model to register as production model perform better") -except: - print("No new model to register as production model perform better") - # raise Exception('No new model to register as production model perform better') - sys.exit(0) - -run_id = config["run_id"] -experiment_name = config["experiment_name"] -exp = Experiment(workspace=ws, name=experiment_name) - -run = Run(experiment=exp, run_id=run_id) -names = run.get_file_names -names() -print("Run ID for last run: {}".format(run_id)) -model_local_dir = "model" -os.makedirs(model_local_dir, exist_ok=True) - -# Download Model to Project root directory -model_name = "sklearn_regression_model.pkl" -run.download_file( - name="./outputs/" + model_name, output_file_path="./model/" + model_name -) -print("Downloaded model {} to Project root directory".format(model_name)) -os.chdir("./model") -model = Model.register( - model_path=model_name, # this points to a local file - model_name=model_name, # this is the name the model is registered as - tags={"area": "diabetes", "type": "regression", "run_id": run_id}, - description="Regression model for diabetes dataset", - workspace=ws, -) -os.chdir("..") -print( - "Model registered: {} \nModel Description: {} \nModel Version: {}".format( - model.name, model.description, model.version - ) -) - -# Remove the evaluate.json as we no longer need it -# os.remove("aml_config/evaluate.json") - -# Writing the registered model details to /aml_config/model.json -model_json = {} -model_json["model_name"] = model.name -model_json["model_version"] = model.version -model_json["run_id"] = run_id -with open("aml_config/model.json", "w") as outfile: - json.dump(model_json, outfile) diff --git a/aml_service/archived/30-CreateScoringImage.py b/aml_service/archived/30-CreateScoringImage.py deleted file mode 100644 index 4c7597e1..00000000 --- a/aml_service/archived/30-CreateScoringImage.py +++ /dev/null @@ -1,111 +0,0 @@ -""" -Copyright (C) Microsoft Corporation. All rights reserved.​ - ​ -Microsoft Corporation (“Microsoft”) grants you a nonexclusive, perpetual, -royalty-free right to use, copy, and modify the software code provided by us -("Software Code"). You may not sublicense the Software Code or any use of it -(except to your affiliates and to vendors to perform work on your behalf) -through distribution, network access, service agreement, lease, rental, or -otherwise. This license does not purport to express any claim of ownership over -data you may have shared with Microsoft in the creation of the Software Code. -Unless applicable law gives you more rights, Microsoft reserves all other -rights not expressly granted herein, whether by implication, estoppel or -otherwise. ​ - ​ -THE SOFTWARE CODE IS PROVIDED “AS IS”, WITHOUT WARRANTY OF ANY KIND, EXPRESS -OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, -FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL -MICROSOFT OR ITS LICENSORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, -SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, -PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR -BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER -IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -ARISING IN ANY WAY OUT OF THE USE OF THE SOFTWARE CODE, EVEN IF ADVISED OF THE -POSSIBILITY OF SUCH DAMAGE. -""" -import os, json, sys -from azureml.core import Workspace -from azureml.core.image import ContainerImage, Image -from azureml.core.model import Model -from azureml.core.authentication import AzureCliAuthentication - -cli_auth = AzureCliAuthentication() - -# Get workspace -ws = Workspace.from_config(auth=cli_auth) - -# Get the latest model details - -# try: -# with open("aml_config/model.json") as f: -# config = json.load(f) -# except: -# print("No new model to register thus no need to create new scoring image") -# # raise Exception('No new model to register as production model perform better') -# sys.exit(0) - -# model_name = config["model_name"] -# model_version = config["model_version"] - - -# model_list = Model.list(workspace=ws) -# model, = (m for m in model_list if m.version == model_version and m.name == model_name) -# print( -# "Model picked: {} \nModel Description: {} \nModel Version: {}".format( -# model.name, model.description, model.version -# ) -# ) - -try: - with open("aml_config/security_config.json") as f: - security_config = json.load(f) -except: - print("No Security Config found") - sys.exit(0) - -# Run a published pipeline -#model_name = "sklearn_regression_model.pkl" -model_name = security_config["model_name"] -model = Model(ws, name=model_name) - -os.chdir("./code/scoring") -image_name = "diabetes-model-score" - -image_config = ContainerImage.image_configuration( - execution_script="score.py", - runtime="python", - conda_file="conda_dependencies.yml", - description="Image with ridge regression model", - tags={"area": "diabetes", "type": "regression"}, -) - -image = Image.create( - name=image_name, models=[model], image_config=image_config, workspace=ws -) - -image.wait_for_creation(show_output=True) -os.chdir("../..") - -if image.creation_state != "Succeeded": - raise Exception("Image creation status: {image.creation_state}") - -print( - "{}(v.{} [{}]) stored at {} with build log {}".format( - image.name, - image.version, - image.creation_state, - image.image_location, - image.image_build_log_uri, - ) -) - -# Writing the image details to /aml_config/image.json -image_json = {} -image_json["image_name"] = image.name -image_json["image_version"] = image.version -image_json["image_location"] = image.image_location -with open("aml_config/image.json", "w") as outfile: - json.dump(image_json, outfile) - - -# How to fix the schema for a model, like if we have multiple models expecting different schema, diff --git a/aml_service/archived/34-GetScoringImageName.py b/aml_service/archived/34-GetScoringImageName.py deleted file mode 100644 index b5f3a764..00000000 --- a/aml_service/archived/34-GetScoringImageName.py +++ /dev/null @@ -1,44 +0,0 @@ -""" -Copyright (C) Microsoft Corporation. All rights reserved.​ - ​ -Microsoft Corporation (“Microsoft”) grants you a nonexclusive, perpetual, -royalty-free right to use, copy, and modify the software code provided by us -("Software Code"). You may not sublicense the Software Code or any use of it -(except to your affiliates and to vendors to perform work on your behalf) -through distribution, network access, service agreement, lease, rental, or -otherwise. This license does not purport to express any claim of ownership over -data you may have shared with Microsoft in the creation of the Software Code. -Unless applicable law gives you more rights, Microsoft reserves all other -rights not expressly granted herein, whether by implication, estoppel or -otherwise. ​ - ​ -THE SOFTWARE CODE IS PROVIDED “AS IS”, WITHOUT WARRANTY OF ANY KIND, EXPRESS -OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, -FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL -MICROSOFT OR ITS LICENSORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, -SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, -PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR -BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER -IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -ARISING IN ANY WAY OUT OF THE USE OF THE SOFTWARE CODE, EVEN IF ADVISED OF THE -POSSIBILITY OF SUCH DAMAGE. -""" -import os, json, sys -from azureml.core import Workspace -from azureml.core.authentication import AzureCliAuthentication - -cli_auth = AzureCliAuthentication() - -# Get workspace -ws = Workspace.from_config(auth=cli_auth) - -# Get the latest image details -latest_image = ws.images -name, version = latest_image.get(list(latest_image)[0]).id.split(':') - -# Writing the image details to /aml_config/image.json -image_json = {} -image_json["image_name"] = name -image_json["image_version"] = int(version) -with open("aml_config/image.json", "w") as outfile: - json.dump(image_json, outfile) diff --git a/aml_service/archived/50-deployOnAci.py b/aml_service/archived/50-deployOnAci.py deleted file mode 100644 index 00313380..00000000 --- a/aml_service/archived/50-deployOnAci.py +++ /dev/null @@ -1,88 +0,0 @@ -""" -Copyright (C) Microsoft Corporation. All rights reserved.​ - ​ -Microsoft Corporation (“Microsoft”) grants you a nonexclusive, perpetual, -royalty-free right to use, copy, and modify the software code provided by us -("Software Code"). You may not sublicense the Software Code or any use of it -(except to your affiliates and to vendors to perform work on your behalf) -through distribution, network access, service agreement, lease, rental, or -otherwise. This license does not purport to express any claim of ownership over -data you may have shared with Microsoft in the creation of the Software Code. -Unless applicable law gives you more rights, Microsoft reserves all other -rights not expressly granted herein, whether by implication, estoppel or -otherwise. ​ - ​ -THE SOFTWARE CODE IS PROVIDED “AS IS”, WITHOUT WARRANTY OF ANY KIND, EXPRESS -OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, -FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL -MICROSOFT OR ITS LICENSORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, -SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, -PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR -BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER -IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -ARISING IN ANY WAY OUT OF THE USE OF THE SOFTWARE CODE, EVEN IF ADVISED OF THE -POSSIBILITY OF SUCH DAMAGE. -""" -import os, json, datetime, sys -from operator import attrgetter -from azureml.core import Workspace -from azureml.core.model import Model -from azureml.core.image import Image -from azureml.core.webservice import Webservice -from azureml.core.webservice import AciWebservice -from azureml.core.authentication import AzureCliAuthentication - -cli_auth = AzureCliAuthentication() -# Get workspace -ws = Workspace.from_config(auth=cli_auth) # Get the Image to deploy details -try: - with open("aml_config/image.json") as f: - config = json.load(f) -except: - print("No new model, thus no deployment on ACI") - # raise Exception('No new model to register as production model perform better') - sys.exit(0) - - -image_name = config["image_name"] -image_version = config["image_version"] - -images = Image.list(workspace=ws) -image, = (m for m in images if m.version == image_version and m.name == image_name) -print( - "From image.json, Image used to deploy webservice on ACI: {}\nImage Version: {}\nImage Location = {}".format( - image.name, image.version, image.image_location - ) -) - -# image = max(images, key=attrgetter('version')) -# print('From Max Version, Image used to deploy webservice on ACI: {}\nImage Version: {}\nImage Location = {}'.format(image.name, image.version, image.image_location)) - - -aciconfig = AciWebservice.deploy_configuration( - cpu_cores=1, - memory_gb=1, - tags={"area": "diabetes", "type": "regression"}, - description="A sample description", -) - -aci_service_name = "aciwebservice" + datetime.datetime.now().strftime("%m%d%H") - -service = Webservice.deploy_from_image( - deployment_config=aciconfig, image=image, name=aci_service_name, workspace=ws -) - -service.wait_for_deployment() -print( - "Deployed ACI Webservice: {} \nWebservice Uri: {}".format( - service.name, service.scoring_uri - ) -) - -# service=Webservice(name ='aciws0622', workspace =ws) -# Writing the ACI details to /aml_config/aci_webservice.json -aci_webservice = {} -aci_webservice["aci_name"] = service.name -aci_webservice["aci_url"] = service.scoring_uri -with open("aml_config/aci_webservice.json", "w") as outfile: - json.dump(aci_webservice, outfile) diff --git a/aml_service/archived/51-deployOnAks.py b/aml_service/archived/51-deployOnAks.py deleted file mode 100644 index 379ea90c..00000000 --- a/aml_service/archived/51-deployOnAks.py +++ /dev/null @@ -1,124 +0,0 @@ -""" -Copyright (C) Microsoft Corporation. All rights reserved.​ - ​ -Microsoft Corporation (“Microsoft”) grants you a nonexclusive, perpetual, -royalty-free right to use, copy, and modify the software code provided by us -("Software Code"). You may not sublicense the Software Code or any use of it -(except to your affiliates and to vendors to perform work on your behalf) -through distribution, network access, service agreement, lease, rental, or -otherwise. This license does not purport to express any claim of ownership over -data you may have shared with Microsoft in the creation of the Software Code. -Unless applicable law gives you more rights, Microsoft reserves all other -rights not expressly granted herein, whether by implication, estoppel or -otherwise. ​ - ​ -THE SOFTWARE CODE IS PROVIDED “AS IS”, WITHOUT WARRANTY OF ANY KIND, EXPRESS -OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, -FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL -MICROSOFT OR ITS LICENSORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, -SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, -PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR -BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER -IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -ARISING IN ANY WAY OUT OF THE USE OF THE SOFTWARE CODE, EVEN IF ADVISED OF THE -POSSIBILITY OF SUCH DAMAGE. -""" -import os, json, datetime, sys -from operator import attrgetter -from azureml.core import Workspace -from azureml.core.model import Model -from azureml.core.image import Image -from azureml.core.compute import AksCompute, ComputeTarget -from azureml.core.webservice import Webservice, AksWebservice -from azureml.core.authentication import AzureCliAuthentication - -cli_auth = AzureCliAuthentication() -# Get workspace -ws = Workspace.from_config(auth=cli_auth) - -# Get the Image to deploy details -try: - with open("aml_config/image.json") as f: - config = json.load(f) -except: - print("No new model, thus no deployment on ACI") - # raise Exception('No new model to register as production model perform better') - sys.exit(0) - -image_name = config["image_name"] -image_version = config["image_version"] - -images = Image.list(workspace=ws) -image, = (m for m in images if m.version == image_version and m.name == image_name) -print( - "From image.json, Image used to deploy webservice on ACI: {}\nImage Version: {}\nImage Location = {}".format( - image.name, image.version, image.image_location - ) -) - -# image = max(images, key=attrgetter('version')) -# print('From Max Version, Image used to deploy webservice on ACI: {}\nImage Version: {}\nImage Location = {}'.format(image.name, image.version, image.image_location)) - -# Check if AKS already Available -try: - with open("aml_config/aks_webservice.json") as f: - config = json.load(f) - aks_name = config["aks_name"] - aks_service_name = config["aks_service_name"] - compute_list = ws.compute_targets() - aks_target, = (c for c in compute_list if c.name == aks_name) - service = Webservice(name=aks_service_name, workspace=ws) - print( - "Updating AKS service {} with image: {}".format( - aks_service_name, image.image_location - ) - ) - service.update(image=image) -except: - aks_name = "aks" + datetime.datetime.now().strftime("%m%d%H") - aks_service_name = "akswebservice" + datetime.datetime.now().strftime("%m%d%H") - prov_config = AksCompute.provisioning_configuration( - agent_count=6, vm_size="Standard_F4s", location="eastus" - ) - print( - "No AKS found in aks_webservice.json. Creating new Aks: {} and AKS Webservice: {}".format( - aks_name, aks_service_name - ) - ) - # Create the cluster - aks_target = ComputeTarget.create( - workspace=ws, name=aks_name, provisioning_configuration=prov_config - ) - - aks_target.wait_for_completion(show_output=True) - print(aks_target.provisioning_state) - print(aks_target.provisioning_errors) - - # Use the default configuration (can also provide parameters to customize) - aks_config = AksWebservice.deploy_configuration(enable_app_insights=True) - - service = Webservice.deploy_from_image( - workspace=ws, - name=aks_service_name, - image=image, - deployment_config=aks_config, - deployment_target=aks_target, - ) - - service.wait_for_deployment(show_output=True) - print(service.state) - print( - "Deployed AKS Webservice: {} \nWebservice Uri: {}".format( - service.name, service.scoring_uri - ) - ) - - -# Writing the AKS details to /aml_config/aks_webservice.json -aks_webservice = {} -aks_webservice["aks_name"] = aks_name -aks_webservice["aks_service_name"] = service.name -aks_webservice["aks_url"] = service.scoring_uri -aks_webservice["aks_keys"] = service.get_keys() -with open("aml_config/aks_webservice.json", "w") as outfile: - json.dump(aks_webservice, outfile) diff --git a/aml_service/archived/60-AciWebserviceTest.py b/aml_service/archived/60-AciWebserviceTest.py deleted file mode 100644 index a8c40f69..00000000 --- a/aml_service/archived/60-AciWebserviceTest.py +++ /dev/null @@ -1,63 +0,0 @@ -""" -Copyright (C) Microsoft Corporation. All rights reserved.​ - ​ -Microsoft Corporation (“Microsoft”) grants you a nonexclusive, perpetual, -royalty-free right to use, copy, and modify the software code provided by us -("Software Code"). You may not sublicense the Software Code or any use of it -(except to your affiliates and to vendors to perform work on your behalf) -through distribution, network access, service agreement, lease, rental, or -otherwise. This license does not purport to express any claim of ownership over -data you may have shared with Microsoft in the creation of the Software Code. -Unless applicable law gives you more rights, Microsoft reserves all other -rights not expressly granted herein, whether by implication, estoppel or -otherwise. ​ - ​ -THE SOFTWARE CODE IS PROVIDED “AS IS”, WITHOUT WARRANTY OF ANY KIND, EXPRESS -OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, -FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL -MICROSOFT OR ITS LICENSORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, -SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, -PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR -BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER -IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -ARISING IN ANY WAY OUT OF THE USE OF THE SOFTWARE CODE, EVEN IF ADVISED OF THE -POSSIBILITY OF SUCH DAMAGE. -""" -import numpy -import os, json, datetime, sys -from operator import attrgetter -from azureml.core import Workspace -from azureml.core.model import Model -from azureml.core.image import Image -from azureml.core.webservice import Webservice -from azureml.core.webservice import AciWebservice -from azureml.core.authentication import AzureCliAuthentication - -cli_auth = AzureCliAuthentication() -# Get workspace -ws = Workspace.from_config(auth=cli_auth) -# Get the ACI Details -try: - with open("aml_config/aci_webservice.json") as f: - config = json.load(f) -except: - print("No new model, thus no deployment on ACI") - # raise Exception('No new model to register as production model perform better') - sys.exit(0) - -service_name = config["aci_name"] -# Get the hosted web service -service = Webservice(name=service_name, workspace=ws) - -# Input for Model with all features -input_j = [[1, 2, 3, 4, 5, 6, 7, 8, 9, 10], [10, 9, 8, 7, 6, 5, 4, 3, 2, 1]] -print(input_j) -test_sample = json.dumps({"data": input_j}) -test_sample = bytes(test_sample, encoding="utf8") -try: - prediction = service.run(input_data=test_sample) - print(prediction) -except Exception as e: - result = str(e) - print(result) - raise Exception("ACI service is not working as expected") diff --git a/aml_service/archived/61-AksWebserviceTest.py b/aml_service/archived/61-AksWebserviceTest.py deleted file mode 100644 index f22982e0..00000000 --- a/aml_service/archived/61-AksWebserviceTest.py +++ /dev/null @@ -1,66 +0,0 @@ -""" -Copyright (C) Microsoft Corporation. All rights reserved.​ - ​ -Microsoft Corporation (“Microsoft”) grants you a nonexclusive, perpetual, -royalty-free right to use, copy, and modify the software code provided by us -("Software Code"). You may not sublicense the Software Code or any use of it -(except to your affiliates and to vendors to perform work on your behalf) -through distribution, network access, service agreement, lease, rental, or -otherwise. This license does not purport to express any claim of ownership over -data you may have shared with Microsoft in the creation of the Software Code. -Unless applicable law gives you more rights, Microsoft reserves all other -rights not expressly granted herein, whether by implication, estoppel or -otherwise. ​ - ​ -THE SOFTWARE CODE IS PROVIDED “AS IS”, WITHOUT WARRANTY OF ANY KIND, EXPRESS -OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, -FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL -MICROSOFT OR ITS LICENSORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, -SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, -PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR -BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER -IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -ARISING IN ANY WAY OUT OF THE USE OF THE SOFTWARE CODE, EVEN IF ADVISED OF THE -POSSIBILITY OF SUCH DAMAGE. -""" -import numpy -import os, json, datetime, sys -from operator import attrgetter -from azureml.core import Workspace -from azureml.core.model import Model -from azureml.core.image import Image -from azureml.core.webservice import Webservice -from azureml.core.authentication import AzureCliAuthentication - -cli_auth = AzureCliAuthentication() -# Get workspace -ws = Workspace.from_config(auth=cli_auth) - -# Get the AKS Details -try: - with open("aml_config/aks_webservice.json") as f: - config = json.load(f) -except: - print("No new model, thus no deployment on ACI") - # raise Exception('No new model to register as production model perform better') - sys.exit(0) - -service_name = config["aks_service_name"] -# Get the hosted web service -service = Webservice(workspace=ws, name=service_name) - -# Input for Model with all features -input_j = [[1, 2, 3, 4, 5, 6, 7, 8, 9, 10], [10, 9, 8, 7, 6, 5, 4, 3, 2, 1]] -print(input_j) -test_sample = json.dumps({"data": input_j}) -test_sample = bytes(test_sample, encoding="utf8") -try: - prediction = service.run(input_data=test_sample) - print(prediction) -except Exception as e: - result = str(e) - print(result) - raise Exception("AKS service is not working as expected") - -# Delete aci after test -service.delete() diff --git a/aml_service/archived/helper/azcli.py b/aml_service/archived/helper/azcli.py deleted file mode 100644 index 4affc1b3..00000000 --- a/aml_service/archived/helper/azcli.py +++ /dev/null @@ -1,73 +0,0 @@ -""" -Copyright (C) Microsoft Corporation. All rights reserved.