Skip to content

Navigation Menu

Sign in
Appearance settings

Search code, repositories, users, issues, pull requests...

Provide feedback

We read every piece of feedback, and take your input very seriously.

Saved searches

Use saved searches to filter your results more quickly

Appearance settings

Fix Estimator role expansion#68

Merged
iquintero merged 1 commit intoaws:masteraws/sagemaker-python-sdk:masterfrom
iquintero:service_roleCopy head branch name to clipboard
Feb 2, 2018
Merged

Fix Estimator role expansion#68
iquintero merged 1 commit intoaws:masteraws/sagemaker-python-sdk:masterfrom
iquintero:service_roleCopy head branch name to clipboard

Conversation

@iquintero
Copy link
Contributor

Instead of manually constructing the role ARN, use the IAM boto client
to do it. This properly expands service-roles and regular roles.

This fixes #43

Instead of manually constructing the role ARN, use the IAM boto client
to do it. This properly expands service-roles and regular roles.
@iquintero iquintero requested a review from owen-t February 1, 2018 18:57
Copy link
Contributor

@mvsusp mvsusp left a comment

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

@iquintero, can we write a unit test for that?

@iquintero
Copy link
Contributor Author

It doesn't really make sense to have a unit test for this, as I would have to mock the boto call to IAM and at that point there is nothing else left to test. Also the ARN is not being manually crafted anymore so we should be able to trust that boto is doing the right thing here.

@mvsusp
Copy link
Contributor

mvsusp commented Feb 2, 2018

Agreed.

@iquintero iquintero merged commit b45d79c into aws:master Feb 2, 2018
jalabort added a commit to hudl/sagemaker-python-sdk that referenced this pull request Mar 1, 2018
* Add data_type to hyperparameters (aws#54)

When we describe a training job the data type of the hyper parameters is
lost because we use a dict[str, str]. This adds a new field to
Hyperparameter so that we can convert the datatypes at runtime.

instead of validating with isinstance(), we cast the hp value to the type it
is meant to be. This enforces a "strongly typed" value. When we
deserialize from the API string responses it becomes easier to deal with
too.

* Add wrapper for LDA. (aws#56)

Update CHANGELOG and bump the version number.

* Add support for async fit() (aws#59)

when calling fit(wait=False) it will return immediately. The training
job will carry on even if the process exits. by using attach() the
estimator can be retrieved by providing the training job name.

_prepare_init_params_from_job_description() is now a classmethod instead
of being a static method. Each class is responsible to implement their
specific logic to convert a training job description into arguments that
can be passed to its own __init__()

* Fix Estimator role expansion (aws#68)

Instead of manually constructing the role ARN, use the IAM boto client
to do it. This properly expands service-roles and regular roles.

* Add FM and LDA to the documentation. (aws#66)

* Fix description of an argument of sagemaker.session.train (aws#69)

* Fix description of an argument of sagemaker.session.train

'input_config' should be an array which has channel objects.

* Add a link to the botocore docs

* Use 'list' instead of 'array' in the description

* Add ntm algorithm with doc, unit tests, integ tests (aws#73)

* JSON serializer: predictor.predict accepts dictionaries (aws#62)

Add support for serializing python dictionaries to json
Add prediction with dictionary in tf iris integ test

* Fixing timeouts for PCA async integration test. (aws#78)

Execute tf_cifar test without logs to eliminate delay to detect that job has finished.

* Fixes in LinearLearner and unit tests addition. (aws#77)

* Print out billable seconds after training completes (aws#30)

* Added: print out billable seconds after training completes

* Fixed: test_session.py to pass unit tests

* Fixed: removed offending tzlocal()

* Use sagemaker_timestamp when creating endpoint names in integration tests. (aws#81)

* Support TensorFlow-1.5.0 and MXNet-1.0.0  (aws#82)

* Update .gitignore to ignore pytest_cache.

* Support TensorFlow-1.5.0 and MXNet-1.0.0

* Update and refactor tests. Add tests for fw_utils.

* Fix typo.

* Update changelog for 1.1.0 (aws#85)
@iquintero iquintero deleted the service_role branch April 2, 2018 00:05
apacker pushed a commit to apacker/sagemaker-python-sdk that referenced this pull request Nov 15, 2018
Updated: XGBoost direct marketing notebook markdown at the end
Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment

Labels

None yet

Projects

None yet

Development

Successfully merging this pull request may close these issues.

creating estimator with role name fails if role is default sagemaker service role

2 participants

Morty Proxy This is a proxified and sanitized view of the page, visit original site.