​ - ​ -Microsoft Corporation (“Microsoft”) grants you a nonexclusive, perpetual, -royalty-free right to use, copy, and modify the software code provided by us -("Software Code"). You may not sublicense the Software Code or any use of it -(except to your affiliates and to vendors to perform work on your behalf) -through distribution, network access, service agreement, lease, rental, or -otherwise. This license does not purport to express any claim of ownership over -data you may have shared with Microsoft in the creation of the Software Code. -Unless applicable law gives you more rights, Microsoft reserves all other -rights not expressly granted herein, whether by implication, estoppel or -otherwise. ​ - ​ -THE SOFTWARE CODE IS PROVIDED “AS IS”, WITHOUT WARRANTY OF ANY KIND, EXPRESS -OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, -FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL -MICROSOFT OR ITS LICENSORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, -SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, -PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR -BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER -IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -ARISING IN ANY WAY OUT OF THE USE OF THE SOFTWARE CODE, EVEN IF ADVISED OF THE -POSSIBILITY OF SUCH DAMAGE. -""" -import subprocess - - -def az_login(sp_user: str, sp_password: str, sp_tenant_id: str): - """ - Uses the provided service principal credentials to log into the azure cli. - This should always be the first step in executing az cli commands. - """ - cmd = "az login --service-principal --username {} --password {} --tenant {}" - out, err = run_cmd(cmd.format(sp_user, sp_password, sp_tenant_id)) - return out, err - - -def run_cmd(cmd: str): - """ - Runs an arbitrary command line command. Works for Linux or Windows. - Returns a tuple of output and error. - """ - proc = subprocess.Popen( - cmd, shell=True, stdout=subprocess.PIPE, universal_newlines=True - ) - output, error = proc.communicate() - if proc.returncode != 0: - print("Following command execution failed: {}".format(cmd)) - raise Exception("Operation Failed. Look at console logs for error info") - return output, error - - -def az_account_set(subscription_id: str): - """ - Sets the correct azure subscription. - This should always be run after the az_login. - """ - cmd = "az account set -s {}" - out, err = run_cmd(cmd.format(subscription_id)) - return out, err - - -def az_acr_create(resource_group: str, acr_name: str): - cmd = "az acr create --resource-group {} --name {} --sku Basic" - out, err = run_cmd(cmd.format(resource_group, acr_name)) - return out, err - - -def az_acr_login(acr_name: str): - cmd = "az acr login --name {}" - out, err = run_cmd(cmd.format(acr_name)) - return out, err diff --git a/azdo_pipelines/base-pipeline.yml b/azdo_pipelines/base-pipeline.yml index 38c9f656..ea16ae13 100644 --- a/azdo_pipelines/base-pipeline.yml +++ b/azdo_pipelines/base-pipeline.yml @@ -1,20 +1,19 @@ +# this pipeline should be ignored for now parameters: pipelineType: 'training' steps: - script: | - ls $BUILD_SOURCESDIRECTORY flake8 --output-file=$(Build.BinariesDirectory)/flake8_amlservice_testresults.xml aml_service - cat $(Build.BinariesDirectory)/flake8_amlservice_testresults.xml - #flake8 --output-file=$(Build.BinariesDirectory)/flake8_tests_testresults.xml tests + flake8 --output-file=$(Build.BinariesDirectory)/flake8_tests_testresults.xml tests workingDirectory: '$(Build.SourcesDirectory)' displayName: 'Run code quality tests' enabled: 'true' -#- script: | -# pytest --junitxml=$(Build.BinariesDirectory)/unittest-results.xml $(Build.SourcesDirectory)/Code/tests/unit/${{parameters.pipelineType}} -# displayName: 'Run unit tests' -# enabled: 'true' +- script: | + pytest --junitxml=$(Build.BinariesDirectory)/unittest-results.xml $(Build.SourcesDirectory)/Code/tests/unit/${{parameters.pipelineType}} + displayName: 'Run unit tests' + enabled: 'true' - task: PublishTestResults@2 condition: succeededOrFailed() diff --git a/azdo_pipelines/build-train.yml b/azdo_pipelines/build-train.yml index d655c915..cb04dcd7 100644 --- a/azdo_pipelines/build-train.yml +++ b/azdo_pipelines/build-train.yml @@ -16,9 +16,7 @@ variables: - group: devopsforai-aml-vg -steps: -- template: base-pipeline.yml - +steps: - bash: | # Invoke the Python training pipeline python3 $(Build.SourcesDirectory)/aml_pipelines/model_train_pipeline.py From 5333249504242e5241aafa613c7b5ebb4b66482d Mon Sep 17 00:00:00 2001 From: Eugene Fedorenko Date: Tue, 6 Aug 2019 11:28:08 -0700 Subject: [PATCH 044/113] cleaning --- aml_pipelines/garbage.py | 122 --------------------------------------- 1 file changed, 122 deletions(-) delete mode 100644 aml_pipelines/garbage.py diff --git a/aml_pipelines/garbage.py b/aml_pipelines/garbage.py deleted file mode 100644 index 49e2d188..00000000 --- a/aml_pipelines/garbage.py +++ /dev/null @@ -1,122 +0,0 @@ - -from azureml.core.authentication import AzureCliAuthentication -from azureml.core.compute import ComputeTarget -from azureml.pipeline.core.graph import PipelineParameter -from azureml.pipeline.core import PublishedPipeline -from azureml.pipeline.steps import PythonScriptStep -from azureml.pipeline.core import Pipeline, PipelineData, StepSequence -from azureml.data.data_reference import DataReference -from azureml.core.runconfig import RunConfiguration, CondaDependencies -from azureml.core import Workspace, Experiment, Datastore -import argparse -import datetime -import requests -import json -import os -import sys -sys.path.append(os.path.abspath("./aml_service")) # NOQA: E402 -from workspace import get_workspace -from attach_compute import get_compute - - -def main(): - load_dotenv() - workspace_name = os.environ.get("AML_WORKSPACE_NAME") - resource_group = os.environ.get("RESOURCE_GROUP") - subscription_id = os.environ.get("SUBSCRIPTION_ID") - tenant_id = os.environ.get("TENANT_ID") - app_id = os.environ.get("SP_APP_ID") - app_secret = os.environ.get("SP_APP_SECRET") - sources_directory_train = os.environ.get("SOURCES_DIR_Train") - vm_size_cpu = os.environ.get("AML_COMPUTE_CLUSTER_CPU_SKU") - compute_name_cpu = os.environ.get("AML_COMPUTE_CLUSTER_NAME") - experiment_name = os.environ.get("EXPERIMENT_NAME") - - # Get Azure machine learning workspace - aml_workspace = get_workspace( - workspace_name, - resource_group, - subscription_id, - tenant_id, - app_id, - app_secret) - print(aml_workspace) - - # Get Azure machine learning cluster - aml_compute_cpu = get_compute( - aml_workspace, - compute_name_cpu, - vm_size_cpu) - if aml_compute_cpu is not None: - print(aml_compute_cpu) - - # working - - # run_config = RunConfiguration(conda_dependencies=CondaDependencies.create( - # conda_packages=['numpy', 'pandas', - # 'scikit-learn', 'tensorflow', 'keras'], - # pip_packages=['azure', 'azureml-core', - # 'azure-storage', - # 'azure-storage-blob']) - # ) - # #run_config.environment.docker.enabled = True - - # Create python script step to run the training/scoring main script - - """ train_step = PythonScriptStep( - name="Train Model", - script_name="training/train.py", - compute_target=aml_compute, - source_directory=source_directory, - arguments=[ - "--config_suffix", config_suffix, - "--json_config", jsonconfigs, - "--model_name", model_name, - ], - runconfig=run_config, - # inputs=[jsonconfigs], - outputs=[jsonconfigs], - allow_reuse=False, - ) - print("Step Train created") - - evaluate_step = PythonScriptStep( - name="Evaluate Model ", - script_name="evaluate/evaluate_model.py", - compute_target=aml_compute, - source_directory=source_directory, - arguments=[ - "--config_suffix", config_suffix, - "--json_config", jsonconfigs, - ], - runconfig=run_config, - inputs=[jsonconfigs], - # outputs=[jsonconfigs], - allow_reuse=False, - ) - print("Step Evaluate created") - - register_model_step = PythonScriptStep( - name="Register New Trained Model", - script_name="register/register_model.py", - compute_target=aml_compute, - source_directory=source_directory, - arguments=[ - "--config_suffix", config_suffix, - "--json_config", jsonconfigs, - "--model_name", model_name, - ], - runconfig=run_config, - inputs=[jsonconfigs], - # outputs=[jsonconfigs], - allow_reuse=False, - ) - print("Step register model created") - - evaluate_step.run_after(train_step) - register_model_step.run_after(evaluate_step) - steps = [register_model_step] - - train_pipeline = Pipeline(workspace=aml_workspace, steps=steps) - train_pipeline.validate() - pipeline_run = train_pipeline.submit(experiment_name=experiment_name) """ From 4bf1bc6f9b38e60d67536d428aa54ba224c5599d Mon Sep 17 00:00:00 2001 From: Eugene Fedorenko Date: Tue, 6 Aug 2019 11:37:45 -0700 Subject: [PATCH 045/113] old pipeline doesn't use container --- azure-pipelines.yml | 4 ---- 1 file changed, 4 deletions(-) diff --git a/azure-pipelines.yml b/azure-pipelines.yml index b1ae0a5d..7514c9d5 100644 --- a/azure-pipelines.yml +++ b/azure-pipelines.yml @@ -1,10 +1,6 @@ pool: vmImage: 'Ubuntu 16.04' -container: - image: mlopscr.azurecr.io/public/mlops/mlopspython:latest - endpoint: acrconnection - variables: - group: AzureKeyVaultSecrets From e12735e2cebf63ddaccab3279bfb598424cea467 Mon Sep 17 00:00:00 2001 From: Eugene Fedorenko Date: Tue, 6 Aug 2019 11:42:08 -0700 Subject: [PATCH 046/113] Dummy code in old pipeline --- azure-pipelines.yml | 40 +++------------------------------------- 1 file changed, 3 insertions(+), 37 deletions(-) diff --git a/azure-pipelines.yml b/azure-pipelines.yml index 7514c9d5..c3714cfd 100644 --- a/azure-pipelines.yml +++ b/azure-pipelines.yml @@ -1,3 +1,4 @@ +# keeping this pipeline for now to get Microsoft.MLOpsPython working on https://dev.azure.com/customai/DevopsForAI-AML pool: vmImage: 'Ubuntu 16.04' @@ -11,42 +12,7 @@ trigger: steps: - script: | - az login --service-principal -u $(spidentity) -p $(spsecret) --tenant $(sptenant) + echo 'dummy step' - displayName: 'Login to Azure' - -- script: | - sed -i 's#"subscription_id": "<>"#"subscription_id": "$(subscriptionid)"#g' aml_config/config.json - - displayName: 'replace subscription value' - -- script: 'pytest tests/unit/data_test.py' - displayName: 'Data Quality Check' - -- script: 'python aml_service/00-WorkSpace.py' - displayName: 'Get or Create Workspace' - -- script: 'python aml_service/03-AttachAmlCluster.py' - displayName: 'Create AML Compute Cluster' - -- script: 'python aml_service/04-AmlPipelines.py' - displayName: 'Create and Test AML Pipeline' - -- script: 'python aml_service/04-AmlPipelines.py --pipeline_action publish' - displayName: 'Publish AML Pipeline as Endpoint' - -- task: CopyFiles@2 - displayName: 'Copy Files to: $(Build.ArtifactStagingDirectory)' - inputs: - SourceFolder: '$(Build.SourcesDirectory)' - TargetFolder: '$(Build.ArtifactStagingDirectory)' - Contents: '**' - -- task: PublishBuildArtifacts@1 - displayName: 'Publish Artifact: devops-for-ai' - inputs: - ArtifactName: 'devops-for-ai' - publishLocation: 'container' - pathtoPublish: '$(Build.ArtifactStagingDirectory)' - TargetPath: '$(Build.ArtifactStagingDirectory)' + displayName: 'Dummy step' From 7d26eadcf8a00bd427656bad078d1a57454cfa39 Mon Sep 17 00:00:00 2001 From: Taylor Rockey Date: Tue, 6 Aug 2019 14:13:14 -0700 Subject: [PATCH 047/113] removed config. --- .gitignore | 2 ++ aml_config/config.json | 1 - 2 files changed, 2 insertions(+), 1 deletion(-) delete mode 100644 aml_config/config.json diff --git a/.gitignore b/.gitignore index bc6e89d1..82e6a89a 100644 --- a/.gitignore +++ b/.gitignore @@ -103,3 +103,5 @@ venv.bak/ # mypy .mypy_cache/ + +aml_config/config.json \ No newline at end of file diff --git a/aml_config/config.json b/aml_config/config.json deleted file mode 100644 index eb5d0991..00000000 --- a/aml_config/config.json +++ /dev/null @@ -1 +0,0 @@ -{"Id": null, "Scope": "/subscriptions/4e3d57a1-3ed9-45f6-b033-e2bc8285fed3/resourceGroups/mlopstesting/providers/Microsoft.MachineLearningServices/workspaces/trmlops"} \ No newline at end of file From c75b8fe7a19c140c7211a33aeeb582de97e131f9 Mon Sep 17 00:00:00 2001 From: Eugene Fedorenko Date: Wed, 7 Aug 2019 13:52:00 -0700 Subject: [PATCH 048/113] Enable and fix linting (#44) --- aml_pipelines/model_train_pipeline.py | 31 +++++++++++---------------- azdo_pipelines/base-pipeline.yml | 9 ++++---- azdo_pipelines/build-train.yml | 19 +++++++++++++++- code/evaluate/evaluate_model.py | 27 +++++++++++------------ code/register/register_model.py | 13 ++++++----- code/scoring/create_scoring_image.py | 12 +++++------ code/scoring/score.py | 5 ++--- code/training/train.py | 19 ++++++---------- tests/unit/data_test.py | 9 +++++--- 9 files changed, 75 insertions(+), 69 deletions(-) diff --git a/aml_pipelines/model_train_pipeline.py b/aml_pipelines/model_train_pipeline.py index 9280c9cb..0d519bf7 100644 --- a/aml_pipelines/model_train_pipeline.py +++ b/aml_pipelines/model_train_pipeline.py @@ -1,16 +1,9 @@ -from azureml.core.authentication import AzureCliAuthentication -from azureml.core.compute import ComputeTarget from azureml.pipeline.core.graph import PipelineParameter -from azureml.pipeline.core import PublishedPipeline from azureml.pipeline.steps import PythonScriptStep -from azureml.pipeline.core import Pipeline, PipelineData, StepSequence -from azureml.data.data_reference import DataReference +from azureml.pipeline.core import Pipeline, PipelineData from azureml.core.runconfig import RunConfiguration, CondaDependencies -from azureml.core import Workspace, Experiment, Datastore -import argparse +from azureml.core import Datastore import datetime -import requests -import json import os import sys from dotenv import load_dotenv @@ -18,7 +11,8 @@ from workspace import get_workspace from attach_compute import get_compute -def main(): + +def main(): load_dotenv() workspace_name = os.environ.get("AML_WORKSPACE_NAME") resource_group = os.environ.get("RESOURCE_GROUP") @@ -29,7 +23,7 @@ def main(): sources_directory_train = os.environ.get("SOURCES_DIR_TRAIN") train_script_path = os.environ.get("TRAIN_SCRIPT_PATH") evaluate_script_path = os.environ.get("EVALUATE_SCRIPT_PATH") - register_script_path = os.environ.get("REGISTER_SCRIPT_PATH") + register_script_path = os.environ.get("REGISTER_SCRIPT_PATH") vm_size_cpu = os.environ.get("AML_COMPUTE_CLUSTER_CPU_SKU") compute_name_cpu = os.environ.get("AML_COMPUTE_CLUSTER_NAME") experiment_name = os.environ.get("EXPERIMENT_NAME") @@ -42,7 +36,7 @@ def main(): tenant_id, app_id, app_secret) - print(aml_workspace) + print(aml_workspace) # Get Azure machine learning cluster aml_compute_cpu = get_compute( @@ -61,7 +55,8 @@ def main(): ) run_config.environment.docker.enabled = True - model_name = PipelineParameter(name="model_name", default_value="sklearn_regression_model.pkl") + model_name = PipelineParameter( + name="model_name", default_value="sklearn_regression_model.pkl") def_blob_store = Datastore(aml_workspace, "workspaceblobstore") jsonconfigs = PipelineData("jsonconfigs", datastore=def_blob_store) config_suffix = datetime.datetime.now().strftime("%Y%m%d%H") @@ -89,15 +84,15 @@ def main(): compute_target=aml_compute_cpu, source_directory=sources_directory_train, arguments=[ - "--config_suffix", config_suffix, - "--json_config", jsonconfigs, + "--config_suffix", config_suffix, + "--json_config", jsonconfigs, ], runconfig=run_config, inputs=[jsonconfigs], # outputs=[jsonconfigs], allow_reuse=False, ) - print("Step Evaluate created") + print("Step Evaluate created") register_model_step = PythonScriptStep( name="Register New Trained Model", @@ -122,8 +117,8 @@ def main(): train_pipeline = Pipeline(workspace=aml_workspace, steps=steps) train_pipeline.validate() - pipeline_run = train_pipeline.submit(experiment_name=experiment_name) + train_pipeline.submit(experiment_name=experiment_name) if __name__ == '__main__': - main() \ No newline at end of file + main() diff --git a/azdo_pipelines/base-pipeline.yml b/azdo_pipelines/base-pipeline.yml index ea16ae13..3dc0a2df 100644 --- a/azdo_pipelines/base-pipeline.yml +++ b/azdo_pipelines/base-pipeline.yml @@ -5,15 +5,14 @@ parameters: steps: - script: | flake8 --output-file=$(Build.BinariesDirectory)/flake8_amlservice_testresults.xml aml_service - flake8 --output-file=$(Build.BinariesDirectory)/flake8_tests_testresults.xml tests workingDirectory: '$(Build.SourcesDirectory)' displayName: 'Run code quality tests' enabled: 'true' -- script: | - pytest --junitxml=$(Build.BinariesDirectory)/unittest-results.xml $(Build.SourcesDirectory)/Code/tests/unit/${{parameters.pipelineType}} - displayName: 'Run unit tests' - enabled: 'true' +# - script: | +# pytest --junitxml=$(Build.BinariesDirectory)/unittest-results.xml $(Build.SourcesDirectory)/Code/tests/unit/${{parameters.pipelineType}} +# displayName: 'Run unit tests' +# enabled: 'true' - task: PublishTestResults@2 condition: succeededOrFailed() diff --git a/azdo_pipelines/build-train.yml b/azdo_pipelines/build-train.yml index cb04dcd7..907e4763 100644 --- a/azdo_pipelines/build-train.yml +++ b/azdo_pipelines/build-train.yml @@ -16,7 +16,24 @@ variables: - group: devopsforai-aml-vg -steps: +steps: +- script: | + flake8 --output-file=$(Build.BinariesDirectory)/flake8_testresults.xml --format junit-xml + workingDirectory: '$(Build.SourcesDirectory)' + displayName: 'Run code quality tests' + enabled: 'true' + +- task: PublishTestResults@2 + condition: succeededOrFailed() + inputs: + testResultsFiles: '$(Build.BinariesDirectory)/*_testresults.xml' + testRunTitle: 'Linitnig' + failTaskOnFailedTests: true + displayName: 'Publish linting results' + enabled: 'true' + + + - bash: | # Invoke the Python training pipeline python3 $(Build.SourcesDirectory)/aml_pipelines/model_train_pipeline.py diff --git a/code/evaluate/evaluate_model.py b/code/evaluate/evaluate_model.py index d3ba5af0..02e048b6 100644 --- a/code/evaluate/evaluate_model.py +++ b/code/evaluate/evaluate_model.py @@ -23,11 +23,9 @@ ARISING IN ANY WAY OUT OF THE USE OF THE SOFTWARE CODE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. """ -import os, json -from azureml.core import Workspace -from azureml.core import Experiment +import os +import json from azureml.core.model import Model -import azureml.core from azureml.core import Run import argparse @@ -68,10 +66,6 @@ with open(train_output_path) as f: config = json.load(f) -# parser = argparse.ArgumentParser() -# parser.add_argument('--train_run_id',type=str,default='',help='Run id of the newly trained model') -# #parser.add_argument('--model_assets_path',type=str,default='outputs',help='Location of trained model.') - new_model_run_id = config["run_id"] # args.train_run_id experiment_name = config["experiment_name"] @@ -79,19 +73,23 @@ try: - # Get most recently registered model, we assume that is the model in production. Download this model and compare it with the recently trained model by running test with same data set. + # Get most recently registered model, we assume that + # is the model in production. + # Download this model and compare it with the recently + # trained model by running test with same data set. model_list = Model.list(ws) production_model = next( filter( - lambda x: x.created_time == max(model.created_time for model in model_list), + lambda x: x.created_time == max( + model.created_time for model in model_list), model_list, ) ) production_model_run_id = production_model.tags.get("run_id") run_list = exp.get_runs() - # production_model_run = next(filter(lambda x: x.id == production_model_run_id, run_list)) - # Get the run history for both production model and newly trained model and compare mse + # Get the run history for both production model and + # newly trained model and compare mse production_model_run = Run(exp, run_id=production_model_run_id) new_model_run = Run(exp, run_id=new_model_run_id) @@ -107,9 +105,10 @@ if new_model_mse < production_model_mse: promote_new_model = True print("New trained model performs better, thus it will be registered") -except: +except Exception: promote_new_model = True - print("This is the first model to be trained, thus nothing to evaluate for now") + print("This is the first model to be trained, \ + thus nothing to evaluate for now") run_id = {} run_id["run_id"] = "" diff --git a/code/register/register_model.py b/code/register/register_model.py index 7308ac73..6a032682 100644 --- a/code/register/register_model.py +++ b/code/register/register_model.py @@ -23,14 +23,13 @@ ARISING IN ANY WAY OUT OF THE USE OF THE SOFTWARE CODE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. """ -import os, json, sys -from azureml.core import Workspace +import os +import json +import sys from azureml.core import Run -from azureml.core import Experiment from azureml.core.model import Model import argparse -from azureml.core.runconfig import RunConfiguration from azureml.core.authentication import AzureCliAuthentication cli_auth = AzureCliAuthentication() @@ -78,10 +77,10 @@ with open(evaluate_output_path) as f: config = json.load(f) if not config["run_id"]: - raise Exception("No new model to register as production model perform better") -except: + raise Exception( + "No new model to register as production model perform better") +except Exception: print("No new model to register as production model perform better") - # raise Exception('No new model to register as production model perform better') sys.exit(0) run_id = config["run_id"] diff --git a/code/scoring/create_scoring_image.py b/code/scoring/create_scoring_image.py index f50650c1..176a2913 100644 --- a/code/scoring/create_scoring_image.py +++ b/code/scoring/create_scoring_image.py @@ -23,7 +23,9 @@ ARISING IN ANY WAY OUT OF THE USE OF THE SOFTWARE CODE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. """ -import os, json, sys +import os +import json +import sys import argparse from azureml.core import Workspace from azureml.core.image import ContainerImage, Image @@ -65,16 +67,16 @@ try: with open(register_output_path) as f: config = json.load(f) -except: +except Exception: print("No new model to register thus no need to create new scoring image") - # raise Exception('No new model to register as production model perform better') sys.exit(0) model_name = config["model_name"] model_version = config["model_version"] model_list = Model.list(workspace=ws) -model, = (m for m in model_list if m.version == model_version and m.name == model_name) +model, = (m for m in model_list if m.version == + model_version and m.name == model_name) print( "Model picked: {} \nModel Description: {} \nModel Version: {}".format( model.name, model.description, model.version @@ -123,5 +125,3 @@ output_path = os.path.join(args.json_config, filename) with open(output_path, "w") as outfile: json.dump(image_json, outfile) - -# How to fix the schema for a model, like if we have multiple models expecting different schema, diff --git a/code/scoring/score.py b/code/scoring/score.py index 994ca24a..3208d9d0 100644 --- a/code/scoring/score.py +++ b/code/scoring/score.py @@ -23,10 +23,8 @@ ARISING IN ANY WAY OUT OF THE USE OF THE SOFTWARE CODE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. """ -import pickle import json import numpy -from sklearn.ensemble import RandomForestClassifier from azureml.core.model import Model @@ -35,7 +33,8 @@ def init(): from sklearn.externals import joblib # load the model from file into a global object - model_path = Model.get_model_path(model_name="sklearn_regression_model.pkl") + model_path = Model.get_model_path( + model_name="sklearn_regression_model.pkl") model = joblib.load(model_path) diff --git a/code/training/train.py b/code/training/train.py index d94e0855..2b541615 100644 --- a/code/training/train.py +++ b/code/training/train.py @@ -23,8 +23,6 @@ ARISING IN ANY WAY OUT OF THE USE OF THE SOFTWARE CODE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. """ -import pickle -from azureml.core import Workspace from azureml.core.run import Run import os import argparse @@ -35,8 +33,6 @@ from sklearn.externals import joblib import numpy as np import json -import subprocess -from typing import Tuple, List parser = argparse.ArgumentParser("train") @@ -72,8 +68,10 @@ X, y = load_diabetes(return_X_y=True) columns = ["age", "gender", "bmi", "bp", "s1", "s2", "s3", "s4", "s5", "s6"] -X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=0) -data = {"train": {"X": X_train, "y": y_train}, "test": {"X": X_test, "y": y_test}} +X_train, X_test, y_train, y_test = train_test_split( + X, y, test_size=0.2, random_state=0) +data = {"train": {"X": X_train, "y": y_train}, + "test": {"X": X_test, "y": y_test}} print("Running train.py") @@ -97,16 +95,13 @@ # upload the model file explicitly into artifacts run.upload_file(name="./outputs/" + model_name, path_or_stream=model_name) -print("Uploaded the model {} to experiment {}".format(model_name, run.experiment.name)) +print("Uploaded the model {} to experiment {}".format( + model_name, run.experiment.name)) dirpath = os.getcwd() print(dirpath) print("Following files are uploaded ") print(run.get_file_names()) -# register the model -# run.log_model(file_name = model_name) -# print('Registered the model {} to run history {}'.format(model_name, run.history.name)) - run_id = {} run_id["run_id"] = run.id run_id["experiment_name"] = run.experiment.name @@ -115,4 +110,4 @@ with open(output_path, "w") as outfile: json.dump(run_id, outfile) -run.complete() \ No newline at end of file +run.complete() diff --git a/tests/unit/data_test.py b/tests/unit/data_test.py index ad5c28ba..8b40b8bc 100644 --- a/tests/unit/data_test.py +++ b/tests/unit/data_test.py @@ -34,7 +34,8 @@ def get_absPath(filename): """Returns the path of the notebooks folder""" path = os.path.abspath( os.path.join( - os.path.dirname(__file__), os.path.pardir, os.path.pardir, "data", filename + os.path.dirname( + __file__), os.path.pardir, os.path.pardir, "data", filename ) ) return path @@ -119,6 +120,8 @@ def test_check_distribution(): mean = np.mean(dataset.values, axis=0) std = np.mean(dataset.values, axis=0) assert ( - np.sum(abs(mean - historical_mean) > shift_tolerance * abs(historical_mean)) - or np.sum(abs(std - historical_std) > shift_tolerance * abs(historical_std)) > 0 + np.sum(abs(mean - historical_mean) > + shift_tolerance * abs(historical_mean)) + or np.sum(abs(std - historical_std) > + shift_tolerance * abs(historical_std)) > 0 ) From 80e063e383abe34c15d8c5123a59b66889cff705 Mon Sep 17 00:00:00 2001 From: Eugene Fedorenko Date: Wed, 7 Aug 2019 16:53:48 -0700 Subject: [PATCH 049/113] Add & enable unit tests (#45) --- azdo_pipelines/build-train.yml | 14 ++++++++++++++ code/register/register_model.py | 1 - code/scoring/create_scoring_image.py | 3 --- environment_setup/requirements.txt | 11 +++-------- tests/unit/code_test.py | 25 +++++++++++++++++++++++++ 5 files changed, 42 insertions(+), 12 deletions(-) create mode 100644 tests/unit/code_test.py diff --git a/azdo_pipelines/build-train.yml b/azdo_pipelines/build-train.yml index 907e4763..536c06f8 100644 --- a/azdo_pipelines/build-train.yml +++ b/azdo_pipelines/build-train.yml @@ -32,7 +32,21 @@ steps: displayName: 'Publish linting results' enabled: 'true' +- script: | + pytest --junitxml=$(Build.BinariesDirectory)/unittest-results.xml $(Build.SourcesDirectory)/tests/unit + displayName: 'Run unit tests' + enabled: 'true' + env: + SP_APP_SECRET: '$(SP_APP_SECRET)' +- task: PublishTestResults@2 + condition: succeededOrFailed() + inputs: + testResultsFiles: '$(Build.BinariesDirectory)/unittest-results.xml' + testRunTitle: 'Unit tests' + failTaskOnFailedTests: true + displayName: 'Publish unit test results' + enabled: 'true' - bash: | # Invoke the Python training pipeline diff --git a/code/register/register_model.py b/code/register/register_model.py index 6a032682..05f469b7 100644 --- a/code/register/register_model.py +++ b/code/register/register_model.py @@ -38,7 +38,6 @@ # ws = Workspace.from_config(auth=cli_auth, path='./') - run = Run.get_context() exp = run.experiment ws = run.experiment.workspace diff --git a/code/scoring/create_scoring_image.py b/code/scoring/create_scoring_image.py index 176a2913..d30d400d 100644 --- a/code/scoring/create_scoring_image.py +++ b/code/scoring/create_scoring_image.py @@ -40,9 +40,6 @@ print("offline run") # Get workspace ws = Workspace.from_config(auth=cli_auth, path='./') - - - else: exp = run.experiment ws = run.experiment.workspace diff --git a/environment_setup/requirements.txt b/environment_setup/requirements.txt index 42ebc217..1a3c1785 100644 --- a/environment_setup/requirements.txt +++ b/environment_setup/requirements.txt @@ -1,12 +1,7 @@ -scipy==1.0.0 -scikit-learn==0.19.1 -numpy==1.14.5 -pandas==0.23.1 pytest==4.3.0 -python-dotenv==0.10.3 -azure-cli -requests>=2.22 #.0 -azureml-sdk>=1.0#.45 +requests>=2.22 +azureml>=0.2 +azureml-sdk>=1.0 python-dotenv>=0.10.3 flake8 flake8_formatter_junit_xml \ No newline at end of file diff --git a/tests/unit/code_test.py b/tests/unit/code_test.py new file mode 100644 index 00000000..b5421c27 --- /dev/null +++ b/tests/unit/code_test.py @@ -0,0 +1,25 @@ +import sys +import os +sys.path.append(os.path.abspath("./aml_service")) # NOQA: E402 +from workspace import get_workspace + + +# Just an example of a unit test against +# a utility function common_scoring.next_saturday +def test_get_workspace(): + workspace_name = os.environ.get("AML_WORKSPACE_NAME") + resource_group = os.environ.get("RESOURCE_GROUP") + subscription_id = os.environ.get("SUBSCRIPTION_ID") + tenant_id = os.environ.get("TENANT_ID") + app_id = os.environ.get("SP_APP_ID") + app_secret = os.environ.get("SP_APP_SECRET") + + aml_workspace = get_workspace( + workspace_name, + resource_group, + subscription_id, + tenant_id, + app_id, + app_secret) + + assert aml_workspace.name == workspace_name From b0d53b70f063f5a0785fca1b83f5a5c8cbfba2cc Mon Sep 17 00:00:00 2001 From: Eugene Fedorenko Date: Thu, 8 Aug 2019 11:57:27 -0700 Subject: [PATCH 050/113] Use base pipeline template (#46) --- azdo_pipelines/base-pipeline.yml | 20 +++++++++++--------- azdo_pipelines/build-train.yml | 31 +------------------------------ 2 files changed, 12 insertions(+), 39 deletions(-) diff --git a/azdo_pipelines/base-pipeline.yml b/azdo_pipelines/base-pipeline.yml index 3dc0a2df..926b404f 100644 --- a/azdo_pipelines/base-pipeline.yml +++ b/azdo_pipelines/base-pipeline.yml @@ -4,21 +4,23 @@ parameters: steps: - script: | - flake8 --output-file=$(Build.BinariesDirectory)/flake8_amlservice_testresults.xml aml_service + flake8 --output-file=$(Build.BinariesDirectory)/lint-testresults.xml --format junit-xml workingDirectory: '$(Build.SourcesDirectory)' displayName: 'Run code quality tests' enabled: 'true' - -# - script: | -# pytest --junitxml=$(Build.BinariesDirectory)/unittest-results.xml $(Build.SourcesDirectory)/Code/tests/unit/${{parameters.pipelineType}} -# displayName: 'Run unit tests' -# enabled: 'true' + +- script: | + pytest --junitxml=$(Build.BinariesDirectory)/unit-testresults.xml $(Build.SourcesDirectory)/tests/unit + displayName: 'Run unit tests' + enabled: 'true' + env: + SP_APP_SECRET: '$(SP_APP_SECRET)' - task: PublishTestResults@2 condition: succeededOrFailed() inputs: - testResultsFiles: '$(Build.BinariesDirectory)/*_testresults.xml' - testRunTitle: 'Unit tests' + testResultsFiles: '$(Build.BinariesDirectory)/*-testresults.xml' + testRunTitle: 'Linting & Unit tests' failTaskOnFailedTests: true - displayName: 'Publish unit test results' + displayName: 'Publish linting and unit test results' enabled: 'true' diff --git a/azdo_pipelines/build-train.yml b/azdo_pipelines/build-train.yml index 536c06f8..d655c915 100644 --- a/azdo_pipelines/build-train.yml +++ b/azdo_pipelines/build-train.yml @@ -17,36 +17,7 @@ variables: steps: -- script: | - flake8 --output-file=$(Build.BinariesDirectory)/flake8_testresults.xml --format junit-xml - workingDirectory: '$(Build.SourcesDirectory)' - displayName: 'Run code quality tests' - enabled: 'true' - -- task: PublishTestResults@2 - condition: succeededOrFailed() - inputs: - testResultsFiles: '$(Build.BinariesDirectory)/*_testresults.xml' - testRunTitle: 'Linitnig' - failTaskOnFailedTests: true - displayName: 'Publish linting results' - enabled: 'true' - -- script: | - pytest --junitxml=$(Build.BinariesDirectory)/unittest-results.xml $(Build.SourcesDirectory)/tests/unit - displayName: 'Run unit tests' - enabled: 'true' - env: - SP_APP_SECRET: '$(SP_APP_SECRET)' - -- task: PublishTestResults@2 - condition: succeededOrFailed() - inputs: - testResultsFiles: '$(Build.BinariesDirectory)/unittest-results.xml' - testRunTitle: 'Unit tests' - failTaskOnFailedTests: true - displayName: 'Publish unit test results' - enabled: 'true' +- template: base-pipeline.yml - bash: | # Invoke the Python training pipeline From 01bd3064fb360b2583d058b6da8ed8b557a15127 Mon Sep 17 00:00:00 2001 From: Eugene Fedorenko Date: Thu, 8 Aug 2019 15:34:46 -0700 Subject: [PATCH 051/113] publishoing artifacts --- aml_pipelines/model_train_pipeline.py | 8 +++++++- aml_service/run_train_pipeline.py | 27 +++++++++++++++++++++++++++ azdo_pipelines/build-train.yml | 19 +++++++++++++++++-- 3 files changed, 51 insertions(+), 3 deletions(-) create mode 100644 aml_service/run_train_pipeline.py diff --git a/aml_pipelines/model_train_pipeline.py b/aml_pipelines/model_train_pipeline.py index 0d519bf7..947dfc3b 100644 --- a/aml_pipelines/model_train_pipeline.py +++ b/aml_pipelines/model_train_pipeline.py @@ -27,6 +27,7 @@ def main(): vm_size_cpu = os.environ.get("AML_COMPUTE_CLUSTER_CPU_SKU") compute_name_cpu = os.environ.get("AML_COMPUTE_CLUSTER_NAME") experiment_name = os.environ.get("EXPERIMENT_NAME") + model_name = os.environ.get("MODEL_NAME") # Get Azure machine learning workspace aml_workspace = get_workspace( @@ -56,7 +57,7 @@ def main(): run_config.environment.docker.enabled = True model_name = PipelineParameter( - name="model_name", default_value="sklearn_regression_model.pkl") + name="model_name", default_value=model_name) def_blob_store = Datastore(aml_workspace, "workspaceblobstore") jsonconfigs = PipelineData("jsonconfigs", datastore=def_blob_store) config_suffix = datetime.datetime.now().strftime("%Y%m%d%H") @@ -119,6 +120,11 @@ def main(): train_pipeline.validate() train_pipeline.submit(experiment_name=experiment_name) + train_pipeline_json = {} + train_pipeline_json["rest_endpoint"] = train_pipeline.endpoint + with open($(Build.ArtifactStagingDirectory)"/train_pipeline.json", "w") as outfile: + json.dump(train_pipeline_json, outfile) + if __name__ == '__main__': main() diff --git a/aml_service/run_train_pipeline.py b/aml_service/run_train_pipeline.py new file mode 100644 index 00000000..74f11873 --- /dev/null +++ b/aml_service/run_train_pipeline.py @@ -0,0 +1,27 @@ +import sys, os, json, requests +from azureml.core.authentication import AzureCliAuthentication + + +try: + with open("train_pipeline.json") as f: + train_pipeline_json = json.load(f) +except: + print("No pipeline json found") + sys.exit(0) + +experiment_name = os.environ.get("EXPERIMENT_NAME") +model_name = os.environ.get("MODEL_NAME") + +cli_auth = AzureCliAuthentication() +token = cli_auth.get_authentication_header() + +rest_endpoint = train_pipeline_json["rest_endpoint"] + +response = requests.post( + rest_endpoint, headers=token, + json={"ExperimentName": experiment_name, + "ParameterAssignments": {"model_name":model_name}} +) + +run_id = response.json()["Id"] +print("Pipeline run initiated ", run_id) diff --git a/azdo_pipelines/build-train.yml b/azdo_pipelines/build-train.yml index 536c06f8..d8cf9c86 100644 --- a/azdo_pipelines/build-train.yml +++ b/azdo_pipelines/build-train.yml @@ -49,10 +49,25 @@ steps: enabled: 'true' - bash: | - # Invoke the Python training pipeline + # Invoke the Python building and publishing a training pipeline python3 $(Build.SourcesDirectory)/aml_pipelines/model_train_pipeline.py failOnStderr: 'false' env: SP_APP_SECRET: '$(SP_APP_SECRET)' displayName: 'Train model using AML with Remote Compute' - enabled: 'true' \ No newline at end of file + enabled: 'true' + +- task: CopyFiles@2 + displayName: 'Copy Files to: $(Build.ArtifactStagingDirectory)' + inputs: + SourceFolder: '$(Build.SourcesDirectory)/aml_service' + TargetFolder: '$(Build.ArtifactStagingDirectory)' + Contents: 'run_train_pipeline.py' + +- task: PublishBuildArtifacts@1 + displayName: 'Publish Artifact' + inputs: + ArtifactName: 'mlops-pipelines' + publishLocation: 'container' + pathtoPublish: '$(Build.ArtifactStagingDirectory)' + TargetPath: '$(Build.ArtifactStagingDirectory)' \ No newline at end of file From fea510a5391d0826f8044802afba1af1c14b835b Mon Sep 17 00:00:00 2001 From: Eugene Fedorenko Date: Thu, 8 Aug 2019 15:46:34 -0700 Subject: [PATCH 052/113] linting --- aml_pipelines/model_train_pipeline.py | 3 ++- aml_service/run_train_pipeline.py | 13 ++++++++----- 2 files changed, 10 insertions(+), 6 deletions(-) diff --git a/aml_pipelines/model_train_pipeline.py b/aml_pipelines/model_train_pipeline.py index 947dfc3b..f8643b06 100644 --- a/aml_pipelines/model_train_pipeline.py +++ b/aml_pipelines/model_train_pipeline.py @@ -122,7 +122,8 @@ def main(): train_pipeline_json = {} train_pipeline_json["rest_endpoint"] = train_pipeline.endpoint - with open($(Build.ArtifactStagingDirectory)"/train_pipeline.json", "w") as outfile: + json_file_path = $(Build.ArtifactStagingDirectory) + "/train_pipeline.json" + with open(json_file_path, "w") as outfile: json.dump(train_pipeline_json, outfile) diff --git a/aml_service/run_train_pipeline.py b/aml_service/run_train_pipeline.py index 74f11873..c036aefd 100644 --- a/aml_service/run_train_pipeline.py +++ b/aml_service/run_train_pipeline.py @@ -1,15 +1,18 @@ -import sys, os, json, requests +import sys +import os +import json +import requests from azureml.core.authentication import AzureCliAuthentication try: with open("train_pipeline.json") as f: train_pipeline_json = json.load(f) -except: +except Exception: print("No pipeline json found") sys.exit(0) -experiment_name = os.environ.get("EXPERIMENT_NAME") +experiment_name = os.environ.get("EXPERIMENT_NAME") model_name = os.environ.get("MODEL_NAME") cli_auth = AzureCliAuthentication() @@ -18,9 +21,9 @@ rest_endpoint = train_pipeline_json["rest_endpoint"] response = requests.post( - rest_endpoint, headers=token, + rest_endpoint, headers=token, json={"ExperimentName": experiment_name, - "ParameterAssignments": {"model_name":model_name}} + "ParameterAssignments": {"model_name": model_name}} ) run_id = response.json()["Id"] From c91f2c6aeb63440514663aeb92b4e235bb75a1bf Mon Sep 17 00:00:00 2001 From: Eugene Fedorenko Date: Thu, 8 Aug 2019 16:00:59 -0700 Subject: [PATCH 053/113] fix --- aml_pipelines/model_train_pipeline.py | 8 +++++--- 1 file changed, 5 insertions(+), 3 deletions(-) diff --git a/aml_pipelines/model_train_pipeline.py b/aml_pipelines/model_train_pipeline.py index f8643b06..671c737c 100644 --- a/aml_pipelines/model_train_pipeline.py +++ b/aml_pipelines/model_train_pipeline.py @@ -118,11 +118,13 @@ def main(): train_pipeline = Pipeline(workspace=aml_workspace, steps=steps) train_pipeline.validate() - train_pipeline.submit(experiment_name=experiment_name) + published_pipeline = train_pipeline.publish( + name="training-pipeline", description="Model training/retraining pipeline" + ) train_pipeline_json = {} - train_pipeline_json["rest_endpoint"] = train_pipeline.endpoint - json_file_path = $(Build.ArtifactStagingDirectory) + "/train_pipeline.json" + train_pipeline_json["rest_endpoint"] = published_pipeline.endpoint + json_file_path = "aml_service/train_pipeline.json" with open(json_file_path, "w") as outfile: json.dump(train_pipeline_json, outfile) From db72b47d5219aa106423db2d359ac1d556520c6e Mon Sep 17 00:00:00 2001 From: Eugene Fedorenko Date: Thu, 8 Aug 2019 16:14:55 -0700 Subject: [PATCH 054/113] fix --- aml_pipelines/model_train_pipeline.py | 5 +++-- 1 file changed, 3 insertions(+), 2 deletions(-) diff --git a/aml_pipelines/model_train_pipeline.py b/aml_pipelines/model_train_pipeline.py index 671c737c..9aab910e 100644 --- a/aml_pipelines/model_train_pipeline.py +++ b/aml_pipelines/model_train_pipeline.py @@ -10,6 +10,7 @@ sys.path.append(os.path.abspath("./aml_service")) # NOQA: E402 from workspace import get_workspace from attach_compute import get_compute +import json def main(): @@ -26,7 +27,6 @@ def main(): register_script_path = os.environ.get("REGISTER_SCRIPT_PATH") vm_size_cpu = os.environ.get("AML_COMPUTE_CLUSTER_CPU_SKU") compute_name_cpu = os.environ.get("AML_COMPUTE_CLUSTER_NAME") - experiment_name = os.environ.get("EXPERIMENT_NAME") model_name = os.environ.get("MODEL_NAME") # Get Azure machine learning workspace @@ -119,7 +119,8 @@ def main(): train_pipeline = Pipeline(workspace=aml_workspace, steps=steps) train_pipeline.validate() published_pipeline = train_pipeline.publish( - name="training-pipeline", description="Model training/retraining pipeline" + name="training-pipeline", + description="Model training/retraining pipeline" ) train_pipeline_json = {} From 9d2ecc5c3ac44418248d72ac7bfdcfd83ef1e97a Mon Sep 17 00:00:00 2001 From: Eugene Fedorenko Date: Thu, 8 Aug 2019 17:10:51 -0700 Subject: [PATCH 055/113] json to artifacts --- azdo_pipelines/build-train.yml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/azdo_pipelines/build-train.yml b/azdo_pipelines/build-train.yml index 2a0b762b..9ce730e6 100644 --- a/azdo_pipelines/build-train.yml +++ b/azdo_pipelines/build-train.yml @@ -33,7 +33,7 @@ steps: inputs: SourceFolder: '$(Build.SourcesDirectory)/aml_service' TargetFolder: '$(Build.ArtifactStagingDirectory)' - Contents: 'run_train_pipeline.py' + Contents: '?(run_train_pipeline.py|*.json)' - task: PublishBuildArtifacts@1 displayName: 'Publish Artifact' From de3f1a41cb9fb8aea414ecf57dfa4ff40b6719f6 Mon Sep 17 00:00:00 2001 From: Eugene Fedorenko Date: Fri, 9 Aug 2019 14:18:28 -0700 Subject: [PATCH 056/113] Update iac-create-environment.yml for Azure Pipelines --- environment_setup/iac-create-environment.yml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/environment_setup/iac-create-environment.yml b/environment_setup/iac-create-environment.yml index fffaf066..af2c2fcd 100644 --- a/environment_setup/iac-create-environment.yml +++ b/environment_setup/iac-create-environment.yml @@ -12,7 +12,7 @@ pool: variables: baseName: $[coalesce(variables['baseNameOverride'], 'mlops')] location: $[coalesce(variables['locationOverride'], 'centralus')] - azuresub: $[coalesce(variables['azuresubOverride'], 'davete02_sub')] + azuresub: $[coalesce(variables['azuresubOverride'], 'AzureResourceConnection')] steps: From d42acaa3a1fe3dff680a8cf2bbfd46c839646578 Mon Sep 17 00:00:00 2001 From: Eugene Fedorenko Date: Fri, 9 Aug 2019 15:24:03 -0700 Subject: [PATCH 057/113] score files to the artifact --- .gitignore | 3 +- aml_pipelines/model_train_pipeline.py | 2 +- .../run_train_pipeline.py | 0 azdo_pipelines/build-train.yml | 6 +- code/scoring/create_scoring_image.py | 124 ------------------ code/scoring/deployment_config_aci.yml | 0 code/scoring/deployment_config_aks.yml | 0 code/scoring/inference_config.yml | 9 ++ 8 files changed, 16 insertions(+), 128 deletions(-) rename {aml_service => aml_pipelines}/run_train_pipeline.py (100%) delete mode 100644 code/scoring/create_scoring_image.py create mode 100644 code/scoring/deployment_config_aci.yml create mode 100644 code/scoring/deployment_config_aks.yml create mode 100644 code/scoring/inference_config.yml diff --git a/.gitignore b/.gitignore index 82e6a89a..b327895b 100644 --- a/.gitignore +++ b/.gitignore @@ -104,4 +104,5 @@ venv.bak/ # mypy .mypy_cache/ -aml_config/config.json \ No newline at end of file +aml_config/config.json +.DS_Store diff --git a/aml_pipelines/model_train_pipeline.py b/aml_pipelines/model_train_pipeline.py index 9aab910e..f4db330e 100644 --- a/aml_pipelines/model_train_pipeline.py +++ b/aml_pipelines/model_train_pipeline.py @@ -125,7 +125,7 @@ def main(): train_pipeline_json = {} train_pipeline_json["rest_endpoint"] = published_pipeline.endpoint - json_file_path = "aml_service/train_pipeline.json" + json_file_path = "aml_pipelines/train_pipeline.json" with open(json_file_path, "w") as outfile: json.dump(train_pipeline_json, outfile) diff --git a/aml_service/run_train_pipeline.py b/aml_pipelines/run_train_pipeline.py similarity index 100% rename from aml_service/run_train_pipeline.py rename to aml_pipelines/run_train_pipeline.py diff --git a/azdo_pipelines/build-train.yml b/azdo_pipelines/build-train.yml index 9ce730e6..a40348b4 100644 --- a/azdo_pipelines/build-train.yml +++ b/azdo_pipelines/build-train.yml @@ -31,9 +31,11 @@ steps: - task: CopyFiles@2 displayName: 'Copy Files to: $(Build.ArtifactStagingDirectory)' inputs: - SourceFolder: '$(Build.SourcesDirectory)/aml_service' + SourceFolder: '$(Build.SourcesDirectory)' TargetFolder: '$(Build.ArtifactStagingDirectory)' - Contents: '?(run_train_pipeline.py|*.json)' + Contents: | + aml_pipelines/**/'?(run_train_pipeline.py|*.json)' + code/scoring/** - task: PublishBuildArtifacts@1 displayName: 'Publish Artifact' diff --git a/code/scoring/create_scoring_image.py b/code/scoring/create_scoring_image.py deleted file mode 100644 index d30d400d..00000000 --- a/code/scoring/create_scoring_image.py +++ /dev/null @@ -1,124 +0,0 @@ -""" -Copyright (C) Microsoft Corporation. All rights reserved.​ - ​ -Microsoft Corporation (“Microsoft”) grants you a nonexclusive, perpetual, -royalty-free right to use, copy, and modify the software code provided by us -("Software Code"). You may not sublicense the Software Code or any use of it -(except to your affiliates and to vendors to perform work on your behalf) -through distribution, network access, service agreement, lease, rental, or -otherwise. This license does not purport to express any claim of ownership over -data you may have shared with Microsoft in the creation of the Software Code. -Unless applicable law gives you more rights, Microsoft reserves all other -rights not expressly granted herein, whether by implication, estoppel or -otherwise. ​ - ​ -THE SOFTWARE CODE IS PROVIDED “AS IS”, WITHOUT WARRANTY OF ANY KIND, EXPRESS -OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, -FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL -MICROSOFT OR ITS LICENSORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, -SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, -PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR -BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER -IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -ARISING IN ANY WAY OUT OF THE USE OF THE SOFTWARE CODE, EVEN IF ADVISED OF THE -POSSIBILITY OF SUCH DAMAGE. -""" -import os -import json -import sys -import argparse -from azureml.core import Workspace -from azureml.core.image import ContainerImage, Image -from azureml.core import Run -from azureml.core.model import Model -from azureml.core.authentication import AzureCliAuthentication - -cli_auth = AzureCliAuthentication() - -run = Run.get_context() -if "OfflineRun" in run.id: - print("offline run") - # Get workspace - ws = Workspace.from_config(auth=cli_auth, path='./') -else: - exp = run.experiment - ws = run.experiment.workspace - -# Get the latest model details - -parser = argparse.ArgumentParser("scoring_image") -parser.add_argument( - "--config_suffix", type=str, help="Datetime suffix for json config files" -) -parser.add_argument( - "--json_config", - type=str, - help="Directory to write all the intermediate json configs", -) -args = parser.parse_args() - -register_model_json = "model_{}.json".format(args.config_suffix) -register_output_path = os.path.join(args.json_config, register_model_json) - - -try: - with open(register_output_path) as f: - config = json.load(f) -except Exception: - print("No new model to register thus no need to create new scoring image") - sys.exit(0) - -model_name = config["model_name"] -model_version = config["model_version"] - -model_list = Model.list(workspace=ws) -model, = (m for m in model_list if m.version == - model_version and m.name == model_name) -print( - "Model picked: {} \nModel Description: {} \nModel Version: {}".format( - model.name, model.description, model.version - ) -) - -os.chdir("scoring") -image_name = "diabetes-model-score" - -image_config = ContainerImage.image_configuration( - execution_script="score.py", - runtime="python-slim", - conda_file="conda_dependencies.yml", - description="Image with ridge regression model", - tags={"area": "diabetes", "type": "regression"}, -) - -image = Image.create( - name=image_name, models=[model], image_config=image_config, workspace=ws -) - -image.wait_for_creation(show_output=True) -os.chdir("..") - -if image.creation_state != "Succeeded": - raise Exception("Image creation status: {image.creation_state}") - -print( - "{}(v.{} [{}]) stored at {} with build log {}".format( - image.name, - image.version, - image.creation_state, - image.image_location, - image.image_build_log_uri, - ) -) - -# Writing the image details to /aml_config/image.json -image_json = {} -image_json["image_name"] = image.name -image_json["image_version"] = image.version -image_json["image_location"] = image.image_location -# with open("aml_config/image.json", "w") as outfile: -# json.dump(image_json, outfile) -filename = "image_{}.json".format(args.config_suffix) -output_path = os.path.join(args.json_config, filename) -with open(output_path, "w") as outfile: - json.dump(image_json, outfile) diff --git a/code/scoring/deployment_config_aci.yml b/code/scoring/deployment_config_aci.yml new file mode 100644 index 00000000..e69de29b diff --git a/code/scoring/deployment_config_aks.yml b/code/scoring/deployment_config_aks.yml new file mode 100644 index 00000000..e69de29b diff --git a/code/scoring/inference_config.yml b/code/scoring/inference_config.yml new file mode 100644 index 00000000..3f65cf33 --- /dev/null +++ b/code/scoring/inference_config.yml @@ -0,0 +1,9 @@ +entryScript: score.py +runtime: python +condaFile: conda_dependencies.yml +extraDockerfileSteps: +schemaFile: +sourceDirectory: +enableGpu: False +baseImage: +baseImageRegistry: \ No newline at end of file From ea22125d45d2608b35d3349afe18d38dbcbb64e1 Mon Sep 17 00:00:00 2001 From: Eugene Fedorenko Date: Fri, 9 Aug 2019 15:24:32 -0700 Subject: [PATCH 058/113] scoring files to the artifacts --- code/scoring/deployment_config_aci.yml | 5 +++++ code/scoring/deployment_config_aks.yml | 16 ++++++++++++++++ 2 files changed, 21 insertions(+) diff --git a/code/scoring/deployment_config_aci.yml b/code/scoring/deployment_config_aci.yml index e69de29b..b64478f0 100644 --- a/code/scoring/deployment_config_aci.yml +++ b/code/scoring/deployment_config_aci.yml @@ -0,0 +1,5 @@ +--- +containerResourceRequirements: + cpu: 1 + memoryInGB: 1 +computeType: ACI \ No newline at end of file diff --git a/code/scoring/deployment_config_aks.yml b/code/scoring/deployment_config_aks.yml index e69de29b..2832da6f 100644 --- a/code/scoring/deployment_config_aks.yml +++ b/code/scoring/deployment_config_aks.yml @@ -0,0 +1,16 @@ +computeType: AKS +autoScaler: + autoscaleEnabled: True + minReplicas: 1 + maxReplicas: 3 + refreshPeriodInSeconds: 10 + targetUtilization: 70 +authEnabled: True +containerResourceRequirements: + cpu: 1 + memoryInGB: 2 +appInsightsEnabled: False +scoringTimeoutMs: 5000 +maxConcurrentRequestsPerContainer: 2 +maxQueueWaitMs: 5000 +sslEnabled: True \ No newline at end of file From ba549960f68f450bad1be8269b6a4c2e50a2c3ca Mon Sep 17 00:00:00 2001 From: Eugene Fedorenko Date: Fri, 9 Aug 2019 15:30:37 -0700 Subject: [PATCH 059/113] fixing artifacts path --- azdo_pipelines/build-train.yml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/azdo_pipelines/build-train.yml b/azdo_pipelines/build-train.yml index a40348b4..b9f0bdea 100644 --- a/azdo_pipelines/build-train.yml +++ b/azdo_pipelines/build-train.yml @@ -34,7 +34,7 @@ steps: SourceFolder: '$(Build.SourcesDirectory)' TargetFolder: '$(Build.ArtifactStagingDirectory)' Contents: | - aml_pipelines/**/'?(run_train_pipeline.py|*.json)' + aml_pipelines/'?(run_train_pipeline.py|*.json)' code/scoring/** - task: PublishBuildArtifacts@1 From ba32d11a91e16a6730938d74530b24ca494fed15 Mon Sep 17 00:00:00 2001 From: Eugene Fedorenko Date: Fri, 9 Aug 2019 15:35:00 -0700 Subject: [PATCH 060/113] artifacts path --- azdo_pipelines/build-train.yml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/azdo_pipelines/build-train.yml b/azdo_pipelines/build-train.yml index b9f0bdea..67953ddd 100644 --- a/azdo_pipelines/build-train.yml +++ b/azdo_pipelines/build-train.yml @@ -35,7 +35,7 @@ steps: TargetFolder: '$(Build.ArtifactStagingDirectory)' Contents: | aml_pipelines/'?(run_train_pipeline.py|*.json)' - code/scoring/** + - task: PublishBuildArtifacts@1 displayName: 'Publish Artifact' From 1b9be89de1acee39a66fc760d948bd6d9d9d908f Mon Sep 17 00:00:00 2001 From: Eugene Fedorenko Date: Fri, 9 Aug 2019 15:41:56 -0700 Subject: [PATCH 061/113] artifacts folders --- azdo_pipelines/build-train.yml | 3 ++- 1 file changed, 2 insertions(+), 1 deletion(-) diff --git a/azdo_pipelines/build-train.yml b/azdo_pipelines/build-train.yml index 67953ddd..9aee2c32 100644 --- a/azdo_pipelines/build-train.yml +++ b/azdo_pipelines/build-train.yml @@ -34,7 +34,8 @@ steps: SourceFolder: '$(Build.SourcesDirectory)' TargetFolder: '$(Build.ArtifactStagingDirectory)' Contents: | - aml_pipelines/'?(run_train_pipeline.py|*.json)' + aml_pipelines/?(run_train_pipeline.py|*.json) + code/scoring/** - task: PublishBuildArtifacts@1 From bbf2a2f95d542bb699b44f154060efc44a15d1ec Mon Sep 17 00:00:00 2001 From: Eugene Fedorenko Date: Fri, 9 Aug 2019 16:48:22 -0700 Subject: [PATCH 062/113] fixing scoring issues --- code/scoring/conda_dependencies.yml | 5 +++-- code/scoring/score.py | 5 +++-- 2 files changed, 6 insertions(+), 4 deletions(-) diff --git a/code/scoring/conda_dependencies.yml b/code/scoring/conda_dependencies.yml index 9bca0710..6dc98620 100644 --- a/code/scoring/conda_dependencies.yml +++ b/code/scoring/conda_dependencies.yml @@ -44,6 +44,7 @@ dependencies: # Required packages for AzureML execution, history, and data preparation. - azureml-sdk[notebooks] # add the version to lock it ==0.1.74 - scipy==1.0.0 - - scikit-learn==0.19.1 + - scikit-learn==0.21.3 - pandas==0.23.1 - - numpy==1.14.5 \ No newline at end of file + - numpy==1.14.5 + - joblib==0.13.2 \ No newline at end of file diff --git a/code/scoring/score.py b/code/scoring/score.py index 3208d9d0..4d61cf80 100644 --- a/code/scoring/score.py +++ b/code/scoring/score.py @@ -26,15 +26,16 @@ import json import numpy from azureml.core.model import Model +import joblib def init(): - global model - from sklearn.externals import joblib + global model # load the model from file into a global object model_path = Model.get_model_path( model_name="sklearn_regression_model.pkl") + print("model_path", model_path) model = joblib.load(model_path) From 0b68535c75cdd75512ab6a02e4bd18ae30c14480 Mon Sep 17 00:00:00 2001 From: Eugene Fedorenko Date: Fri, 9 Aug 2019 16:53:02 -0700 Subject: [PATCH 063/113] linting score --- code/scoring/score.py | 5 ++--- 1 file changed, 2 insertions(+), 3 deletions(-) diff --git a/code/scoring/score.py b/code/scoring/score.py index 4d61cf80..d16ff6d9 100644 --- a/code/scoring/score.py +++ b/code/scoring/score.py @@ -30,12 +30,11 @@ def init(): - global model + global model # load the model from file into a global object model_path = Model.get_model_path( - model_name="sklearn_regression_model.pkl") - print("model_path", model_path) + model_name="sklearn_regression_model.pkl") model = joblib.load(model_path) From 2bb53b586c08090fe63df6a5a1bb75392bb2fb17 Mon Sep 17 00:00:00 2001 From: Eugene Fedorenko Date: Fri, 9 Aug 2019 16:55:56 -0700 Subject: [PATCH 064/113] linting score --- code/scoring/score.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/code/scoring/score.py b/code/scoring/score.py index d16ff6d9..dafe6bee 100644 --- a/code/scoring/score.py +++ b/code/scoring/score.py @@ -34,7 +34,7 @@ def init(): # load the model from file into a global object model_path = Model.get_model_path( - model_name="sklearn_regression_model.pkl") + model_name="sklearn_regression_model.pkl") model = joblib.load(model_path) From a51e5a113c436c504774134149b891d6cabbc3ac Mon Sep 17 00:00:00 2001 From: Eugene Fedorenko Date: Fri, 9 Aug 2019 18:17:16 -0700 Subject: [PATCH 065/113] scoring dependencies --- code/scoring/conda_dependencies.yml | 6 +++++- code/scoring/deployment_config_aci.yml | 2 +- code/scoring/deployment_config_aks.yml | 2 +- 3 files changed, 7 insertions(+), 3 deletions(-) diff --git a/code/scoring/conda_dependencies.yml b/code/scoring/conda_dependencies.yml index 6dc98620..f13c3c3d 100644 --- a/code/scoring/conda_dependencies.yml +++ b/code/scoring/conda_dependencies.yml @@ -47,4 +47,8 @@ dependencies: - scikit-learn==0.21.3 - pandas==0.23.1 - numpy==1.14.5 - - joblib==0.13.2 \ No newline at end of file + - joblib==0.13.2 + - gunicorn==19.9.0 + - flask==1.1.1 + - azure-ml-api-sdk + diff --git a/code/scoring/deployment_config_aci.yml b/code/scoring/deployment_config_aci.yml index b64478f0..939483b5 100644 --- a/code/scoring/deployment_config_aci.yml +++ b/code/scoring/deployment_config_aci.yml @@ -1,5 +1,5 @@ --- containerResourceRequirements: cpu: 1 - memoryInGB: 1 + memoryInGB: 4 computeType: ACI \ No newline at end of file diff --git a/code/scoring/deployment_config_aks.yml b/code/scoring/deployment_config_aks.yml index 2832da6f..5cc78847 100644 --- a/code/scoring/deployment_config_aks.yml +++ b/code/scoring/deployment_config_aks.yml @@ -8,7 +8,7 @@ autoScaler: authEnabled: True containerResourceRequirements: cpu: 1 - memoryInGB: 2 + memoryInGB: 4 appInsightsEnabled: False scoringTimeoutMs: 5000 maxConcurrentRequestsPerContainer: 2 From 808104af01806157e21d69c6da24eb01eee9c2b4 Mon Sep 17 00:00:00 2001 From: Eugene Fedorenko Date: Mon, 12 Aug 2019 11:43:56 -0700 Subject: [PATCH 066/113] folders refactoring --- .../build_train_pipeline.py | 0 .../run_train_pipeline.py | 0 azdo_pipelines/ci-build-score.yml | 19 - .../{build-train.yml => ci-build-train.yml} | 2 +- azdo_pipelines/ci-build.yml | 14 - .../docker-builder-image-pipeline.yml | 17 - azdo_pipelines/pr-build-score.yml | 18 - azdo_pipelines/pr-build-train.yml | 13 +- .../docker-builder-image-template.yml | 10 - azure-pipelines.yml | 18 - .../arm-templates/cloud-environment.json | 4 +- .../{ => azure}/docker-image-pipeline.yml | 0 .../{ => azure}/iac-create-environment.yml | 0 .../{ => azure}/iac-remove-environment.yml | 0 model/placeholder | 0 release-pipelines/releasedeployment.json | 581 ------------------ release-pipelines/retrainingtrigger.json | 291 --------- 17 files changed, 11 insertions(+), 976 deletions(-) rename aml_pipelines/model_train_pipeline.py => aml_service/build_train_pipeline.py (100%) rename {aml_pipelines => aml_service}/run_train_pipeline.py (100%) delete mode 100644 azdo_pipelines/ci-build-score.yml rename azdo_pipelines/{build-train.yml => ci-build-train.yml} (99%) delete mode 100644 azdo_pipelines/ci-build.yml delete mode 100644 azdo_pipelines/docker-builder-image-pipeline.yml delete mode 100644 azdo_pipelines/pr-build-score.yml delete mode 100644 azdo_pipelines/templates/docker-builder-image-template.yml delete mode 100644 azure-pipelines.yml rename environment_setup/{ => azure}/arm-templates/cloud-environment.json (99%) rename environment_setup/{ => azure}/docker-image-pipeline.yml (100%) rename environment_setup/{ => azure}/iac-create-environment.yml (100%) rename environment_setup/{ => azure}/iac-remove-environment.yml (100%) delete mode 100644 model/placeholder delete mode 100644 release-pipelines/releasedeployment.json delete mode 100644 release-pipelines/retrainingtrigger.json diff --git a/aml_pipelines/model_train_pipeline.py b/aml_service/build_train_pipeline.py similarity index 100% rename from aml_pipelines/model_train_pipeline.py rename to aml_service/build_train_pipeline.py diff --git a/aml_pipelines/run_train_pipeline.py b/aml_service/run_train_pipeline.py similarity index 100% rename from aml_pipelines/run_train_pipeline.py rename to aml_service/run_train_pipeline.py diff --git a/azdo_pipelines/ci-build-score.yml b/azdo_pipelines/ci-build-score.yml deleted file mode 100644 index 61e7ba79..00000000 --- a/azdo_pipelines/ci-build-score.yml +++ /dev/null @@ -1,19 +0,0 @@ -pr: -- master - -pool: - vmImage: 'ubuntu-latest' - -container: - image: $(FULL_AGENT_IMAGE_NAME) - endpoint: acrconnection - - -steps: -- template: base-pipeline.yml - parameters: - requirementsPath: 'requirements.txt' - pipelineType: 'score' - -- publish: $(Build.SourcesDirectory)/Code/src/score - artifact: 'scoring_pipeline' diff --git a/azdo_pipelines/build-train.yml b/azdo_pipelines/ci-build-train.yml similarity index 99% rename from azdo_pipelines/build-train.yml rename to azdo_pipelines/ci-build-train.yml index 9aee2c32..6d26230c 100644 --- a/azdo_pipelines/build-train.yml +++ b/azdo_pipelines/ci-build-train.yml @@ -4,7 +4,7 @@ trigger: include: - master -pool: +pool: vmImage: 'ubuntu-latest' container: diff --git a/azdo_pipelines/ci-build.yml b/azdo_pipelines/ci-build.yml deleted file mode 100644 index a1ff4d9c..00000000 --- a/azdo_pipelines/ci-build.yml +++ /dev/null @@ -1,14 +0,0 @@ -pr: -- master - -pool: - vmImage: 'ubuntu-latest' - -container: - image: $(FULL_AGENT_IMAGE_NAME) - endpoint: acrconnection - -steps: -- template: base-pipeline.yml - parameters: - requirementsPath: 'requirements.txt' \ No newline at end of file diff --git a/azdo_pipelines/docker-builder-image-pipeline.yml b/azdo_pipelines/docker-builder-image-pipeline.yml deleted file mode 100644 index bf993992..00000000 --- a/azdo_pipelines/docker-builder-image-pipeline.yml +++ /dev/null @@ -1,17 +0,0 @@ -trigger: none -pr: - branches: - include: - - master - -pool: - vmImage: 'ubuntu-latest' - -variables: - baseName: $[coalesce(variables['baseNameOverride'], 'pythonml')] - containerRegistry: $[coalesce(variables['acrServiceConnection'], 'acrconnection')] - imageName: $[coalesce(variables['builderImageName'], 'mlopsbuildagent')] - - -steps: - - template: templates/docker-builder-image-template.yml diff --git a/azdo_pipelines/pr-build-score.yml b/azdo_pipelines/pr-build-score.yml deleted file mode 100644 index 855044d7..00000000 --- a/azdo_pipelines/pr-build-score.yml +++ /dev/null @@ -1,18 +0,0 @@ -trigger: none -pr: - branches: - include: - - master - -pool: - vmImage: 'ubuntu-latest' - -container: - image: $(FULL_AGENT_IMAGE_NAME) - endpoint: acrconnection - -steps: -- template: base-pipeline.yml - parameters: - requirementsPath: 'requirements.txt' - pipelineType: 'score' \ No newline at end of file diff --git a/azdo_pipelines/pr-build-train.yml b/azdo_pipelines/pr-build-train.yml index 607ea133..f6941301 100644 --- a/azdo_pipelines/pr-build-train.yml +++ b/azdo_pipelines/pr-build-train.yml @@ -4,16 +4,17 @@ pr: include: - master -pool: +pool: vmImage: 'ubuntu-latest' - container: - image: $(FULL_AGENT_IMAGE_NAME) + image: mlopscr.azurecr.io/public/mlops/mlopspython:latest endpoint: acrconnection +variables: +- group: devopsforai-aml-vg + + steps: -- template: base-pipeline.yml - parameters: - requirementsPath: 'requirements.txt' \ No newline at end of file +- template: base-pipeline.yml \ No newline at end of file diff --git a/azdo_pipelines/templates/docker-builder-image-template.yml b/azdo_pipelines/templates/docker-builder-image-template.yml deleted file mode 100644 index 0640ff50..00000000 --- a/azdo_pipelines/templates/docker-builder-image-template.yml +++ /dev/null @@ -1,10 +0,0 @@ -steps: - - task: Docker@2 - displayName: Build and Push - inputs: - command: buildAndPush - containerRegistry: '$(containerRegistry)' - repository: '$(imageName)' - tags: 'latest' - buildContext: '$(Build.SourcesDirectory)/Code' - dockerFile: '$(Build.SourcesDirectory)/Code/build_agent/Dockerfile' \ No newline at end of file diff --git a/azure-pipelines.yml b/azure-pipelines.yml deleted file mode 100644 index c3714cfd..00000000 --- a/azure-pipelines.yml +++ /dev/null @@ -1,18 +0,0 @@ -# keeping this pipeline for now to get Microsoft.MLOpsPython working on https://dev.azure.com/customai/DevopsForAI-AML -pool: - vmImage: 'Ubuntu 16.04' - -variables: -- group: AzureKeyVaultSecrets - -trigger: -- master -- releases/* -- develop - -steps: -- script: | - echo 'dummy step' - - displayName: 'Dummy step' - diff --git a/environment_setup/arm-templates/cloud-environment.json b/environment_setup/azure/arm-templates/cloud-environment.json similarity index 99% rename from environment_setup/arm-templates/cloud-environment.json rename to environment_setup/azure/arm-templates/cloud-environment.json index 8fd905cb..45c6a0b8 100644 --- a/environment_setup/arm-templates/cloud-environment.json +++ b/environment_setup/azure/arm-templates/cloud-environment.json @@ -118,6 +118,8 @@ "containerRegistry": "[resourceId('Microsoft.ContainerRegistry/registries',variables('containerRegistryName'))]", "storageAccount": "[resourceId('Microsoft.Storage/storageAccounts/',variables('storageAccountName'))]" } - } + }, + + ] } \ No newline at end of file diff --git a/environment_setup/docker-image-pipeline.yml b/environment_setup/azure/docker-image-pipeline.yml similarity index 100% rename from environment_setup/docker-image-pipeline.yml rename to environment_setup/azure/docker-image-pipeline.yml diff --git a/environment_setup/iac-create-environment.yml b/environment_setup/azure/iac-create-environment.yml similarity index 100% rename from environment_setup/iac-create-environment.yml rename to environment_setup/azure/iac-create-environment.yml diff --git a/environment_setup/iac-remove-environment.yml b/environment_setup/azure/iac-remove-environment.yml similarity index 100% rename from environment_setup/iac-remove-environment.yml rename to environment_setup/azure/iac-remove-environment.yml diff --git a/model/placeholder b/model/placeholder deleted file mode 100644 index e69de29b..00000000 diff --git 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"https://vsrm.dev.azure.com/userorg/420d3eaf-7dbb-46cb-a7c9-93662c745570/_apis/Release/definitions/6", - "_links": { - "self": { - "href": "https://vsrm.dev.azure.com/userorg/420d3eaf-7dbb-46cb-a7c9-93662c745570/_apis/Release/definitions/6" - }, - "web": { - "href": "https://dev.azure.com/userorg/420d3eaf-7dbb-46cb-a7c9-93662c745570/_release?definitionId=6" - } - } -} \ No newline at end of file From d49770e1b490582fe54b615e4a09646e3f32a20f Mon Sep 17 00:00:00 2001 From: Eugene Fedorenko Date: Mon, 12 Aug 2019 12:31:05 -0700 Subject: [PATCH 067/113] folders refactoring --- .../base-pipeline.yml => .pipelines/azdo-base-pipeline.yml | 0 .../ci-build-train.yml => .pipelines/azdo-ci-build-train.yml | 0 .../pr-build-train.yml => .pipelines/azdo-pr-build-train.yml | 0 .../{azure => }/arm-templates/cloud-environment.json | 0 environment_setup/{azure => }/docker-image-pipeline.yml | 0 environment_setup/{azure => }/iac-create-environment.yml | 0 environment_setup/{azure => }/iac-remove-environment.yml | 0 {aml_service => ml_service/pipelines}/build_train_pipeline.py | 0 {aml_service => ml_service/pipelines}/run_train_pipeline.py | 0 .../util/azure_ml_attach_compute.py | 0 {aml_service => ml_service/util}/register_model.py | 0 {aml_service => ml_service/util}/workspace.py | 0 12 files changed, 0 insertions(+), 0 deletions(-) rename azdo_pipelines/base-pipeline.yml => .pipelines/azdo-base-pipeline.yml (100%) rename azdo_pipelines/ci-build-train.yml => .pipelines/azdo-ci-build-train.yml (100%) rename azdo_pipelines/pr-build-train.yml => .pipelines/azdo-pr-build-train.yml (100%) rename environment_setup/{azure => }/arm-templates/cloud-environment.json (100%) rename environment_setup/{azure => }/docker-image-pipeline.yml (100%) rename environment_setup/{azure => }/iac-create-environment.yml (100%) rename environment_setup/{azure => }/iac-remove-environment.yml (100%) rename {aml_service => ml_service/pipelines}/build_train_pipeline.py (100%) rename {aml_service => ml_service/pipelines}/run_train_pipeline.py (100%) rename aml_service/attach_compute.py => ml_service/util/azure_ml_attach_compute.py (100%) rename {aml_service => ml_service/util}/register_model.py (100%) rename {aml_service => ml_service/util}/workspace.py (100%) diff --git a/azdo_pipelines/base-pipeline.yml b/.pipelines/azdo-base-pipeline.yml similarity index 100% rename from azdo_pipelines/base-pipeline.yml rename to .pipelines/azdo-base-pipeline.yml diff --git a/azdo_pipelines/ci-build-train.yml b/.pipelines/azdo-ci-build-train.yml similarity index 100% rename from azdo_pipelines/ci-build-train.yml rename to .pipelines/azdo-ci-build-train.yml diff --git a/azdo_pipelines/pr-build-train.yml b/.pipelines/azdo-pr-build-train.yml similarity index 100% rename from azdo_pipelines/pr-build-train.yml rename to .pipelines/azdo-pr-build-train.yml diff --git a/environment_setup/azure/arm-templates/cloud-environment.json b/environment_setup/arm-templates/cloud-environment.json similarity index 100% rename from environment_setup/azure/arm-templates/cloud-environment.json rename to environment_setup/arm-templates/cloud-environment.json diff --git a/environment_setup/azure/docker-image-pipeline.yml b/environment_setup/docker-image-pipeline.yml similarity index 100% rename from environment_setup/azure/docker-image-pipeline.yml rename to environment_setup/docker-image-pipeline.yml diff --git a/environment_setup/azure/iac-create-environment.yml b/environment_setup/iac-create-environment.yml similarity index 100% rename from environment_setup/azure/iac-create-environment.yml rename to environment_setup/iac-create-environment.yml diff --git a/environment_setup/azure/iac-remove-environment.yml b/environment_setup/iac-remove-environment.yml similarity index 100% rename from environment_setup/azure/iac-remove-environment.yml rename to environment_setup/iac-remove-environment.yml diff --git a/aml_service/build_train_pipeline.py b/ml_service/pipelines/build_train_pipeline.py similarity index 100% rename from aml_service/build_train_pipeline.py rename to ml_service/pipelines/build_train_pipeline.py diff --git a/aml_service/run_train_pipeline.py b/ml_service/pipelines/run_train_pipeline.py similarity index 100% rename from aml_service/run_train_pipeline.py rename to ml_service/pipelines/run_train_pipeline.py diff --git a/aml_service/attach_compute.py b/ml_service/util/azure_ml_attach_compute.py similarity index 100% rename from aml_service/attach_compute.py rename to ml_service/util/azure_ml_attach_compute.py diff --git a/aml_service/register_model.py b/ml_service/util/register_model.py similarity index 100% rename from aml_service/register_model.py rename to ml_service/util/register_model.py diff --git a/aml_service/workspace.py b/ml_service/util/workspace.py similarity index 100% rename from aml_service/workspace.py rename to ml_service/util/workspace.py From 91981ff8d357d60716ba1e2a90e7b054bf8ffd02 Mon Sep 17 00:00:00 2001 From: Eugene Fedorenko Date: Mon, 12 Aug 2019 12:39:40 -0700 Subject: [PATCH 068/113] connection name --- environment_setup/iac-create-environment.yml | 2 +- environment_setup/iac-remove-environment.yml | 2 +- 2 files changed, 2 insertions(+), 2 deletions(-) diff --git a/environment_setup/iac-create-environment.yml b/environment_setup/iac-create-environment.yml index fffaf066..af2c2fcd 100644 --- a/environment_setup/iac-create-environment.yml +++ b/environment_setup/iac-create-environment.yml @@ -12,7 +12,7 @@ pool: variables: baseName: $[coalesce(variables['baseNameOverride'], 'mlops')] location: $[coalesce(variables['locationOverride'], 'centralus')] - azuresub: $[coalesce(variables['azuresubOverride'], 'davete02_sub')] + azuresub: $[coalesce(variables['azuresubOverride'], 'AzureResourceConnection')] steps: diff --git a/environment_setup/iac-remove-environment.yml b/environment_setup/iac-remove-environment.yml index aaf6f060..152efa59 100644 --- a/environment_setup/iac-remove-environment.yml +++ b/environment_setup/iac-remove-environment.yml @@ -12,7 +12,7 @@ pool: variables: baseName: $[coalesce(variables['baseNameOverride'], 'mlops')] location: $[coalesce(variables['locationOverride'], 'centralus')] - azuresub: $[coalesce(variables['azuresubOverride'], 'davete02_sub')] + azuresub: $[coalesce(variables['azuresubOverride'], 'AzureResourceConnection')] steps: From 46389e6519423cc9faced633b3a8198092d51c83 Mon Sep 17 00:00:00 2001 From: Eugene Fedorenko Date: Mon, 12 Aug 2019 12:41:33 -0700 Subject: [PATCH 069/113] arm template fix --- environment_setup/arm-templates/cloud-environment.json | 4 +--- 1 file changed, 1 insertion(+), 3 deletions(-) diff --git a/environment_setup/arm-templates/cloud-environment.json b/environment_setup/arm-templates/cloud-environment.json index 45c6a0b8..e01471d7 100644 --- a/environment_setup/arm-templates/cloud-environment.json +++ b/environment_setup/arm-templates/cloud-environment.json @@ -118,8 +118,6 @@ "containerRegistry": "[resourceId('Microsoft.ContainerRegistry/registries',variables('containerRegistryName'))]", "storageAccount": "[resourceId('Microsoft.Storage/storageAccounts/',variables('storageAccountName'))]" } - }, - - + } ] } \ No newline at end of file From 03beb1fa7928195a766d8f62423f92c60feb98b9 Mon Sep 17 00:00:00 2001 From: Eugene Fedorenko Date: Mon, 12 Aug 2019 12:48:15 -0700 Subject: [PATCH 070/113] base pipeline got renamed --- .pipelines/azdo-ci-build-train.yml | 2 +- .pipelines/azdo-pr-build-train.yml | 2 +- 2 files changed, 2 insertions(+), 2 deletions(-) diff --git a/.pipelines/azdo-ci-build-train.yml b/.pipelines/azdo-ci-build-train.yml index 6d26230c..aeea9fad 100644 --- a/.pipelines/azdo-ci-build-train.yml +++ b/.pipelines/azdo-ci-build-train.yml @@ -17,7 +17,7 @@ variables: steps: -- template: base-pipeline.yml +- template: azdo-base-pipeline.yml - bash: | # Invoke the Python building and publishing a training pipeline diff --git a/.pipelines/azdo-pr-build-train.yml b/.pipelines/azdo-pr-build-train.yml index f6941301..6bbf7387 100644 --- a/.pipelines/azdo-pr-build-train.yml +++ b/.pipelines/azdo-pr-build-train.yml @@ -17,4 +17,4 @@ variables: steps: -- template: base-pipeline.yml \ No newline at end of file +- template: azdo-base-pipeline.yml \ No newline at end of file From 9df780c9c41f54cb6d19f8ca40aa220e819de233 Mon Sep 17 00:00:00 2001 From: Eugene Fedorenko Date: Mon, 12 Aug 2019 12:52:01 -0700 Subject: [PATCH 071/113] unit test fix --- ml_service/pipelines/build_train_pipeline.py | 2 +- tests/unit/code_test.py | 2 +- 2 files changed, 2 insertions(+), 2 deletions(-) diff --git a/ml_service/pipelines/build_train_pipeline.py b/ml_service/pipelines/build_train_pipeline.py index f4db330e..0f04b635 100644 --- a/ml_service/pipelines/build_train_pipeline.py +++ b/ml_service/pipelines/build_train_pipeline.py @@ -7,7 +7,7 @@ import os import sys from dotenv import load_dotenv -sys.path.append(os.path.abspath("./aml_service")) # NOQA: E402 +sys.path.append(os.path.abspath("./ml_service/util")) # NOQA: E402 from workspace import get_workspace from attach_compute import get_compute import json diff --git a/tests/unit/code_test.py b/tests/unit/code_test.py index b5421c27..bcdf5e3e 100644 --- a/tests/unit/code_test.py +++ b/tests/unit/code_test.py @@ -1,6 +1,6 @@ import sys import os -sys.path.append(os.path.abspath("./aml_service")) # NOQA: E402 +sys.path.append(os.path.abspath("./ml_service/util")) # NOQA: E402 from workspace import get_workspace From 82b7eb586003bbdbb8efa23a6cf31aa0b07e7b9e Mon Sep 17 00:00:00 2001 From: Eugene Fedorenko Date: Mon, 12 Aug 2019 13:47:23 -0700 Subject: [PATCH 072/113] fix --- .pipelines/azdo-ci-build-train.yml | 4 ++-- ml_service/pipelines/build_train_pipeline.py | 2 +- .../util/{azure_ml_attach_compute.py => attach_compute.py} | 0 3 files changed, 3 insertions(+), 3 deletions(-) rename ml_service/util/{azure_ml_attach_compute.py => attach_compute.py} (100%) diff --git a/.pipelines/azdo-ci-build-train.yml b/.pipelines/azdo-ci-build-train.yml index aeea9fad..f05c0958 100644 --- a/.pipelines/azdo-ci-build-train.yml +++ b/.pipelines/azdo-ci-build-train.yml @@ -21,7 +21,7 @@ steps: - bash: | # Invoke the Python building and publishing a training pipeline - python3 $(Build.SourcesDirectory)/aml_pipelines/model_train_pipeline.py + python3 $(Build.SourcesDirectory)/.pipelines/azdo-ci-build-train.py failOnStderr: 'false' env: SP_APP_SECRET: '$(SP_APP_SECRET)' @@ -34,7 +34,7 @@ steps: SourceFolder: '$(Build.SourcesDirectory)' TargetFolder: '$(Build.ArtifactStagingDirectory)' Contents: | - aml_pipelines/?(run_train_pipeline.py|*.json) + ml_service/pipelines/?(run_train_pipeline.py|*.json) code/scoring/** diff --git a/ml_service/pipelines/build_train_pipeline.py b/ml_service/pipelines/build_train_pipeline.py index 0f04b635..a294a1c0 100644 --- a/ml_service/pipelines/build_train_pipeline.py +++ b/ml_service/pipelines/build_train_pipeline.py @@ -125,7 +125,7 @@ def main(): train_pipeline_json = {} train_pipeline_json["rest_endpoint"] = published_pipeline.endpoint - json_file_path = "aml_pipelines/train_pipeline.json" + json_file_path = "ml_service/pipelines/train_pipeline.json" with open(json_file_path, "w") as outfile: json.dump(train_pipeline_json, outfile) diff --git a/ml_service/util/azure_ml_attach_compute.py b/ml_service/util/attach_compute.py similarity index 100% rename from ml_service/util/azure_ml_attach_compute.py rename to ml_service/util/attach_compute.py From d13f4703026442bed2228e431516b48754712899 Mon Sep 17 00:00:00 2001 From: Eugene Fedorenko Date: Mon, 12 Aug 2019 13:52:50 -0700 Subject: [PATCH 073/113] fix --- .pipelines/azdo-ci-build-train.yml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/.pipelines/azdo-ci-build-train.yml b/.pipelines/azdo-ci-build-train.yml index f05c0958..eab1a743 100644 --- a/.pipelines/azdo-ci-build-train.yml +++ b/.pipelines/azdo-ci-build-train.yml @@ -21,7 +21,7 @@ steps: - bash: | # Invoke the Python building and publishing a training pipeline - python3 $(Build.SourcesDirectory)/.pipelines/azdo-ci-build-train.py + python3 $(Build.SourcesDirectory)/ml_service/pipelines/build_train_pipeline.py failOnStderr: 'false' env: SP_APP_SECRET: '$(SP_APP_SECRET)' From 0abdb5d1cb9e29eaa59490a02bccc0b433ba0d1a Mon Sep 17 00:00:00 2001 From: Eugene Fedorenko Date: Mon, 12 Aug 2019 15:21:30 -0700 Subject: [PATCH 074/113] getting started --- docs/getting_started.md | 4 ---- 1 file changed, 4 deletions(-) diff --git a/docs/getting_started.md b/docs/getting_started.md index 2f0de306..2e7193b8 100644 --- a/docs/getting_started.md +++ b/docs/getting_started.md @@ -10,10 +10,6 @@ We use Azure DevOps for running our build(CI), retraining trigger and release (C If you already have Azure DevOps account, create a [new project](https://docs.microsoft.com/en-us/azure/devops/organizations/projects/create-project?view=azure-devops). -#### Enable Azure DevOps Preview -The steps below uses the latest DevOps features. Thus, please enable the feature **New YAML pipeline creation experience** by following the instructions [here](https://docs.microsoft.com/en-us/azure/devops/project/navigation/preview-features?view=azure-devops). - -**Note:** Make sure you have the right permissions in Azure DevOps to do so. ### 3. Create Service Principal to Login to Azure and create resources From a460ab0717f8592f2bd04c4d032c7df2f6214a6e Mon Sep 17 00:00:00 2001 From: Eugene Fedorenko Date: Mon, 12 Aug 2019 15:22:30 -0700 Subject: [PATCH 075/113] removed garbage --- .gitignore | 1 - 1 file changed, 1 deletion(-) diff --git a/.gitignore b/.gitignore index b327895b..3a5a8879 100644 --- a/.gitignore +++ b/.gitignore @@ -104,5 +104,4 @@ venv.bak/ # mypy .mypy_cache/ -aml_config/config.json .DS_Store From c298a61e50d8c8fe257b40714e88587ba6bf5a59 Mon Sep 17 00:00:00 2001 From: Eugene Fedorenko Date: Mon, 12 Aug 2019 15:25:59 -0700 Subject: [PATCH 076/113] removed extra line from gitignore --- .gitignore | 1 - 1 file changed, 1 deletion(-) diff --git a/.gitignore b/.gitignore index b327895b..3a5a8879 100644 --- a/.gitignore +++ b/.gitignore @@ -104,5 +104,4 @@ venv.bak/ # mypy .mypy_cache/ -aml_config/config.json .DS_Store From 033dbbf817c801760dc2e6db81af1599b129aa54 Mon Sep 17 00:00:00 2001 From: Eugene Fedorenko Date: Mon, 12 Aug 2019 17:03:07 -0700 Subject: [PATCH 077/113] getting started update --- docs/getting_started.md | 39 +++++++++++++++++++++------- docs/images/select-iac-pipeline.png | Bin 0 -> 72258 bytes 2 files changed, 29 insertions(+), 10 deletions(-) create mode 100644 docs/images/select-iac-pipeline.png diff --git a/docs/getting_started.md b/docs/getting_started.md index 2e7193b8..fd28df1a 100644 --- a/docs/getting_started.md +++ b/docs/getting_started.md @@ -11,17 +11,22 @@ We use Azure DevOps for running our build(CI), retraining trigger and release (C If you already have Azure DevOps account, create a [new project](https://docs.microsoft.com/en-us/azure/devops/organizations/projects/create-project?view=azure-devops). -### 3. Create Service Principal to Login to Azure and create resources +### 3. Create Service Principal to Login to Azure To create service principal, register an application entity in Azure Active Directory (Azure AD) and grant it the Contributor or Owner role of the subscription or the resource group where the web service belongs to. See [how to create service principal](https://docs.microsoft.com/en-us/azure/active-directory/develop/howto-create-service-principal-portal) and assign permissions to manage Azure resource. Please make note the following values after creating a service principal, we will need them in subsequent steps -- Azure subscription id (subscriptionid) -- Service principal username (spidentity)([application id](https://docs.microsoft.com/en-us/azure/active-directory/develop/howto-create-service-principal-portal#get-application-id-and-authentication-key)) +- Application (client) ID +- Directory (tenant) ID +- Application Secret + + **Note:** You must have sufficient permissions to register an application with your Azure AD tenant, and assign the application to a role in your Azure subscription. Contact your subscription adminstator if you don't have the permissions. Normally a subscription admin can create a Service principal and can provide you the details. + + +### 4. Create a Variable Group We make use of variable group inside Azure DevOps to store variables and their values that we want to make available across multiple pipelines. You can either store the values directly in [Azure DevOps](https://docs.microsoft.com/en-us/azure/devops/pipelines/library/variable-groups?view=azure-devops&tabs=designer#create-a-variable-group) or connect to an Azure Key Vault in your subscription. Please refer to the documentation [here](https://docs.microsoft.com/en-us/azure/devops/pipelines/library/variable-groups?view=azure-devops&tabs=designer#create-a-variable-group) to learn more about how to create a variable group and [link](https://docs.microsoft.com/en-us/azure/devops/pipelines/library/variable-groups?view=azure-devops&tabs=designer#use-a-variable-group) it to your pipeline. -Please name your variable group **``AzureKeyVaultSecrets``**, we are using this name within our build yaml file. +Please name your variable group **``devopsforai-aml-vg``** as we are using this name within our build yaml file. + +The varibale group should contain the following variables: -Up until now you shouls have +a table (name, description, value) + +Up until now you should have - Forked (or cloned) the repo - Created a devops account or use an existing one - Got service principal details and subscription id -- Set them as variable group within devops +- A variable group with all configuration values -We now have 3 pipelines that we would set up + + +### 5. Create resources + +The easiest way to create all required resources (Resource Group, ML Workspace, Container Registry, Storage Account, etc.) is to leverage an "Infrastructure as Code" [pipeline coming in this repository](../environment_setup/iac-create-environment.yml). This **IaC** pipeline takes care of all required resources basing on these [ARM templates](../environment_setup/arm-templates/cloud-environment.json) +In your DevOps project create a build pipeline from your forked **GitHub** repository +![build connnect step](./images/build-connect.png) +refering to an **Existing Azure Pipelines YAML file** +![configure step](./images/select-iac-pipeline.png) ### 5. Set up Build Pipeline 1. 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pipelines --- docs/getting_started.md | 2 +- environment_setup/iac-create-environment.yml | 12 +++++------- environment_setup/iac-remove-environment.yml | 10 ++++------ 3 files changed, 10 insertions(+), 14 deletions(-) diff --git a/docs/getting_started.md b/docs/getting_started.md index fd28df1a..35715dd9 100644 --- a/docs/getting_started.md +++ b/docs/getting_started.md @@ -72,7 +72,7 @@ The easiest way to create all required resources (Resource Group, ML Workspace, In your DevOps project create a build pipeline from your forked **GitHub** repository ![build connnect step](./images/build-connect.png) -refering to an **Existing Azure Pipelines YAML file** +Refer to an **Existing Azure Pipelines YAML file** ![configure step](./images/select-iac-pipeline.png) ### 5. Set up Build Pipeline diff --git a/environment_setup/iac-create-environment.yml b/environment_setup/iac-create-environment.yml index af2c2fcd..57e5a106 100644 --- a/environment_setup/iac-create-environment.yml +++ b/environment_setup/iac-create-environment.yml @@ -10,21 +10,19 @@ pool: vmImage: 'ubuntu-latest' variables: - baseName: $[coalesce(variables['baseNameOverride'], 'mlops')] - location: $[coalesce(variables['locationOverride'], 'centralus')] - azuresub: $[coalesce(variables['azuresubOverride'], 'AzureResourceConnection')] +- group: devopsforai-aml-vg steps: - task: AzureResourceGroupDeployment@2 inputs: - azureSubscription: $(azuresub) + azureSubscription: 'AzureResourceConnection' action: 'Create Or Update Resource Group' - resourceGroupName: '$(baseName)-AML-RG' - location: $(location) + resourceGroupName: '$(RESOURCE_GROUP)' + location: $(LOCATION) templateLocation: 'Linked artifact' csmFile: '$(Build.SourcesDirectory)/environment_setup/arm-templates/cloud-environment.json' - overrideParameters: '-baseName $(baseName)' + overrideParameters: '-baseName $(BASE_NAME)' deploymentMode: 'Incremental' displayName: 'Deploy MLOps resources to Azure' diff --git a/environment_setup/iac-remove-environment.yml b/environment_setup/iac-remove-environment.yml index 152efa59..67626223 100644 --- a/environment_setup/iac-remove-environment.yml +++ b/environment_setup/iac-remove-environment.yml @@ -10,18 +10,16 @@ pool: vmImage: 'ubuntu-latest' variables: - baseName: $[coalesce(variables['baseNameOverride'], 'mlops')] - location: $[coalesce(variables['locationOverride'], 'centralus')] - azuresub: $[coalesce(variables['azuresubOverride'], 'AzureResourceConnection')] +- group: devopsforai-aml-vg steps: - task: AzureResourceGroupDeployment@2 inputs: - azureSubscription: $(azuresub) + azureSubscription: 'AzureResourceConnection' action: 'DeleteRG' - resourceGroupName: '$(baseName)-AML-RG' - location: $(location) + resourceGroupName: '$(RESOURCE_GROUP)' + location: $(LOCATION) displayName: 'Delete resources in Azure' \ No newline at end of file From 5a1e994faf473bb4179263a363172b39d1bc92a5 Mon Sep 17 00:00:00 2001 From: Eugene Fedorenko Date: Mon, 12 Aug 2019 17:54:50 -0700 Subject: [PATCH 079/113] document update progress --- docs/getting_started.md | 18 +++++++++++++++++- docs/images/create-rm-service-connection.png | Bin 0 -> 116424 bytes docs/images/created-resources.png | Bin 0 -> 89397 bytes docs/images/run-iac-pipeline.png | Bin 0 -> 74750 bytes 4 files changed, 17 insertions(+), 1 deletion(-) create mode 100644 docs/images/create-rm-service-connection.png create mode 100644 docs/images/created-resources.png create mode 100644 docs/images/run-iac-pipeline.png diff --git a/docs/getting_started.md b/docs/getting_started.md index 35715dd9..7a457913 100644 --- a/docs/getting_started.md +++ b/docs/getting_started.md @@ -54,6 +54,10 @@ The varibale group should contain the following variables: a table (name, description, value) +Mark **SP_APP_SECRET** variable as a secret one. + +Make sure to select the **Allow access to all pipelines** checkbox in the variable group configuration. + Up until now you should have - Forked (or cloned) the repo - Created a devops account or use an existing one @@ -67,7 +71,9 @@ Up until now you should have ### 5. Create resources -The easiest way to create all required resources (Resource Group, ML Workspace, Container Registry, Storage Account, etc.) is to leverage an "Infrastructure as Code" [pipeline coming in this repository](../environment_setup/iac-create-environment.yml). This **IaC** pipeline takes care of all required resources basing on these [ARM templates](../environment_setup/arm-templates/cloud-environment.json) +The easiest way to create all required resources (Resource Group, ML Workspace, Container Registry, Storage Account, etc.) is to leverage an "Infrastructure as Code" [pipeline coming in this repository](../environment_setup/iac-create-environment.yml). This **IaC** pipeline takes care of all required resources basing on these [ARM templates](../environment_setup/arm-templates/cloud-environment.json). The pipeline requires an **Azure Resource Manager** service connection +![create service connection](./images/create-rm-service-connection.png) +Give the connection **``AzureResourceCOnnection``** as it is referred by the pipeline definition. In your DevOps project create a build pipeline from your forked **GitHub** repository ![build connnect step](./images/build-connect.png) @@ -75,6 +81,16 @@ In your DevOps project create a build pipeline from your forked **GitHub** repos Refer to an **Existing Azure Pipelines YAML file** ![configure step](./images/select-iac-pipeline.png) +Having done that, run the pipeline +![iac run](./images/run-iac-pipeline.png) + +and check out created resources in the **Azure Portal** +![created resources](./images/created resources.png) + + + + + ### 5. Set up Build Pipeline 1. Select your devops organization and project by clicking dev.azure.com 2. 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changed, 3 insertions(+), 3 deletions(-) diff --git a/docs/getting_started.md b/docs/getting_started.md index 7a457913..fa21fc06 100644 --- a/docs/getting_started.md +++ b/docs/getting_started.md @@ -73,7 +73,7 @@ Up until now you should have The easiest way to create all required resources (Resource Group, ML Workspace, Container Registry, Storage Account, etc.) is to leverage an "Infrastructure as Code" [pipeline coming in this repository](../environment_setup/iac-create-environment.yml). This **IaC** pipeline takes care of all required resources basing on these [ARM templates](../environment_setup/arm-templates/cloud-environment.json). The pipeline requires an **Azure Resource Manager** service connection ![create service connection](./images/create-rm-service-connection.png) -Give the connection **``AzureResourceCOnnection``** as it is referred by the pipeline definition. +Give the connection name **``AzureResourceConnection``** as it is referred by the pipeline definition. In your DevOps project create a build pipeline from your forked **GitHub** repository ![build connnect step](./images/build-connect.png) @@ -84,8 +84,8 @@ Refer to an **Existing Azure Pipelines YAML file** Having done that, run the pipeline ![iac run](./images/run-iac-pipeline.png) -and check out created resources in the **Azure Portal** -![created resources](./images/created resources.png) +Check out created resources in the [Azure Portal](portal.azure.com) +![created resources](./images/created_resources.png) diff --git a/docs/images/create-rm-service-connection.png b/docs/images/create-rm-service-connection.png index 70a6499f4e3c2c2f3a527c73f4e3a78a392380d9..629d3c2a1e91109ef6ba5135d707b1bbf61356b8 100644 GIT binary patch delta 109712 zcmYhiby!n>-2V^Kf`lN=08v6Zq)QM`8d16%=^lBcRZ6vxpXna3LR94NJY5p5=|~@R zGWr4aOa+(eGmReQ-ygJpKX)A6n)|7kdl^={m>SRDqotvFYhdn0Mfu`w+3V!h5gfce z-I#B87{pj$YQWWM@EWgZLvHr9ySq2`m6GSAdaC1MH5UW~?G-niFS=9`kkXcU!3NLXG(kW2tZ?jka^R#Dr6;VwH8g*~Kr8*e9! 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z^L5w#i_2q>XMO*zmrR^@DnGcY<12=6#H0CFM?LO&IBS=-QrB0RMh1o+g8no+e8r`G z8S+~!FN?RwA$U6No-k*9W6CthjIqtEr|<3RaT2F-LarzTZ{hFrd8T2OWdwVBO&`s; zw;F*xPRoOctcR!(-)-tD@ bo7Ohu1NzR0^vehMo51C0k2*=S^}GEaCepo8 From 67fd322306fc8c41eba38e5a418111cdbc4421ee Mon Sep 17 00:00:00 2001 From: Eugene Fedorenko Date: Mon, 12 Aug 2019 18:07:21 -0700 Subject: [PATCH 081/113] update document progress --- docs/getting_started.md | 6 +++++- docs/images/build-connect.png | Bin 172824 -> 219240 bytes docs/images/created-resources.png | Bin 89397 -> 74797 bytes docs/images/run-iac-pipeline.png | Bin 74750 -> 76748 bytes docs/images/select-iac-pipeline.png | Bin 72258 -> 69549 bytes 5 files changed, 5 insertions(+), 1 deletion(-) diff --git a/docs/getting_started.md b/docs/getting_started.md index fa21fc06..1e6f4c99 100644 --- a/docs/getting_started.md +++ b/docs/getting_started.md @@ -72,20 +72,24 @@ Up until now you should have ### 5. Create resources The easiest way to create all required resources (Resource Group, ML Workspace, Container Registry, Storage Account, etc.) is to leverage an "Infrastructure as Code" [pipeline coming in this repository](../environment_setup/iac-create-environment.yml). This **IaC** pipeline takes care of all required resources basing on these [ARM templates](../environment_setup/arm-templates/cloud-environment.json). The pipeline requires an **Azure Resource Manager** service connection + ![create service connection](./images/create-rm-service-connection.png) + Give the connection name **``AzureResourceConnection``** as it is referred by the pipeline definition. In your DevOps project create a build pipeline from your forked **GitHub** repository + ![build connnect step](./images/build-connect.png) Refer to an **Existing Azure Pipelines YAML file** + ![configure step](./images/select-iac-pipeline.png) Having done that, run the pipeline ![iac run](./images/run-iac-pipeline.png) Check out created resources in the [Azure Portal](portal.azure.com) -![created resources](./images/created_resources.png) +![created resources](./images/created-resources.png) diff --git a/docs/images/build-connect.png b/docs/images/build-connect.png index f5d9d61acc761eac588d1affdfcef43adfa8980e..5218aaeab98969778eebd3f8163bffea5a604b5a 100644 GIT binary patch literal 219240 zcmeFYg;!k9vM@SGa2N&>7~Cbn13?CNw~*jYa0qU}b#Ow^gaE-IxCD0wCpcknhv4q^ zCg>guZQ>gtjRH5FN0EK)200DvnmC-oWtKn(x@Q06hv z5MKl&+qD4z9C>R=Ni}&%NoqA`2McREa{xdtB1sEfTce*SL+`b`RUn2OW=q8DTt&<* zY5b2b;284MS+I}zQhV%!FY4VvNMwyKvVZFWbXazDi8~H-DI*J+cTGFO2GX8tPv0+k 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docs/getting_started.md | 27 ++++++++++++++++++-- docs/images/ci-build-logs.png | Bin 0 -> 80696 bytes docs/images/ci-build-pipeline-configure.png | Bin 0 -> 69008 bytes docs/images/training-pipeline.png | Bin 0 -> 69220 bytes 4 files changed, 25 insertions(+), 2 deletions(-) create mode 100644 docs/images/ci-build-logs.png create mode 100644 docs/images/ci-build-pipeline-configure.png create mode 100644 docs/images/training-pipeline.png diff --git a/docs/getting_started.md b/docs/getting_started.md index 1e6f4c99..a958637d 100644 --- a/docs/getting_started.md +++ b/docs/getting_started.md @@ -91,11 +91,34 @@ Having done that, run the pipeline Check out created resources in the [Azure Portal](portal.azure.com) ![created resources](./images/created-resources.png) +Alternatively, you can also use a [cleaning pipeline](../environment_setup/iac-create-environment.yml) that removes resources ctreated for this project or you can just delete a resource group in the [Azure Portal](portal.azure.com). +### 6. Set up Build Pipeline +In your [Azure DevOps](https://dev.azure.com) project create and run a new build pipeline refereing to **azdo-ci-build-train.yml** pipeline in yuor forked **GitHub** repository + +![configure ci build pipeline](./images/ci-build-pipeline-configure.png) + +Once the pipline is finished, explore the execution logs + +![ci build logs](./images/ci-build-logs.png) + +and checkout a published training pipeline in the **mlops-AML-WS** workspace in [Azure Portal](https://ms.portal.azure.com/) + +![training pipeline](./images/training-pipeline.png) + +Rename the pipeline as **ci-build**. + +Great, you now have the build pipeline setup, you can either manually trigger it or it gets automatically triggered everytime there is a change in the master branch. The pipeline performs linitnig, unit testing, builds and publishes an **ML Training Pipeline** in an **ML Workspace** + +### 6. Train the Model + +The next step is to invoke the training pipeline created in the previous step. + + +The pipeline is triggered whenever a new training pipeline is published by the builder pipeline. It can also be triggered manually or configured to run on a scheduled basis. -### 5. Set up Build Pipeline 1. Select your devops organization and project by clicking dev.azure.com 2. Once you are in the right devops project, click Pipelines on the left hand menu and select Builds 3. Click **New pipeline** to create new pipeline @@ -115,7 +138,7 @@ Check out created resources in the [Azure Portal](portal.azure.com) 8. Your build run would look similar to the following image ![select repo](./images/build-run.png) -Great, you now have the build pipeline setup, you can either manually trigger it or it gets automatically triggered everytime there is a change in the master branch. + **Note:** The build pipeline will perform basic test on the code and provision infrastructure on azure. 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-flake8_formatter_junit_xml \ No newline at end of file +flake8_formatter_junit_xml +azure-cli==2.0.46 \ No newline at end of file From 5f300f48897e4e367f8eb6b66e36a8aeabb78eb2 Mon Sep 17 00:00:00 2001 From: Eugene Fedorenko Date: Tue, 13 Aug 2019 15:30:51 -0700 Subject: [PATCH 085/113] document update progress --- docs/getting_started.md | 8 +++++++- docs/images/artifact-invoke-pipeline.png | Bin 0 -> 66759 bytes docs/images/invoke-training-pipeline.png | Bin 0 -> 56762 bytes ml_service/pipelines/run_train_pipeline.py | 9 +++++++++ 4 files changed, 16 insertions(+), 1 deletion(-) create mode 100644 docs/images/artifact-invoke-pipeline.png create mode 100644 docs/images/invoke-training-pipeline.png diff --git a/docs/getting_started.md b/docs/getting_started.md index a958637d..08758899 100644 --- a/docs/getting_started.md +++ b/docs/getting_started.md @@ -114,7 +114,13 @@ Great, you now have the build pipeline setup, you can either manually trigger it ### 6. Train the Model -The next step is to invoke the training pipeline created in the previous step. +The next step is to invoke the training pipeline created in the previous step. It can be done with a **Release Pipeline**: + +![invoke training pipeline](./images/invoke-training-pipeline.png) + +An artifact of this pipeline will be the result of the build pipeline **ci-buid** + +![artifact invoke pipeline](./images/artifact-invoke-pipeline.png) The pipeline is triggered whenever a new training pipeline is published by the builder pipeline. 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zAlvw`s%gUBGr=^|?Uj171;r#M__m*&&S;?L+L-y+!gz4@B#q)Bx#h*5=d&(4Qj}1# zo^fVB3P=$}6g8XyAO5fzZs^+DI8+0#>OpN-=Ct)g?XB@k>W_+BskoJDIILvXpk^>G zWz%C zhF2>6l)a$+!+AW{kV~$o?>2t~o2EO=ZTJD=`lM{`iY}p-sNwm(sv}T_{}D<)ad1nN zqDiQ5S1iiE52lTwLJly~_lYGv431B3ns; zy&n$y3DTq*hm@Yn58tuMMYuc^rRvX0@RK$FMyT^4ic#PwPNgUMbsj8p$2eDOomW9I)=Dltu%qlO^jrPgQj#LL(6m&_4|I?0c6y4! zpFK*jv{#0Mj8XVVCzeikDlE$_hSkms|#&+EFeR=1otja!B`=-~}~=FZ-PnF;EyLLg~u zL2ftz*BivlelsUJ^p{8Dw=|xkEo1>*U6GytnXLI%xPwn+WY+MrN|K zq-9!Nxw`UA6k;mShSP2`%yYA%YFQ@HQJN)Bbnp{+c@WqM)y3QrBnu+h#k4x z_O|f*<@L5QUS{|BSD-z%52(QDT76=t3R9^=C$j$BNj3OMXpZ5zPX(Fvqz{NZ*-SG; zfVEr2YEOSPg~y8%>~zMF>!nxT3Z2v*C$FcQ;=tM!-2vin6ap-2{{PSYU;lUC{-Fmf WTOUUxNKa^h&kbE;ofp@T(f Date: Tue, 13 Aug 2019 15:37:39 -0700 Subject: [PATCH 086/113] document update progress --- ml_service/pipelines/run_train_pipeline.py | 1 - 1 file changed, 1 deletion(-) diff --git a/ml_service/pipelines/run_train_pipeline.py b/ml_service/pipelines/run_train_pipeline.py index 4e8f4636..317ffec5 100644 --- a/ml_service/pipelines/run_train_pipeline.py +++ b/ml_service/pipelines/run_train_pipeline.py @@ -21,7 +21,6 @@ # secret = KEY, # tenant = TENANT_ID # ) -# az login --service-principal -u $(SP_APP_ID) -p $(SP_APP_SECRET) --tenant $(TENANT_ID) cli_auth = AzureCliAuthentication() token = cli_auth.get_authentication_header() From 4eca7b118b897716032e61d6dd01ce2ad992bab8 Mon Sep 17 00:00:00 2001 From: Eugene Fedorenko Date: Wed, 14 Aug 2019 09:40:12 -0700 Subject: [PATCH 087/113] document update progress --- docs/getting_started.md | 188 ++++------------------ docs/images/agent-specificatioin.png | Bin 0 -> 59869 bytes docs/images/create-release.png | Bin 0 -> 64802 bytes docs/images/deploy-aci.png | Bin 0 -> 106637 bytes docs/images/deploy-aks.png | Bin 0 -> 61196 bytes docs/images/deploy-model.png | Bin 0 -> 55899 bytes docs/images/model-artifact.png | Bin 199413 -> 86949 bytes docs/images/retrain-pipeline-vg.png | Bin 0 -> 27967 bytes docs/images/running-training-pipeline.png | Bin 0 -> 106087 bytes docs/images/trained-model.png | Bin 0 -> 61705 bytes docs/images/workspace-connection.png | Bin 0 -> 84836 bytes 11 files changed, 35 insertions(+), 153 deletions(-) create mode 100644 docs/images/agent-specificatioin.png create mode 100644 docs/images/create-release.png create mode 100644 docs/images/deploy-aci.png create mode 100644 docs/images/deploy-aks.png create mode 100644 docs/images/deploy-model.png create mode 100644 docs/images/retrain-pipeline-vg.png create mode 100644 docs/images/running-training-pipeline.png create mode 100644 docs/images/trained-model.png create mode 100644 docs/images/workspace-connection.png diff --git a/docs/getting_started.md b/docs/getting_started.md index 08758899..96afd9be 100644 --- a/docs/getting_started.md +++ b/docs/getting_started.md @@ -19,30 +19,9 @@ Please make note the following values after creating a service principal, we wil - Directory (tenant) ID - Application Secret - **Note:** You must have sufficient permissions to register an application with your Azure AD tenant, and assign the application to a role in your Azure subscription. Contact your subscription adminstator if you don't have the permissions. Normally a subscription admin can create a Service principal and can provide you the details. - ### 4. Create a Variable Group @@ -64,11 +43,6 @@ Up until now you should have - Got service principal details and subscription id - A variable group with all configuration values - - ### 5. Create resources The easiest way to create all required resources (Resource Group, ML Workspace, Container Registry, Storage Account, etc.) is to leverage an "Infrastructure as Code" [pipeline coming in this repository](../environment_setup/iac-create-environment.yml). This **IaC** pipeline takes care of all required resources basing on these [ARM templates](../environment_setup/arm-templates/cloud-environment.json). The pipeline requires an **Azure Resource Manager** service connection @@ -122,163 +96,71 @@ An artifact of this pipeline will be the result of the build pipeline **ci-buid* ![artifact invoke pipeline](./images/artifact-invoke-pipeline.png) +Configure a pipeline to see values from the previously defined variable group **devopsforai-aml-vg** -The pipeline is triggered whenever a new training pipeline is published by the builder pipeline. It can also be triggered manually or configured to run on a scheduled basis. - -1. Select your devops organization and project by clicking dev.azure.com -2. Once you are in the right devops project, click Pipelines on the left hand menu and select Builds -3. Click **New pipeline** to create new pipeline - ![new build pipeline](./images/new-build-pipeline1.png) -4. On the Connect option page, select **GitHub** - ![build connnect step](./images/build-connect.png) - -5. On the Select option page, select the GitHub repository where you forked the code. -![select repo](./images/build-selectrepo.png) - -6. Authorize Azure Pipelines to access your git account -![select repo](./images/Install_Azure_pipeline.png) - -7. Since the repository contains azure-pipelines.yml at the root level, Azure DevOps recognizes it and auto imports it. Click **Run** and this will start the build pipeline. -![select repo](./images/build-createpipeline1.png) - -8. Your build run would look similar to the following image -![select repo](./images/build-run.png) - - +![retrain pipeline vg](./images/retrain-pipeline-vg.png) +Add an empty stage with name **``Invoke Training Pipeline``** and make sure that the **Agent Specification** is **``ubuntu-16.04``** +![agent specification](./images/agent-specification.png) -**Note:** The build pipeline will perform basic test on the code and provision infrastructure on azure. This can take around 10 mins to complete. +Add a command line step **``Invoke Training Pipeline``** with the following script -### 6. Set up Retraining trigger release pipeline +```bash +docker run -v $(System.DefaultWorkingDirectory)/_ci-build/mlops-pipelines/ml_service/pipelines:/pipelines -w=/pipelines -e MODEL_NAME=$MODEL_NAME -e EXPERIMENT_NAME=$EXPERIMENT_NAME microsoft/mlopspython python run_train_pipeline.py +``` -**Note:** For setting up release pipelines, first download the [release-pipelines](../release-pipelines) to your local filesystem so you can import it. +The pipeline is triggered whenever a new training pipeline is published by the builder pipeline. It can also be triggered manually or configured to run on a scheduled basis. Create a new release to trigger the pipeline manually -**Also Note:** If this is the first time you are creating a release pipeline, you would see the following option, click on **New Pipeline** -![import release pipeline](./images/release-new-pipeline.png) +![create release](./images/create-release.png) -To enable the option to **Import release pipeline**, we must have atleast one release pipeline so let's create one with an empty job. -![import release pipeline](./images/release-empty-job.png) +Once the pipeline is completed, check out in the **ML Workspace** that the training pipeline is running -On the next screen, click on **Save** and then click **Ok** to save the empty release pipeline. -![import release pipeline](./images/release-save-empty.png) +![running training pipeline](./images/running-training-pipeline.png) -**Steps** +The training pipeline will train, evaluate and register a new model. Wait intil it is fininshed and make sure there is a new model in the **ML Workspace** -1. Select the Release tab from the menu on the left, then click the New dropdown on top and click on **Import Release pipeline** -![import release pipeline](./images/release-import.png) +![trained model](./images/trained-model.png) -1. On the next screen, navigate to **release-pipelines** folder and select **retrainingtrigger.json** pipeline file, click import. You should now see the following screen. Under Stages click on the Retrain stage, where it shows the red error sign. -![release retraining triggger](./images/release-retrainingtrigger.png) +Good! Now we have a trained model. - Click on agent job and then from the drop down for Agent Pool on the right side select **Hosted Ubuntu 1604** agent to execute your run and click **Save** button on top right. -![release retraining agent](./images/release-retrainingagent.png) - -1. We would now link the variable group we created earlier to this release pipeline. To do so click on the **Variables** tab, then click on **Variable** groups and then select **Link variable group** and select the variable group that we created in previous step and click **Link** followed by **Save** button. -![release retraining artifact](./images/release-link-vg.png) -1. We want the retraining pipeline to be triggered every time build pipeline is complete. To create this dependency, we will link the artifact from build pipeline as a trigger for retraining trigger release pipeline. To do so, click on the **pipeline** tab and then select **Add an artifact** option under Artifacts. -![release pipeline view](./images/release-retrainingpipeline.png) - -1. This will open up a pop up window, on this screen: - - for source type, select **Build** - - for project, select your project in Azure DevOps that you created in previous steps. - - For Source select the source build pipeline. If you have forked the git repo, the build pipeline may named ``yourgitusername.MLOpsPython`` - - In the Source alias, replace the auto-populated value with - **``DevOpsForAI``** - - Field **Default version** will get auto populated **Latest**, you can leave them as it is. - - Click on **Add**, and then **Save** the pipeline - ![release retraining artifact](./images/release-retrainingartifact.png) - -1. Artifact is now added for retraining trigger pipeline, hit the **save** button on top right and then click **ok**. - -1. To trigger this pipeline every time build pipeline executes, click on the lighting sign to enable the **Continous Deployment Trigger**, click **Save**. - ![release retraining artifact](./images/release-retrainingtrigger1.png) - -2. If you want to run this pipeline on a schedule, you can set one by clicking on **Schedule set** in Artifacts section. -![release retraining artifact](./images/release-retrainingartifactsuccess.png) - -1. For the first time, we will manually trigger this pipeline. - - Click Releases option on the left hand side and navigate to the release pipeline you just created. - ![release retraining artifact](./images/release-createarelease.png) - - Click **Create Release** - ![release create ](./images/release-create.png) - - On the next screen click on **Create** button, this creates a manual release for you. - - **Note**: This release pipeline will call the published AML pipeline. The AML pipeline will train the model and package it into image. It will take around 10 mins to complete. The next steps need this pipeline to complete successfully. At this point, you can go to the Azure Portal AML WOrkspace resource created inside resource group "DevOps_AzureML_Demo" and click on the **Pipeline** tab to see the running pipeline. - -### 7. Set up release (Deployment) pipeline +### 6. Train the Model -**Note:** For setting up release pipelines, first download the [release-pipelines](../release-pipelines) to your local filesystem so you can import it. +The final step is to deploy the model across environments with a release pipeline. There will be a **``QA``** environment running on [Azure Container Instances](https://azure.microsoft.com/en-us/services/container-instances/) and a **``Prod``** environment running on [Azure Kubernetes Service](https://azure.microsoft.com/en-us/services/kubernetes-service). -**Also Note:** Before creating this pipeline, make sure that the build pipeline, retraining trigger release pipeline and AML retraining pipeline have been executed, as they will be creating resources during their run like docker images that we will deploy as part of this pipeline. So it is important for them to have successful runs before the setup here. +![deploy model](./images/deploy-model.png) -Let's set up the release deployment pipeline now. -1. As done in previous step, Select the Release tab from the menu on the left, then click the New dropdown on top and click on **Import Release pipeline** -![import release pipeline](./images/release-import.png) -1. On the next screen, navigate to **release-pipelines** folder and select **releasedeployment.json** pipeline file, click import. You should now see the following screen. Under Stages click on the QA environment's **view stage task", where it shows the red error sign. -![release retraining triggger](./images/release-deployment.png) +This pipeline leverages the **Azure Machine Learning** extension that should be installed in your organization from the [marketplace](https://marketplace.visualstudio.com/items?itemName=ms-air-aiagility.vss-services-azureml) - Click on agent job and then from the drop down for Agent Pool on the right side select **Hosted Ubuntu 1604** agent to execute your run and click **Save** button on top right. -![release retraining agent](./images/release-deploymentqaagent.png) +The pipeline consumes two artifacts: the result of the **Build Pipeline** as it contains configuration files and the **model** trained and registered by the ML training pipeline. - Follow the same steps for **Prod Environment** and select **Hosted Ubuntu 1604** for agent pool and save the pipeline. - ![release retraining agent](./images/release-deploymentprodagent.png) +Configuration of a code **``_ci-build``** artifact is similar to what we did in the previous chapter. -1. We would now link the variable group we created earlier to this release pipeline. To do so click on the **Variables** tab, then click on **Variable** groups and then select **Link variable group** and select the variable group that we created in previous step and click **Link** followed by **Save** button. -![release retraining artifact](./images/release-link-vg.png) +In order to configure a model artifact there should be a service connection to **``mlops-AML-WS``** workspace. -1. We now need to add artifact that will trigger this pipeline. We will add two artifacts: - - Build pipeline output as artifact since that contains our configuration and code files that we require in this pipeline. - - ACR artifact to trigger this pipeline everytime there is a new image that gets published to Azure container registry (ACR) as part of retraining pipeline. +![workspace connection](./images/workspace-connection.png) - Here are the steps to add build output as artifact +Add an artifact to the pipeline and select **AzureML Model Artifact** source type. Select the **Service Endpoint** and **Model Names** from the drop down lists - - Click on pipeline tab to go back to pipeline view and click **Add an artifact**. This will open a pop up window - - for source type, select **Build** - - for project, select your project in Azure DevOps that you created in previous steps. - - For Source select the source build pipeline. If you have forked the git repo, the build pipeline may named ``yourgitusername.DevOpsForAI`` - - In the Source alias, replace the auto-populated value with - **``DevOpsForAI``** - - Field **Devault version** will get auto populated **Latest**, you can leave them as it is. - - Click on **Add**, and then **Save** the pipeline - ![release retraining artifact](./images/release-retrainingartifact.png) +![model artifact](./images/model-artifact.png) - **Here are the steps to add [Azure ML Model as an artifact](https://marketplace.visualstudio.com/items?itemName=ms-air-aiagility.vss-services-azureml)** +Create a stage **``QA (ACI)``** and add a single task to the job **Azure ML Model Deploy**. Specify task parameters as it is shown below +![deploy aci](./images/deploy-aci.png) - - Install the Azure Machine Learning extension for your DevOps organization from [here](https://marketplace.visualstudio.com/items?itemName=ms-air-aiagility.vss-services-azureml). You need to have admin rights to install it. +In a similar way create a stage **``Prod (AKS)``** and add a single task to the job **Azure ML Model Deploy**. Specify task parameters as it is shown below - - Create Service Connection - 1. Go to your DevOps project and click on Project settings on bottom left corner - 2. Under Project Settings -> Pipelines, click on Service connections, click on "New service connection" and select Azure Resource Manager - ![release retraining agent](./images/service-connection.png) - - 3. Provide following info and click Ok once done: - ![release retraining agent](./images/service-connection-add.png) - - - - Click on pipeline tab to go back to pipeline view and click **Add an artifact**. This will open a pop up window - - For Source type, click on **more artifact types** dropdown and select **AzureML Model Artifact** - - For **Service Endpoint**, select an existing endpoint **MLOpsPython**, if you don't see anything in the dropdown, click on **Manage** and [create new **Azure Resource Manager**](https://docs.microsoft.com/en-us/azure/devops/pipelines/library/service-endpoints?view=azure-devops#create-a-service-connection) service connection for your subscription. - ![release retraining agent](./images/model-artifact.png) - **Note:** You must have sufficient privileges to create a service connection, if not contact your subscription adminstrator. - - For Model Names, select **sklearn_regression_model.pkl**, this is the name of the newly trained model and if the previous pipelines executed properly you will see this model name in the drop down. - - For Default version, keep it to **Latest version** - - For Source alias, keep the default generated name. - - Click Add - - Click on lighting sign to enable the **Continous Deployment Trigger**, click **Save**. - ![release retraining artifact](./images/model-artifact-cd-trigger.png) +![deploy aks](./images/deploy-aks.png) -1. We now have QA environment continously deployed each time there is a new ml model registered in AML Model Management. You can select pre-deployment conditions for prod environment, normally you don't want it to be auto deployed, so select manual only trigger here. +Note! Creating of a Kubernetes cluster on AKS is out of scope of this tutorial, so you should take care of it on your own. - ![release retraining artifact](./images/release-deploymentprodtrigger.png) +Save the pipeline and craete a release for it to trigger the pipeline manually. Once it's finished, check out deployments in the **``mlops-AML-WS``** workspace. - To deploy a release manually, follow the document [here](https://docs.microsoft.com/en-us/azure/devops/pipelines/get-started-designer?view=azure-devops&tabs=new-nav#deploy-a-release) Congratulations, you now have three pipelines set up end to end. - - Build pipeline: triggered on code change to master branch on GitHub. - - Release Trigger pipeline: triggered on build pipeline execution and registers a new ML model to AML Model Management if better than previous one. - - Release Deployment pipeline: QA environment is auto triggered when there is a new model. - Prod is manual only and user decides when to release to this environment. + - Build pipeline: triggered on code change to master branch on GitHub, performs linting, unit testing and publishing a trainig pipeline + - Release Trigger pipeline: runs a published training pipeline to trian, evaluate and register a model + - Release Deployment pipeline: 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z0i3Oj(C0t9J?JonR=0xc3{;x6cQ95*V0+j@oClXI*fJ4w%`boT8oW%fuR1jH zu~O&zxPw&n5QbRFl#lIn%Oj*6V3KA=+Vntzn-D^Zu(~N1othK#X}JB}Nryh3l}~=X ztdXj!@3}kv`=s%YBy7j2mUVpf Date: Wed, 14 Aug 2019 14:54:53 -0700 Subject: [PATCH 099/113] Update README.md --- README.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/README.md b/README.md index af833f4a..58077409 100644 --- a/README.md +++ b/README.md @@ -31,7 +31,7 @@ This reference architecture shows how to implement continuous integration (CI), ### Train Model 1. Data Scientist writes/updates the code and push it to git repo. This triggers the Azure DevOps build pipeline (continuous integration). -2. Once the Azure DevOps build pipeline is triggered, it performs code quality checks, data sanity tests, unit tests, builds a [Azure ML Pipeline](https://docs.microsoft.com/en-us/azure/machine-learning/service/concept-ml-pipelines) and publishes it in an [Azure ML Service Workspace](https://docs.microsoft.com/en-us/azure/machine-learning/service/concept-azure-machine-learning-architecture#workspace). +2. Once the Azure DevOps build pipeline is triggered, it performs code quality checks, data sanity tests, unit tests, builds an [Azure ML Pipeline](https://docs.microsoft.com/en-us/azure/machine-learning/service/concept-ml-pipelines) and publishes it in an [Azure ML Service Workspace](https://docs.microsoft.com/en-us/azure/machine-learning/service/concept-azure-machine-learning-architecture#workspace). 3. The [Azure ML Pipeline](https://docs.microsoft.com/en-us/azure/machine-learning/service/concept-ml-pipelines) is triggered once the Azure DevOps build pipeline completes. All the tasks in this pipeline runs on Azure ML Compute. Following are the tasks in this pipeline: - **Train Model** task executes model training script on Azure ML Compute. It outputs a [model](https://docs.microsoft.com/en-us/azure/machine-learning/service/concept-azure-machine-learning-architecture#model) file which is stored in the [run history](https://docs.microsoft.com/en-us/azure/machine-learning/service/concept-azure-machine-learning-architecture#run). From 5897a3157b75389c73c41f7a2731a3bc561782ae Mon Sep 17 00:00:00 2001 From: Eugene Fedorenko Date: Wed, 14 Aug 2019 14:59:59 -0700 Subject: [PATCH 100/113] readme update --- README.md | 2 +- docs/images/main-diagram.png | Bin 307433 -> 0 bytes docs/images/main-flow.png | Bin 0 -> 185583 bytes 3 files changed, 1 insertion(+), 1 deletion(-) delete mode 100644 docs/images/main-diagram.png create mode 100644 docs/images/main-flow.png diff --git a/README.md b/README.md index af833f4a..1b1f34ff 100644 --- a/README.md +++ b/README.md @@ -24,7 +24,7 @@ To deploy this solution in your subscription, follow the manual instructions in This reference architecture shows how to implement continuous integration (CI), continuous delivery (CD), and retraining pipeline for an AI application using Azure DevOps and Azure Machine Learning. The solution is built on the scikit-learn diabetes dataset but can be easily adapted for any AI scenario and other popular build systems such as Jenkins and Travis. -![Architecture](/docs/images/main-diagram.png) +![Architecture](/docs/images/main-flow.png) ## Architecture Flow diff --git a/docs/images/main-diagram.png b/docs/images/main-diagram.png deleted file mode 100644 index 97aecaaac657de1ce48bd3bfaba4c1961dd4a556..0000000000000000000000000000000000000000 GIT binary patch literal 0 HcmV?d00001 literal 307433 zcmeEucUY6z*Dat3f+7|`rCJc_iqfkBHVmQ=kS<*agx-4-K@k)i9RxuVLQMz|ibzwc z7ziaaLFo``D52bw(V1_??|#m`|J;A>Z=OeG2+8}t`|Pv#+H0*tq?YE@{Y=N1XlQ8m zU%#eyhlYkBg@$I26XPE6owt0G=V)m5-LO?v)w-^#%BSVxXl-k6MMHBf@`WD5UF}co zDTa5h-w)Qx3>#Dv{PH&J^GU{QZ1!QNW3|k0GM@Bc*Qf6mJDHX@fq3{Rk3JUjCeQu$ z%vSotrl#_{1?h`t=m}k<%GJsxe^*lKh4Ia7%el%6G!vbRnO_uiID-7H2aBALcrJNf zG+BL$?&#-Tr&VbB6snAxp2Wn^YCV|Sc`n^e`=-Lw8S3IMzhkO?i|_dot;)!Wwj&?c 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zHh=VZ7#sKJu>_CU&GA4==G8P#KEt!rIB7H4YJ;eJ- zniEvs*z&>+u`f|vv#BbgKGSMqaLtwKh5sxk2hu10`*ZlRF$I6r7`|3PpH26C>Qk)K zRi=LDv7NYOcA_Cn|A0Ppd{dB9tI*BS;1k(Gwq~>Q@vu1DfQKQkp}vtIKIe9JtIt53 z=JbcO?$`mth|#+KyaUsHj8qQ6l^u^!LJ0)aH7{lW3!ADG^JiZ953$Uo3%rbbV prCMA&I0t7xL;mki& Date: Wed, 14 Aug 2019 16:06:40 -0700 Subject: [PATCH 101/113] update document progress --- docs/code_description.md | 64 +++++++++++++--------------------------- 1 file changed, 21 insertions(+), 43 deletions(-) diff --git a/docs/code_description.md b/docs/code_description.md index 45fb7bb7..efda15ca 100644 --- a/docs/code_description.md +++ b/docs/code_description.md @@ -2,59 +2,37 @@ ### Environment Setup -- requirements.txt : It consist of list of python packages which are needed by the train.py to run successfully on host agent (locally). +- environment_setup/requirements.txt : It consist of list of python packages which are needed by the train.py to run successfully on host agent (locally). -- install_requirements.sh : This script prepare the python environment i.e. install the Azure ML SDK and the packages specified in requirements.txt +- environment_setup/install_requirements.sh : This script prepare the python environment i.e. install the Azure ML SDK and the packages specified in requirements.txt -### Config Files -All the scripts inside the ./aml_config are config files. These are the files where you need to provide details about the subscription, resource group, workspace, conda dependencies, remote vm, AKS etc. +- environment_setup/iac-*.yml, arm-templates: Infrastructure as Code piplines to create and delete required resources along with corresponding arm-templates. -- config.json : This is a mandatory config file. Provide the subscription id, resource group name, workspace name and location where you want to create Azure ML services workspace. If you have already created the workspace, provide the existing workspace details in here. +- environment_setup/Dockerfile : Dockerfile of a building agent (microsoft/mlopspython) containing Python 3.6 and all required packages. -- conda_dependencies.yml : This is a mandatory file. This files contains the list of dependencies which are needed by the training/scoring script to run. This file is used to prepare environment for the local run(user managed/system managed) and docker run(local/remote). +- environment_setup/docker-image-pipeline.yml : An AzDo pipeline building and pushing microsoft/mlopspython image. -- security_config.json : This file contains the credentials to the remove vm where we want to train the model. This config is used by the script 02-AttachTrainingVM.py to attach remote vm as a compute to the workspace. Attaching remote vm to workspace is one time operation. It is recommended not to publish this file with credentials populated in it. You can put the credentials, run the 02-AttachTrainingVM.py manually and clear the credentials before pushing it to git. +### Pipelines -- aks_webservice.json : This is an optional config. If you already have an AKS attached to your workspace, then provide the details in this file. If not, you do not have to check in this file to git. +- .pipelines/azdo-base-pipeline.yml : a pipeline template used by ci-build-train pipeline and pr-build-train pipelines. It contains steps performig linting, data and unit testing. +- .pipelines/azdo-ci-build-train.yml : a pipeline triggered when the code is merged into **master**. It profrorms linting, data integrity testing, unit testing, building and publishing an ML pipeline. +- .pipelines/azdo-pr-build-train.yml : a pipeline triggered when a **pull request** to the **master** branch is created. It profrorms linting, data integrity testing and unit testing only. -### Build Pipeline Scripts +### ML Services -The script under ./aml_service are used in build pipeline. All the scripts starting with 0 are the one time run scripts. These are the scripts which need to be run only once. There is no harm of running these scripts every time in build pipeline. +- ml_service/pipelines/build_train_pipeline.py : builds and publishes an ML training pipeline. +- ml_service/pipelines/run_train_pipeline.py : invokes a published ML training pipeline via REST API. +- ml_service/util : contains common utility functions used to build and publish an ML training pipeline. -- 00-WorkSpace.py : This is a onetime run script. It reads the workspace details from ./aml_config/config.json file and create (if workspace not available) or get (existing workspace). +### Code -- 01-Experiment.py : This is a onetime run script. It registers the root directory as project. It is not included as a step in build pipeline. +- code/training/train.py : a training step of an ML training pipeline. +- code/evaluate/evaluate_model.py : an evaluating step of an ML training pipeline. +- code/evaluate/evaluate_model.py : registers a new trained model if evaluation shows the new model is more performent than the previous one. -- 02-AttachTrainingVM.py : This is a onetime run script. It attaches a remote VM to the workspace. It reads the config from ./aml_config/security_config.json. It is not included as a step in build pipeline. +### Scoring +- code/scoring/score.py : a scoring script which is about to be packed into a Docker Image along with a model while being deployed to QA/Prod environment. +- code/scoring/conda_dependencies.yml : contains a list of dependencies required by sore.py to be installed in a deployable Docker Image +- code/scoring/inference_config.yml, deployment_config_aci.yml, deployment_config_aks.yml : configuration files for the [AML Model Deploy](https://marketplace.visualstudio.com/items?itemName=ms-air-aiagility.private-vss-services-azureml&ssr=false#overview) pipeline task for ACI and AKS deployment targets. -- 10-TrainOnLocal.py : This scripts triggers the run of ./training/train.py script on the local compute(Host agent in case of build pipeline). If you are training on remote vm, you do not need this script in build pipeline. All the training scripts (1x) generates an output file aml_config/run_id.json which records the run_id and run history name of the training run. run_id.json is used by 20-RegisterModel.py to get the trained model. - -- 11-TrainOnLocalEnv.py : Its functionality is same as 10-TrainOnLocal.py, the only difference is that it creates a virtual environment on local compute and run training script on virtual env. - -- 12-TrainOnVM.py : As we want to train the model on remote VM, this script is included as a task in build pipeline. It submits the training job on remote vm. - -- 15.EvaluateModel.py : It gets the metrics of latest model trained and compares it with the model in production. If the production model still performs better, all below scripts are skipped. - -- 20-RegisterModel.py : It gets the run id from training steps output json and registers the model associated with that run along with tags. This scripts outputs a model.json file which contains model name and version. This script included as build task. - -- 30-CreateScoringImage.py : This takes the model details from last step, creates a scoring webservice docker image and publish the image to ACR. This script included as build task. It writes the image name and version to image.json file. - -### Deployment/Release Scripts -File under the directory ./aml_service starting with 5x and 6x are used in release pipeline. They are basically to deploy the docker image on AKS and ACI and publish webservice on them. - -- 50-deployOnAci.py : This script reads the image.json which is published as an artifact from build pipeline, create aci cluster and deploy the scoring web service on it. It writes the scoring service details to aci_webservice.json - -- 51-deployOnAks.py : This script reads the image.json which is published as an artifact from build pipeline, create aks cluster and deploy the scoring web service on it. If the aks_webservice.json file was checked in with existing aks details, it will update the existing webservice with new Image. It writes the scoring service details to aks_webservice.json - -- 60-AciWebServiceTest.py : Reads the ACI info from aci_webservice.json and test it with sample data. - -- 61-AksWebServiceTest.py : Reads the AKS info from aks_webservice.json and test it with sample data. - -### Training/Scoring Scripts - -- /code/training/train.py : This is the model training code. It uploads the model file to AML Service run id once the training is successful. This script is submitted as run job by all the 1x scripts. - -- /code/scoring/score.py : This is the score file used to create the webservice docker image. There is a conda_dependencies.yml in this directory which is exactly same as the one in aml_config. These two files are needed by the 30-CreateScoringImage.py scripts to be in same root directory while creating the image. - -**Note: In CICD Pipeline, please make sure that the working directory is the root directory of the repo.** From 2b122c5ae5147ee8d7611918322f13cc2f606967 Mon Sep 17 00:00:00 2001 From: Eugene Fedorenko Date: Wed, 14 Aug 2019 17:18:27 -0700 Subject: [PATCH 102/113] update documentation progress --- ml_service/pipelines/run_train_pipeline.py | 10 +--------- 1 file changed, 1 insertion(+), 9 deletions(-) diff --git a/ml_service/pipelines/run_train_pipeline.py b/ml_service/pipelines/run_train_pipeline.py index 317ffec5..d4244069 100644 --- a/ml_service/pipelines/run_train_pipeline.py +++ b/ml_service/pipelines/run_train_pipeline.py @@ -3,7 +3,6 @@ import json import requests from azureml.core.authentication import AzureCliAuthentication -# from azure.common.credentials import ServicePrincipalCredentials try: @@ -16,16 +15,10 @@ experiment_name = os.environ.get("EXPERIMENT_NAME") model_name = os.environ.get("MODEL_NAME") -# credentials = ServicePrincipalCredentials( -# client_id = $(SP_APP_ID), -# secret = KEY, -# tenant = TENANT_ID -# ) cli_auth = AzureCliAuthentication() token = cli_auth.get_authentication_header() rest_endpoint = train_pipeline_json["rest_endpoint"] -print("rest_endpoint ", rest_endpoint) response = requests.post( rest_endpoint, headers=token, @@ -33,6 +26,5 @@ "ParameterAssignments": {"model_name": model_name}} ) -print("response ", response) run_id = response.json()["Id"] -print("Pipeline run initiated ", run_id) +print("Pipeline run initiated ", run_id) \ No newline at end of file From 4d34ace2d93181ba4bbe15bff79ee013cd4001b0 Mon Sep 17 00:00:00 2001 From: Eugene Fedorenko Date: Thu, 15 Aug 2019 09:23:09 -0700 Subject: [PATCH 103/113] azure-cli library update --- environment_setup/requirements.txt | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/environment_setup/requirements.txt b/environment_setup/requirements.txt index 3f5ce1e2..8a086c4d 100644 --- a/environment_setup/requirements.txt +++ b/environment_setup/requirements.txt @@ -5,4 +5,4 @@ azureml-sdk>=1.0 python-dotenv>=0.10.3 flake8 flake8_formatter_junit_xml -azure-cli==2.0.46 \ No newline at end of file +azure-cli==2.0.71 \ No newline at end of file From 71208d6bb73b5a1b365b4d26e0443664f0783058 Mon Sep 17 00:00:00 2001 From: Eugene Fedorenko Date: Thu, 15 Aug 2019 09:29:43 -0700 Subject: [PATCH 104/113] docker image update --- .pipelines/azdo-ci-build-train.yml | 2 +- .pipelines/azdo-pr-build-train.yml | 2 +- docs/code_description.md | 4 ++-- docs/getting_started.md | 2 +- 4 files changed, 5 insertions(+), 5 deletions(-) diff --git a/.pipelines/azdo-ci-build-train.yml b/.pipelines/azdo-ci-build-train.yml index eab1a743..36e7ce86 100644 --- a/.pipelines/azdo-ci-build-train.yml +++ b/.pipelines/azdo-ci-build-train.yml @@ -8,7 +8,7 @@ pool: vmImage: 'ubuntu-latest' container: - image: mlopscr.azurecr.io/public/mlops/mlopspython:latest + image: mcr.microsoft.com/mlops/python:latest endpoint: acrconnection diff --git a/.pipelines/azdo-pr-build-train.yml b/.pipelines/azdo-pr-build-train.yml index 6bbf7387..fc1017bf 100644 --- a/.pipelines/azdo-pr-build-train.yml +++ b/.pipelines/azdo-pr-build-train.yml @@ -8,7 +8,7 @@ pool: vmImage: 'ubuntu-latest' container: - image: mlopscr.azurecr.io/public/mlops/mlopspython:latest + image: mcr.microsoft.com/mlops/python:latest endpoint: acrconnection diff --git a/docs/code_description.md b/docs/code_description.md index efda15ca..11fd8b80 100644 --- a/docs/code_description.md +++ b/docs/code_description.md @@ -8,9 +8,9 @@ - environment_setup/iac-*.yml, arm-templates: Infrastructure as Code piplines to create and delete required resources along with corresponding arm-templates. -- environment_setup/Dockerfile : Dockerfile of a building agent (microsoft/mlopspython) containing Python 3.6 and all required packages. +- environment_setup/Dockerfile : Dockerfile of a building agent containing Python 3.6 and all required packages. -- environment_setup/docker-image-pipeline.yml : An AzDo pipeline building and pushing microsoft/mlopspython image. +- environment_setup/docker-image-pipeline.yml : An AzDo pipeline building and pushing [microsoft/mlopspython](https://hub.docker.com/_/microsoft-mlops-python) image. ### Pipelines diff --git a/docs/getting_started.md b/docs/getting_started.md index 9c1f3e28..28348ffb 100644 --- a/docs/getting_started.md +++ b/docs/getting_started.md @@ -127,7 +127,7 @@ Add a command line step **Run Training Pipeline** with the following script: ```bash docker run -v $(System.DefaultWorkingDirectory)/_ci-build/mlops-pipelines/ml_service/pipelines:/pipelines \ -w=/pipelines -e MODEL_NAME=$MODEL_NAME -e EXPERIMENT_NAME=$EXPERIMENT_NAME \ - microsoft/mlopspython python run_train_pipeline.py + mcr.microsoft.com/mlops/python:latest python run_train_pipeline.py ``` This release pipeline should be triggered whenever a new **ML training pipeline** is published by the **AzDo builder pipeline**. It can also be triggered manually or configured to run on a scheduled basis. Create a new release to trigger the pipeline manually: From 9736e0a4cf9facc39384872bc4786f2ebc40ada0 Mon Sep 17 00:00:00 2001 From: Eugene Fedorenko Date: Thu, 15 Aug 2019 09:39:38 -0700 Subject: [PATCH 105/113] docker image update --- .pipelines/azdo-ci-build-train.yml | 4 +--- .pipelines/azdo-pr-build-train.yml | 4 +--- 2 files changed, 2 insertions(+), 6 deletions(-) diff --git a/.pipelines/azdo-ci-build-train.yml b/.pipelines/azdo-ci-build-train.yml index 36e7ce86..09f90909 100644 --- a/.pipelines/azdo-ci-build-train.yml +++ b/.pipelines/azdo-ci-build-train.yml @@ -7,9 +7,7 @@ trigger: pool: vmImage: 'ubuntu-latest' -container: - image: mcr.microsoft.com/mlops/python:latest - endpoint: acrconnection +container: mcr.microsoft.com/mlops/python:latest variables: diff --git a/.pipelines/azdo-pr-build-train.yml b/.pipelines/azdo-pr-build-train.yml index fc1017bf..8bf6ca56 100644 --- a/.pipelines/azdo-pr-build-train.yml +++ b/.pipelines/azdo-pr-build-train.yml @@ -7,9 +7,7 @@ pr: pool: vmImage: 'ubuntu-latest' -container: - image: mcr.microsoft.com/mlops/python:latest - endpoint: acrconnection +container: mcr.microsoft.com/mlops/python:latest variables: From 7b7e382423f96ee45b71e125723ede68e01f6544 Mon Sep 17 00:00:00 2001 From: Eugene Fedorenko Date: Thu, 15 Aug 2019 09:50:39 -0700 Subject: [PATCH 106/113] liniting --- ml_service/pipelines/run_train_pipeline.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/ml_service/pipelines/run_train_pipeline.py b/ml_service/pipelines/run_train_pipeline.py index d4244069..c036aefd 100644 --- a/ml_service/pipelines/run_train_pipeline.py +++ b/ml_service/pipelines/run_train_pipeline.py @@ -27,4 +27,4 @@ ) run_id = response.json()["Id"] -print("Pipeline run initiated ", run_id) \ No newline at end of file +print("Pipeline run initiated ", run_id) From 5294441bd5dcff584f1ad75448c74772df6683a5 Mon Sep 17 00:00:00 2001 From: Eugene Fedorenko Date: Thu, 15 Aug 2019 17:17:06 -0700 Subject: [PATCH 107/113] Update getting_started.md --- docs/getting_started.md | 5 +++-- 1 file changed, 3 insertions(+), 2 deletions(-) diff --git a/docs/getting_started.md b/docs/getting_started.md index 28348ffb..c675ee57 100644 --- a/docs/getting_started.md +++ b/docs/getting_started.md @@ -126,8 +126,9 @@ Add a command line step **Run Training Pipeline** with the following script: ```bash docker run -v $(System.DefaultWorkingDirectory)/_ci-build/mlops-pipelines/ml_service/pipelines:/pipelines \ - -w=/pipelines -e MODEL_NAME=$MODEL_NAME -e EXPERIMENT_NAME=$EXPERIMENT_NAME \ - mcr.microsoft.com/mlops/python:latest python run_train_pipeline.py +-w=/pipelines -e MODEL_NAME=$MODEL_NAME -e EXPERIMENT_NAME=$EXPERIMENT_NAME \ +-e TENANT_ID=$TENANT_ID -e SP_APP_ID=$SP_APP_ID -e SP_APP_SECRET=$SP_APP_SECRET \ +mcr.microsoft.com/mlops/python:latest python run_train_pipeline.py ``` This release pipeline should be triggered whenever a new **ML training pipeline** is published by the **AzDo builder pipeline**. It can also be triggered manually or configured to run on a scheduled basis. 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z`gv96rD{hSZt8ino}r@C5xix8v^Ye^b*gU-~L|zGhadJG^4?&NEMdtM&F+ z#N*1#u(z{4@87Nh;ex!>&y9ao`y&h9_Y^BMgakJPs>2p20#b+(Ym7_b{jT(vN}opD zRp!B8DHcLRX>i`rxq`?@W6&_aj>v0&&W<7>YTokj8YFPv|C;*ducBmg%ZuF0A{Nnb z?V#^(jqP@mw+pWO+UZXsJ_Xt&r`#LMf2RZJ-di5^Lu+cOy(l&oKzh9O>byRG%PjkI wcD99I9HEUo+;zQiTrsw48S~#pCP18`r41jNEPF0BN&|ijbxn23wXos;1A;@nV*mgE From c8c282430d7266a1e620e0fba5cafb0ecd1c67f8 Mon Sep 17 00:00:00 2001 From: David Tesar Date: Thu, 15 Aug 2019 17:38:20 -0700 Subject: [PATCH 109/113] minor add and typo fix --- docs/getting_started.md | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/docs/getting_started.md b/docs/getting_started.md index c675ee57..7059122d 100644 --- a/docs/getting_started.md +++ b/docs/getting_started.md @@ -84,7 +84,7 @@ Check out created resources in the [Azure Portal](portal.azure.com): ![created resources](./images/created-resources.png) -Alternatively, you can also use a [cleaning pipeline](../environment_setup/iac-remove-environment.yml) that removes resources ctreated for this project or you can just delete a resource group in the [Azure Portal](portal.azure.com). +Alternatively, you can also use a [cleaning pipeline](../environment_setup/iac-remove-environment.yml) that removes resources created for this project or you can just delete a resource group in the [Azure Portal](portal.azure.com). ### 6. Set up Build Pipeline @@ -131,7 +131,7 @@ docker run -v $(System.DefaultWorkingDirectory)/_ci-build/mlops-pipelines/ml_se mcr.microsoft.com/mlops/python:latest python run_train_pipeline.py ``` -This release pipeline should be triggered whenever a new **ML training pipeline** is published by the **AzDo builder pipeline**. It can also be triggered manually or configured to run on a scheduled basis. Create a new release to trigger the pipeline manually: +This release pipeline should be automatically triggered (continuous deployment) whenever a new **ML training pipeline** is published by the **AzDo builder pipeline**. It can also be triggered manually or configured to run on a scheduled basis. Create a new release to trigger the pipeline manually: ![create release](./images/create-release.png) From 48718f363b7ce6dbe01cbc450eb92cfc5608b26d Mon Sep 17 00:00:00 2001 From: Eugene Fedorenko Date: Thu, 15 Aug 2019 17:55:43 -0700 Subject: [PATCH 110/113] duplicate file paths and `code` snippet for file paths --- docs/code_description.md | 28 ++++++++++++++-------------- 1 file changed, 14 insertions(+), 14 deletions(-) diff --git a/docs/code_description.md b/docs/code_description.md index 11fd8b80..ef131408 100644 --- a/docs/code_description.md +++ b/docs/code_description.md @@ -2,33 +2,33 @@ ### Environment Setup -- environment_setup/requirements.txt : It consist of list of python packages which are needed by the train.py to run successfully on host agent (locally). +- `environment_setup/requirements.txt` : It consist of list of python packages which are needed by the train.py to run successfully on host agent (locally). -- environment_setup/install_requirements.sh : This script prepare the python environment i.e. install the Azure ML SDK and the packages specified in requirements.txt +- `environment_setup/install_requirements.sh` : This script prepare the python environment i.e. install the Azure ML SDK and the packages specified in requirements.txt -- environment_setup/iac-*.yml, arm-templates: Infrastructure as Code piplines to create and delete required resources along with corresponding arm-templates. +- `environment_setup/iac-*.yml, arm-templates` : Infrastructure as Code piplines to create and delete required resources along with corresponding arm-templates. -- environment_setup/Dockerfile : Dockerfile of a building agent containing Python 3.6 and all required packages. +- `environment_setup/Dockerfile` : Dockerfile of a building agent containing Python 3.6 and all required packages. -- environment_setup/docker-image-pipeline.yml : An AzDo pipeline building and pushing [microsoft/mlopspython](https://hub.docker.com/_/microsoft-mlops-python) image. +- `environment_setup/docker-image-pipeline.yml` : An AzDo pipeline building and pushing [microsoft/mlopspython](https://hub.docker.com/_/microsoft-mlops-python) image. ### Pipelines -- .pipelines/azdo-base-pipeline.yml : a pipeline template used by ci-build-train pipeline and pr-build-train pipelines. It contains steps performig linting, data and unit testing. -- .pipelines/azdo-ci-build-train.yml : a pipeline triggered when the code is merged into **master**. It profrorms linting, data integrity testing, unit testing, building and publishing an ML pipeline. -- .pipelines/azdo-pr-build-train.yml : a pipeline triggered when a **pull request** to the **master** branch is created. It profrorms linting, data integrity testing and unit testing only. +- `.pipelines/azdo-base-pipeline.yml` : a pipeline template used by ci-build-train pipeline and pr-build-train pipelines. It contains steps performig linting, data and unit testing. +- `.pipelines/azdo-ci-build-train.yml` : a pipeline triggered when the code is merged into **master**. It profrorms linting, data integrity testing, unit testing, building and publishing an ML pipeline. +- `.pipelines/azdo-pr-build-train.yml` : a pipeline triggered when a **pull request** to the **master** branch is created. It profrorms linting, data integrity testing and unit testing only. ### ML Services -- ml_service/pipelines/build_train_pipeline.py : builds and publishes an ML training pipeline. -- ml_service/pipelines/run_train_pipeline.py : invokes a published ML training pipeline via REST API. -- ml_service/util : contains common utility functions used to build and publish an ML training pipeline. +- `ml_service/pipelines/build_train_pipeline.py` : builds and publishes an ML training pipeline. +- `ml_service/pipelines/run_train_pipeline.py` : invokes a published ML training pipeline via REST API. +- `ml_service/util` : contains common utility functions used to build and publish an ML training pipeline. ### Code -- code/training/train.py : a training step of an ML training pipeline. -- code/evaluate/evaluate_model.py : an evaluating step of an ML training pipeline. -- code/evaluate/evaluate_model.py : registers a new trained model if evaluation shows the new model is more performent than the previous one. +- `code/training/train.py` : a training step of an ML training pipeline. +- `code/evaluate/evaluate_model.py` : an evaluating step of an ML training pipeline. +- `code/evaluate/register_model.py` : registers a new trained model if evaluation shows the new model is more performent than the previous one. ### Scoring - code/scoring/score.py : a scoring script which is about to be packed into a Docker Image along with a model while being deployed to QA/Prod environment. From 2d4bdeeade05c4cf861c315a34667a01825aee16 Mon Sep 17 00:00:00 2001 From: Eugene Fedorenko Date: Thu, 15 Aug 2019 18:17:08 -0700 Subject: [PATCH 111/113] Model Deploy tasks parameters in tables --- docs/getting_started.md | 27 +++++++++++++++++++++++++-- 1 file changed, 25 insertions(+), 2 deletions(-) diff --git a/docs/getting_started.md b/docs/getting_started.md index 7059122d..45988bf7 100644 --- a/docs/getting_started.md +++ b/docs/getting_started.md @@ -166,14 +166,37 @@ Add an artifact to the pipeline and select **AzureML Model Artifact** source typ ![model artifact](./images/model-artifact.png) -Create a stage **QA (ACI)** and add a single task to the job **Azure ML Model Deploy**. Specify task parameters as it is shown below: +Create a stage **QA (ACI)** and add a single task to the job **Azure ML Model Deploy**: ![deploy aci](./images/deploy-aci.png) -In a similar way create a stage **Prod (AKS** and add a single task to the job **Azure ML Model Deploy**. Specify task parameters as it is shown below: +Specify task parameters as it is shown in the table below: +| Parameter | Value | +| --- | --- | +| Display Name | Azure ML Model Deploy | +| Azure ML Workspace | mlops-AML-WS | +| Inference config Path | `$(System.DefaultWorkingDirectory)/_ci-build/mlops-pipelines/code/scoring/inference_config.yml` | +| Model Deployment Target | Azure Container Instance | +| Deployment Name | mlopspython-aci | +| Deployment Configuration file | `$(System.DefaultWorkingDirectory)/_ci-build/mlops-pipelines/code/scoring/deployment_config_aci.yml` | +| Overwrite existing deployment | X | + + +In a similar way create a stage **Prod (AKS** and add a single task to the job **Azure ML Model Deploy**: ![deploy aks](./images/deploy-aks.png) +Specify task parameters as it is shown in the table below: +| Parameter | Value | +| --- | --- | +| Display Name | Azure ML Model Deploy | +| Azure ML Workspace | mlops-AML-WS | +| Inference config Path | `$(System.DefaultWorkingDirectory)/_ci-build/mlops-pipelines/code/scoring/inference_config.yml` | +| Model Deployment Target | Azure Kubernetes Service | +| Select AKS Cluster for Deployment | YOUR_DEPLOYMENT_K8S_CLUSTER | +| Deployment Name | mlopspython-aks | +| Deployment Configuration file | `$(System.DefaultWorkingDirectory)/_ci-build/mlops-pipelines/code/scoring/deployment_config_aks.yml` | +| Overwrite existing deployment | X | **Note:** Creating of a Kubernetes cluster on AKS is out of scope of this tutorial, so you should take care of it on your own. From c0860e5d3c990b0aae974959f125af19cb318016 Mon Sep 17 00:00:00 2001 From: Eugene Fedorenko Date: Thu, 15 Aug 2019 18:19:22 -0700 Subject: [PATCH 112/113] tables with task parameters uopdate --- docs/getting_started.md | 3 +++ 1 file changed, 3 insertions(+) diff --git a/docs/getting_started.md b/docs/getting_started.md index 45988bf7..994e220d 100644 --- a/docs/getting_started.md +++ b/docs/getting_started.md @@ -171,6 +171,8 @@ Create a stage **QA (ACI)** and add a single task to the job **Azure ML Model De ![deploy aci](./images/deploy-aci.png) Specify task parameters as it is shown in the table below: + + | Parameter | Value | | --- | --- | | Display Name | Azure ML Model Deploy | @@ -187,6 +189,7 @@ In a similar way create a stage **Prod (AKS** and add a single task to the job * ![deploy aks](./images/deploy-aks.png) Specify task parameters as it is shown in the table below: + | Parameter | Value | | --- | --- | | Display Name | Azure ML Model Deploy | From f6f44276a043e3863fdf5515019e02eb08334eef Mon Sep 17 00:00:00 2001 From: Eugene Fedorenko Date: Thu, 15 Aug 2019 20:18:12 -0700 Subject: [PATCH 113/113] Eedorenko/yaml header (#49) * added YAML front-matter hreder to readme * Added azure to the list of products --- README.md | 10 ++++++++++ 1 file changed, 10 insertions(+) diff --git a/README.md b/README.md index e09b85b1..28d2a078 100644 --- a/README.md +++ b/README.md @@ -1,3 +1,13 @@ +--- +page_type: sample +languages: +- python +products: +- azure +- azure-machine-learning-service +- azure-devops +--- + # MLOps with Azure ML

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insertion(+), 1 deletion(-) diff --git a/docs/getting_started.md b/docs/getting_started.md index 96afd9be..cd56dd9f 100644 --- a/docs/getting_started.md +++ b/docs/getting_started.md @@ -14,7 +14,7 @@ If you already have Azure DevOps account, create a [new project](https://docs.mi ### 3. Create Service Principal to Login to Azure To create service principal, register an application entity in Azure Active Directory (Azure AD) and grant it the Contributor or Owner role of the subscription or the resource group where the web service belongs to. See [how to create service principal](https://docs.microsoft.com/en-us/azure/active-directory/develop/howto-create-service-principal-portal) and assign permissions to manage Azure resource. -Please make note the following values after creating a service principal, we will need them in subsequent steps +Please make note of the following values after creating a service principal, we will need them in subsequent steps - Application (client) ID - Directory (tenant) ID - Application Secret From 5c7ebe450319f21fdeb5248529766038b383b889 Mon Sep 17 00:00:00 2001 From: Eugene Fedorenko Date: Wed, 14 Aug 2019 10:03:34 -0700 Subject: [PATCH 089/113] Update getting_started.md --- docs/getting_started.md | 21 +++++++++++++++++++-- 1 file changed, 19 insertions(+), 2 deletions(-) diff --git a/docs/getting_started.md b/docs/getting_started.md index cd56dd9f..b61f6827 100644 --- a/docs/getting_started.md +++ b/docs/getting_started.md @@ -31,7 +31,24 @@ Please name your variable group **``devopsforai-aml-vg``** as we are using this The varibale group should contain the following variables: -a table (name, description, value) +| Variable Name | Suggested Value | +| --- | --- | +| AML_COMPUTE_CLUSTER_CPU_SKU | STANDARD_DS2_V2 | +| AML_COMPUTE_CLUSTER_NAME | train-cluster | +| AML_WORKSPACE_NAME | mlops-AML-WS | +| BASE_NAME | mlops | +| EVALUATE_SCRIPT_PATH | evaluate/evaluate_model.py | +| EXPERIMENT_NAME | mlopspython | +| LOCATION | centralus | +| MODEL_NAME | sklearn_regression_model.pkl | +| REGISTER_SCRIPT_PATH | register/register_model.py | +| RESOURCE_GROUP | mlops-AML-RG | +| SOURCES_DIR_TRAIN | code | +| SP_APP_ID | | +| SP_APP_SECRET | | +| SUBSCRIPTION_ID | | +| TENANT_ID | | +| TRAIN_SCRIPT_PATH | training/train.py | Mark **SP_APP_SECRET** variable as a secret one. @@ -70,7 +87,7 @@ Alternatively, you can also use a [cleaning pipeline](../environment_setup/iac-c ### 6. Set up Build Pipeline -In your [Azure DevOps](https://dev.azure.com) project create and run a new build pipeline refereing to **azdo-ci-build-train.yml** pipeline in yuor forked **GitHub** repository +In your [Azure DevOps](https://dev.azure.com) project create and run a new build pipeline refereing to **azdo-ci-build-train.yml** pipeline in your forked **GitHub** repository ![configure ci build pipeline](./images/ci-build-pipeline-configure.png) From 8fc0ba132237109026751f165b7796b65759d6c7 Mon Sep 17 00:00:00 2001 From: Eugene Fedorenko Date: Wed, 14 Aug 2019 10:04:24 -0700 Subject: [PATCH 090/113] Update getting_started.md --- docs/getting_started.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/docs/getting_started.md b/docs/getting_started.md index b61f6827..6d575f48 100644 --- a/docs/getting_started.md +++ b/docs/getting_started.md @@ -54,7 +54,7 @@ Mark **SP_APP_SECRET** variable as a secret one. Make sure to select the **Allow access to all pipelines** checkbox in the variable group configuration. -Up until now you should have +Up until now you should have: - Forked (or cloned) the repo - Created a devops account or use an existing one - Got service principal details and subscription id From 5a05f009c6c13c45b34f520466340812f16a864a Mon Sep 17 00:00:00 2001 From: Eugene Fedorenko Date: Wed, 14 Aug 2019 10:06:45 -0700 Subject: [PATCH 091/113] Update getting_started.md --- docs/getting_started.md | 12 ++++++------ 1 file changed, 6 insertions(+), 6 deletions(-) diff --git a/docs/getting_started.md b/docs/getting_started.md index 6d575f48..caf42118 100644 --- a/docs/getting_started.md +++ b/docs/getting_started.md @@ -62,24 +62,24 @@ Up until now you should have: ### 5. Create resources -The easiest way to create all required resources (Resource Group, ML Workspace, Container Registry, Storage Account, etc.) is to leverage an "Infrastructure as Code" [pipeline coming in this repository](../environment_setup/iac-create-environment.yml). This **IaC** pipeline takes care of all required resources basing on these [ARM templates](../environment_setup/arm-templates/cloud-environment.json). The pipeline requires an **Azure Resource Manager** service connection +The easiest way to create all required resources (Resource Group, ML Workspace, Container Registry, Storage Account, etc.) is to leverage an "Infrastructure as Code" [pipeline coming in this repository](../environment_setup/iac-create-environment.yml). This **IaC** pipeline takes care of all required resources basing on these [ARM templates](../environment_setup/arm-templates/cloud-environment.json). The pipeline requires an **Azure Resource Manager** service connection: ![create service connection](./images/create-rm-service-connection.png) Give the connection name **``AzureResourceConnection``** as it is referred by the pipeline definition. -In your DevOps project create a build pipeline from your forked **GitHub** repository +In your DevOps project create a build pipeline from your forked **GitHub** repository: ![build connnect step](./images/build-connect.png) -Refer to an **Existing Azure Pipelines YAML file** +Refer to an **Existing Azure Pipelines YAML file**: ![configure step](./images/select-iac-pipeline.png) -Having done that, run the pipeline +Having done that, run the pipeline: ![iac run](./images/run-iac-pipeline.png) -Check out created resources in the [Azure Portal](portal.azure.com) +Check out created resources in the [Azure Portal](portal.azure.com): ![created resources](./images/created-resources.png) Alternatively, you can also use a [cleaning pipeline](../environment_setup/iac-create-environment.yml) that removes resources ctreated for this project or you can just delete a resource group in the [Azure Portal](portal.azure.com). @@ -87,7 +87,7 @@ Alternatively, you can also use a [cleaning pipeline](../environment_setup/iac-c ### 6. Set up Build Pipeline -In your [Azure DevOps](https://dev.azure.com) project create and run a new build pipeline refereing to **azdo-ci-build-train.yml** pipeline in your forked **GitHub** repository +In your [Azure DevOps](https://dev.azure.com) project create and run a new build pipeline refereing to **azdo-ci-build-train.yml** pipeline in your forked **GitHub** repository: ![configure ci build pipeline](./images/ci-build-pipeline-configure.png) From 8b5b76af4fdee54e0a57f84981a797f6da608d25 Mon Sep 17 00:00:00 2001 From: Eugene Fedorenko Date: Wed, 14 Aug 2019 10:08:05 -0700 Subject: [PATCH 092/113] Update getting_started.md --- docs/getting_started.md | 2 ++ 1 file changed, 2 insertions(+) diff --git a/docs/getting_started.md b/docs/getting_started.md index caf42118..a2930a49 100644 --- a/docs/getting_started.md +++ b/docs/getting_started.md @@ -77,9 +77,11 @@ Refer to an **Existing Azure Pipelines YAML file**: ![configure step](./images/select-iac-pipeline.png) Having done that, run the pipeline: + ![iac run](./images/run-iac-pipeline.png) Check out created resources in the [Azure Portal](portal.azure.com): + ![created resources](./images/created-resources.png) Alternatively, you can also use a [cleaning pipeline](../environment_setup/iac-create-environment.yml) that removes resources ctreated for this project or you can just delete a resource group in the [Azure Portal](portal.azure.com). From a50b0d424bbcd98a6e72d57d331bf079a6b000d6 Mon Sep 17 00:00:00 2001 From: Eugene Fedorenko Date: Wed, 14 Aug 2019 10:09:29 -0700 Subject: [PATCH 093/113] Update getting_started.md --- docs/getting_started.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/docs/getting_started.md b/docs/getting_started.md index a2930a49..7a5d1da9 100644 --- a/docs/getting_started.md +++ b/docs/getting_started.md @@ -84,7 +84,7 @@ Check out created resources in the [Azure Portal](portal.azure.com): ![created resources](./images/created-resources.png) -Alternatively, you can also use a [cleaning pipeline](../environment_setup/iac-create-environment.yml) that removes resources ctreated for this project or you can just delete a resource group in the [Azure Portal](portal.azure.com). +Alternatively, you can also use a [cleaning pipeline](../environment_setup/iac-remove-environment.yml) that removes resources ctreated for this project or you can just delete a resource group in the [Azure Portal](portal.azure.com). ### 6. Set up Build Pipeline From bd2a43b2674a82881c57fc7b89196581d396a01f Mon Sep 17 00:00:00 2001 From: Eugene Fedorenko Date: Wed, 14 Aug 2019 10:11:53 -0700 Subject: [PATCH 094/113] Update getting_started.md --- docs/getting_started.md | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/docs/getting_started.md b/docs/getting_started.md index 7a5d1da9..70b7db9a 100644 --- a/docs/getting_started.md +++ b/docs/getting_started.md @@ -89,15 +89,15 @@ Alternatively, you can also use a [cleaning pipeline](../environment_setup/iac-r ### 6. Set up Build Pipeline -In your [Azure DevOps](https://dev.azure.com) project create and run a new build pipeline refereing to **azdo-ci-build-train.yml** pipeline in your forked **GitHub** repository: +In your [Azure DevOps](https://dev.azure.com) project create and run a new build pipeline refereing to [azdo-ci-build-train.yml](../.pipelines/azdo-ci-build-train.yml) pipeline in your forked **GitHub** repository: ![configure ci build pipeline](./images/ci-build-pipeline-configure.png) -Once the pipline is finished, explore the execution logs +Once the pipline is finished, explore the execution logs: ![ci build logs](./images/ci-build-logs.png) -and checkout a published training pipeline in the **mlops-AML-WS** workspace in [Azure Portal](https://ms.portal.azure.com/) +and checkout a published training pipeline in the **mlops-AML-WS** workspace in [Azure Portal](https://ms.portal.azure.com/): ![training pipeline](./images/training-pipeline.png) From f93058007a64aee5eb745c588229c2f9c5bdb654 Mon Sep 17 00:00:00 2001 From: Eugene Fedorenko Date: Wed, 14 Aug 2019 10:13:58 -0700 Subject: [PATCH 095/113] Update getting_started.md --- docs/getting_started.md | 3 +-- 1 file changed, 1 insertion(+), 2 deletions(-) diff --git a/docs/getting_started.md b/docs/getting_started.md index 70b7db9a..eafc8df6 100644 --- a/docs/getting_started.md +++ b/docs/getting_started.md @@ -93,7 +93,7 @@ In your [Azure DevOps](https://dev.azure.com) project create and run a new build ![configure ci build pipeline](./images/ci-build-pipeline-configure.png) -Once the pipline is finished, explore the execution logs: +Name the pipeline **ci-build**. Once the pipline is finished, explore the execution logs: ![ci build logs](./images/ci-build-logs.png) @@ -101,7 +101,6 @@ and checkout a published training pipeline in the **mlops-AML-WS** workspace in ![training pipeline](./images/training-pipeline.png) -Rename the pipeline as **ci-build**. Great, you now have the build pipeline setup, you can either manually trigger it or it gets automatically triggered everytime there is a change in the master branch. The pipeline performs linitnig, unit testing, builds and publishes an **ML Training Pipeline** in an **ML Workspace** From e433ca863362f39b79d6c997001b074526428493 Mon Sep 17 00:00:00 2001 From: Eugene Fedorenko Date: Wed, 14 Aug 2019 10:18:49 -0700 Subject: [PATCH 096/113] Update getting_started.md --- docs/getting_started.md | 19 ++++++++++--------- 1 file changed, 10 insertions(+), 9 deletions(-) diff --git a/docs/getting_started.md b/docs/getting_started.md index eafc8df6..7f329ade 100644 --- a/docs/getting_started.md +++ b/docs/getting_started.md @@ -102,40 +102,41 @@ and checkout a published training pipeline in the **mlops-AML-WS** workspace in ![training pipeline](./images/training-pipeline.png) -Great, you now have the build pipeline setup, you can either manually trigger it or it gets automatically triggered everytime there is a change in the master branch. The pipeline performs linitnig, unit testing, builds and publishes an **ML Training Pipeline** in an **ML Workspace** +Great, you now have the build pipeline setup, you can either manually trigger it or it gets automatically triggered everytime there is a change in the master branch. The pipeline performs linting, unit testing, builds and publishes an **ML Training Pipeline** in an **ML Workspace** -### 6. Train the Model +### 7. Train the Model The next step is to invoke the training pipeline created in the previous step. It can be done with a **Release Pipeline**: ![invoke training pipeline](./images/invoke-training-pipeline.png) -An artifact of this pipeline will be the result of the build pipeline **ci-buid** +An artifact of this pipeline will be the result of the build pipeline **ci-buid**: ![artifact invoke pipeline](./images/artifact-invoke-pipeline.png) -Configure a pipeline to see values from the previously defined variable group **devopsforai-aml-vg** +Configure a pipeline to see values from the previously defined variable group **devopsforai-aml-vg**: ![retrain pipeline vg](./images/retrain-pipeline-vg.png) -Add an empty stage with name **``Invoke Training Pipeline``** and make sure that the **Agent Specification** is **``ubuntu-16.04``** +Add an empty stage with name **``Invoke Training Pipeline``** and make sure that the **Agent Specification** is **``ubuntu-16.04``**: + ![agent specification](./images/agent-specification.png) -Add a command line step **``Invoke Training Pipeline``** with the following script +Add a command line step **``Invoke Training Pipeline``** with the following script: ```bash docker run -v $(System.DefaultWorkingDirectory)/_ci-build/mlops-pipelines/ml_service/pipelines:/pipelines -w=/pipelines -e MODEL_NAME=$MODEL_NAME -e EXPERIMENT_NAME=$EXPERIMENT_NAME microsoft/mlopspython python run_train_pipeline.py ``` -The pipeline is triggered whenever a new training pipeline is published by the builder pipeline. It can also be triggered manually or configured to run on a scheduled basis. Create a new release to trigger the pipeline manually +This release pipeline is triggered whenever a new **ML training pipeline** is published by the **AzDo builder pipeline**. It can also be triggered manually or configured to run on a scheduled basis. Create a new release to trigger the pipeline manually: ![create release](./images/create-release.png) -Once the pipeline is completed, check out in the **ML Workspace** that the training pipeline is running +Once the release pipeline is completed, check out in the **ML Workspace** that the training pipeline is running: ![running training pipeline](./images/running-training-pipeline.png) -The training pipeline will train, evaluate and register a new model. Wait intil it is fininshed and make sure there is a new model in the **ML Workspace** +The training pipeline will train, evaluate and register a new model. Wait until it is fininshed and make sure there is a new model in the **ML Workspace**: ![trained model](./images/trained-model.png) From a4f44bb8374be675b5b96b6117ee354711540927 Mon Sep 17 00:00:00 2001 From: Eugene Fedorenko Date: Wed, 14 Aug 2019 11:50:24 -0700 Subject: [PATCH 097/113] Update getting_started.md --- docs/getting_started.md | 30 ++++++++++++++++-------------- 1 file changed, 16 insertions(+), 14 deletions(-) diff --git a/docs/getting_started.md b/docs/getting_started.md index 7f329ade..9c1f3e28 100644 --- a/docs/getting_started.md +++ b/docs/getting_started.md @@ -118,17 +118,19 @@ Configure a pipeline to see values from the previously defined variable group ** ![retrain pipeline vg](./images/retrain-pipeline-vg.png) -Add an empty stage with name **``Invoke Training Pipeline``** and make sure that the **Agent Specification** is **``ubuntu-16.04``**: +Add an empty stage with name **Invoke Training Pipeline** and make sure that the **Agent Specification** is **ubuntu-16.04**: ![agent specification](./images/agent-specification.png) -Add a command line step **``Invoke Training Pipeline``** with the following script: +Add a command line step **Run Training Pipeline** with the following script: ```bash -docker run -v $(System.DefaultWorkingDirectory)/_ci-build/mlops-pipelines/ml_service/pipelines:/pipelines -w=/pipelines -e MODEL_NAME=$MODEL_NAME -e EXPERIMENT_NAME=$EXPERIMENT_NAME microsoft/mlopspython python run_train_pipeline.py +docker run -v $(System.DefaultWorkingDirectory)/_ci-build/mlops-pipelines/ml_service/pipelines:/pipelines \ + -w=/pipelines -e MODEL_NAME=$MODEL_NAME -e EXPERIMENT_NAME=$EXPERIMENT_NAME \ + microsoft/mlopspython python run_train_pipeline.py ``` -This release pipeline is triggered whenever a new **ML training pipeline** is published by the **AzDo builder pipeline**. It can also be triggered manually or configured to run on a scheduled basis. Create a new release to trigger the pipeline manually: +This release pipeline should be triggered whenever a new **ML training pipeline** is published by the **AzDo builder pipeline**. It can also be triggered manually or configured to run on a scheduled basis. Create a new release to trigger the pipeline manually: ![create release](./images/create-release.png) @@ -142,43 +144,43 @@ The training pipeline will train, evaluate and register a new model. Wait until Good! Now we have a trained model. -### 6. Train the Model +### 8. Deploy the Model The final step is to deploy the model across environments with a release pipeline. There will be a **``QA``** environment running on [Azure Container Instances](https://azure.microsoft.com/en-us/services/container-instances/) and a **``Prod``** environment running on [Azure Kubernetes Service](https://azure.microsoft.com/en-us/services/kubernetes-service). ![deploy model](./images/deploy-model.png) -This pipeline leverages the **Azure Machine Learning** extension that should be installed in your organization from the [marketplace](https://marketplace.visualstudio.com/items?itemName=ms-air-aiagility.vss-services-azureml) +This pipeline leverages the **Azure Machine Learning** extension that should be installed in your organization from the [marketplace](https://marketplace.visualstudio.com/items?itemName=ms-air-aiagility.vss-services-azureml). The pipeline consumes two artifacts: the result of the **Build Pipeline** as it contains configuration files and the **model** trained and registered by the ML training pipeline. -Configuration of a code **``_ci-build``** artifact is similar to what we did in the previous chapter. +Configuration of a code **_ci-build** artifact is similar to what we did in the previous chapter. -In order to configure a model artifact there should be a service connection to **``mlops-AML-WS``** workspace. +In order to configure a model artifact there should be a service connection to **mlops-AML-WS** workspace: ![workspace connection](./images/workspace-connection.png) -Add an artifact to the pipeline and select **AzureML Model Artifact** source type. Select the **Service Endpoint** and **Model Names** from the drop down lists +Add an artifact to the pipeline and select **AzureML Model Artifact** source type. Select the **Service Endpoint** and **Model Names** from the drop down lists: ![model artifact](./images/model-artifact.png) -Create a stage **``QA (ACI)``** and add a single task to the job **Azure ML Model Deploy**. Specify task parameters as it is shown below +Create a stage **QA (ACI)** and add a single task to the job **Azure ML Model Deploy**. Specify task parameters as it is shown below: ![deploy aci](./images/deploy-aci.png) -In a similar way create a stage **``Prod (AKS)``** and add a single task to the job **Azure ML Model Deploy**. Specify task parameters as it is shown below +In a similar way create a stage **Prod (AKS** and add a single task to the job **Azure ML Model Deploy**. Specify task parameters as it is shown below: ![deploy aks](./images/deploy-aks.png) -Note! Creating of a Kubernetes cluster on AKS is out of scope of this tutorial, so you should take care of it on your own. +**Note:** Creating of a Kubernetes cluster on AKS is out of scope of this tutorial, so you should take care of it on your own. -Save the pipeline and craete a release for it to trigger the pipeline manually. Once it's finished, check out deployments in the **``mlops-AML-WS``** workspace. +Save the pipeline and craete a release to trigger it manually. Once the pipeline exection is finished, check out deployments in the **mlops-AML-WS** workspace. -Congratulations, you now have three pipelines set up end to end. +Congratulations! You have three pipelines set up end to end: - Build pipeline: triggered on code change to master branch on GitHub, performs linting, unit testing and publishing a trainig pipeline - Release Trigger pipeline: runs a published training pipeline to trian, evaluate and register a model - Release Deployment pipeline: deploys a model to QA (ACI) and Prod (AKS) environemts From d4b343eede1d08d0d194e9757c6798f27182c62e Mon Sep 17 00:00:00 2001 From: Eugene Fedorenko Date: Wed, 14 Aug 2019 14:52:04 -0700 Subject: [PATCH 098/113] readme update --- README.md | 22 ++++-------------- ...ificatioin.png => agent-specification.png} | Bin docs/images/main-diagram.png | Bin 0 -> 307433 bytes 3 files changed, 4 insertions(+), 18 deletions(-) rename docs/images/{agent-specificatioin.png => agent-specification.png} (100%) create mode 100644 docs/images/main-diagram.png diff --git a/README.md b/README.md index 29ebd646..af833f4a 100644 --- a/README.md +++ b/README.md @@ -3,7 +3,6 @@ [![Build Status](https://dev.azure.com/customai/DevopsForAI-AML/_apis/build/status/Microsoft.MLOpsPython?branchName=master)](https://dev.azure.com/customai/DevopsForAI-AML/_build/latest?definitionId=25&branchName=master) -### Author: Praneet Solanki | Richin Jain MLOps will help you to understand how to build the Continuous Integration and Continuous Delivery pipeline for a ML/AI project. We will be using the Azure DevOps Project for build and release/deployment pipelines along with Azure ML services for model retraining pipeline, model management and operationalization. @@ -25,20 +24,15 @@ To deploy this solution in your subscription, follow the manual instructions in This reference architecture shows how to implement continuous integration (CI), continuous delivery (CD), and retraining pipeline for an AI application using Azure DevOps and Azure Machine Learning. The solution is built on the scikit-learn diabetes dataset but can be easily adapted for any AI scenario and other popular build systems such as Jenkins and Travis. -![Architecture](/docs/images/Architecture_DevOps_AI.png) +![Architecture](/docs/images/main-diagram.png) ## Architecture Flow ### Train Model 1. Data Scientist writes/updates the code and push it to git repo. This triggers the Azure DevOps build pipeline (continuous integration). -2. Once the Azure DevOps build pipeline is triggered, it runs following types of tasks: - - Run for new code: Every time new code is committed to the repo, the build pipeline performs data sanity tests and unit tests on the new code. - - One-time run: These tasks runs only for the first time the build pipeline runs. It will programatically create an [Azure ML Service Workspace](https://docs.microsoft.com/en-us/azure/machine-learning/service/concept-azure-machine-learning-architecture#workspace), provision [Azure ML Compute](https://docs.microsoft.com/en-us/azure/machine-learning/service/how-to-set-up-training-targets#amlcompute) (used for model training compute), and publish an [Azure ML Pipeline](https://docs.microsoft.com/en-us/azure/machine-learning/service/concept-ml-pipelines). This published Azure ML pipeline is the model training/retraining pipeline. - - > Note: The Publish Azure ML pipeline task currently runs for every code change - -3. The Azure ML Retraining pipeline is triggered once the Azure DevOps build pipeline completes. All the tasks in this pipeline runs on Azure ML Compute created earlier. Following are the tasks in this pipeline: +2. Once the Azure DevOps build pipeline is triggered, it performs code quality checks, data sanity tests, unit tests, builds a [Azure ML Pipeline](https://docs.microsoft.com/en-us/azure/machine-learning/service/concept-ml-pipelines) and publishes it in an [Azure ML Service Workspace](https://docs.microsoft.com/en-us/azure/machine-learning/service/concept-azure-machine-learning-architecture#workspace). +3. The [Azure ML Pipeline](https://docs.microsoft.com/en-us/azure/machine-learning/service/concept-ml-pipelines) is triggered once the Azure DevOps build pipeline completes. All the tasks in this pipeline runs on Azure ML Compute. Following are the tasks in this pipeline: - **Train Model** task executes model training script on Azure ML Compute. It outputs a [model](https://docs.microsoft.com/en-us/azure/machine-learning/service/concept-azure-machine-learning-architecture#model) file which is stored in the [run history](https://docs.microsoft.com/en-us/azure/machine-learning/service/concept-azure-machine-learning-architecture#run). @@ -50,16 +44,8 @@ This reference architecture shows how to implement continuous integration (CI), Once you have registered your ML model, you can use Azure ML + Azure DevOps to deploy it. -The **Package Model** task packages the new model along with the scoring file and its python dependencies into a [docker image](https://docs.microsoft.com/en-us/azure/machine-learning/service/concept-azure-machine-learning-architecture#image) and pushes it to [Azure Container Registry](https://docs.microsoft.com/en-us/azure/container-registry/container-registry-intro). This image is used to deploy the model as [web service](https://docs.microsoft.com/en-us/azure/machine-learning/service/concept-azure-machine-learning-architecture#web-service). - -The **Deploy Model** task handles deploying your Azure ML model to the cloud (ACI or AKS). -This pipeline deploys the model scoring image into Staging/QA and PROD environments. - - In the Staging/QA environment, one task creates an [Azure Container Instance](https://docs.microsoft.com/en-us/azure/container-instances/container-instances-overview) and deploys the scoring image as a [web service](https://docs.microsoft.com/en-us/azure/machine-learning/service/concept-azure-machine-learning-architecture#web-service) on it. - -The second task invokes the web service by calling its REST endpoint with dummy data. +[Azure DevOps release pipeline](https://docs.microsoft.com/en-us/azure/devops/pipelines/release/?view=azure-devops) packages the new model along with the scoring file and its python dependencies into a [docker image](https://docs.microsoft.com/en-us/azure/machine-learning/service/concept-azure-machine-learning-architecture#image) and pushes it to [Azure Container Registry](https://docs.microsoft.com/en-us/azure/container-registry/container-registry-intro). This image is used to deploy the model as [web service](https://docs.microsoft.com/en-us/azure/machine-learning/service/concept-azure-machine-learning-architecture#web-service) across QA and Prod environments. The QA environment is running on top of [Azure Container Instances (ACI)](https://azure.microsoft.com/en-us/services/container-instances/) and the Prod environemt is built with [Azure Kubernetes Service (AKS)](https://docs.microsoft.com/en-us/azure/aks/intro-kubernetes). -5. The deployment in production is a [gated release](https://docs.microsoft.com/en-us/azure/devops/pipelines/release/approvals/gates?view=azure-devops). This means that once the model web service deployment in the Staging/QA environment is successful, a notification is sent to approvers to manually review and approve the release. Once the release is approved, the model scoring web service is deployed to [Azure Kubernetes Service(AKS)](https://docs.microsoft.com/en-us/azure/aks/intro-kubernetes) and the deployment is tested. ### Repo Details diff --git a/docs/images/agent-specificatioin.png b/docs/images/agent-specification.png similarity index 100% rename from docs/images/agent-specificatioin.png rename to docs/images/agent-specification.png diff --git a/docs/images/main-diagram.png b/docs/images/main-diagram.png new file mode 100644 index 0000000000000000000000000000000000000000..97aecaaac657de1ce48bd3bfaba4c1961dd4a556 GIT binary patch literal 307433 zcmeEucUY6z*Dat3f+7|`rCJc_iqfkBHVmQ=kS<*agx-4-K@k)i9RxuVLQMz|ibzwc z7ziaaLFo``D52bw(V1_??|#m`|J;A>Z=OeG2+8}t`|Pv#+H0*tq?YE@{Y=N1XlQ8m zU%#eyhlYkBg@$I26XPE6owt0G=V)m5-LO?v)w-^#%BSVxXl-k6MMHBf@`WD5UF}co zDTa5h-w)Qx3>#Dv{PH&J^GU{QZ1!QNW3|k0GM@Bc*Qf6mJDHX@fq3{Rk3JUjCeQu$ z%vSotrl#_{1?h`t=m}k<%GJsxe^*lKh4Ia7%el%6G!vbRnO_uiID-7H2aBALcrJNf 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