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Commit 9713a4c

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kushalkolarkushalkolar
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nb to explore garbage collection
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‎examples/garbage_collection.ipynb

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{
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"cells": [
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "1ef0578e-09e1-45ff-bd34-84472db3885e",
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"metadata": {
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"tags": []
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},
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"outputs": [],
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"source": [
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"from fastplotlib import Plot\n",
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"import numpy as np\n",
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"import sys\n",
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"\n",
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"import weakref\n",
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"import gc\n",
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"import os, psutil\n",
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"process = psutil.Process(os.getpid())"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "1bb6bc6f-7786-4d23-9eb1-e30bbc66c798",
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"metadata": {},
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"outputs": [],
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"source": [
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"print(process.memory_info().rss / 1024 / 1024)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "b23ba640-88ec-40d9-b53c-c8cbb3e39b0b",
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"metadata": {},
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"outputs": [],
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"source": [
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"plot = Plot()\n",
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"\n",
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"# a = np.random.rand(5_000_000)\n",
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"# plot.add_line(a)\n",
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"\n",
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"\n",
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"plot.show()"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "17f46f21-b29d-4dd3-9496-989bbb240f50",
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"metadata": {},
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"outputs": [],
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"source": [
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"print(process.memory_info().rss / 1024 / 1024)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "e26d392f-6afd-4e89-a685-d618065d3caf",
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"metadata": {},
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"outputs": [],
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"source": [
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"a = np.random.rand(1_000, 5_000)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "31e3027a-56cf-4f7b-ba78-aed4f78eef47",
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"metadata": {},
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"outputs": [],
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"source": [
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"print(process.memory_info().rss / 1024 / 1024)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "9cf2ceaa-5b01-4e12-be39-f267cd355833",
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"metadata": {},
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"outputs": [],
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"source": [
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"plot.add_line_stack(a)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "53170858-ae72-4451-8647-7d5b1f9da75e",
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"metadata": {},
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"outputs": [],
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"source": [
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"print(process.memory_info().rss / 1024 / 1024)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "ee2481c9-82e3-4043-85fd-21a0cdf21187",
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"metadata": {},
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"outputs": [],
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"source": [
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"plot.auto_scale()"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "e4e0f73b-c58a-40e7-acf5-07a1f70d2821",
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"metadata": {},
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"outputs": [],
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"source": [
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"plot.delete_graphic(plot.graphics[0])"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "56c64498-229e-48b7-9fb1-f7c327fff2ae",
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"metadata": {},
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"outputs": [],
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"source": [
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"print(process.memory_info().rss / 1024 / 1024)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "dd6a26c1-ea81-469d-ae7a-95839b1f9d5a",
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"metadata": {},
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"outputs": [],
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"source": [
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"import numpy as np\n",
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"from wgpu.gui.auto import WgpuCanvas, run\n",
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"import pygfx as gfx\n",
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"import subprocess\n",
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"\n",
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"canvas = WgpuCanvas()\n",
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"renderer = gfx.WgpuRenderer(canvas)\n",
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"scene = gfx.Scene()\n",
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"camera = gfx.OrthographicCamera(5000, 5000)\n",
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"camera.position.x = 2048\n",
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"camera.position.y = 2048\n",
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"\n",
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"\n",
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"def make_image():\n",
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" data = np.random.rand(4096, 4096).astype(np.float32)\n",
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"\n",
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" return gfx.Image(\n",
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" gfx.Geometry(grid=gfx.Texture(data, dim=2)),\n",
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" gfx.ImageBasicMaterial(clim=(0, 1)),\n",
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" )\n",
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"\n",
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"\n",
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"class Graphic:\n",
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" def __init__(self):\n",
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" data = np.random.rand(4096, 4096).astype(np.float32)\n",
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" self.wo = gfx.Image(\n",
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" gfx.Geometry(grid=gfx.Texture(data, dim=2)),\n",
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" gfx.ImageBasicMaterial(clim=(0, 1)),\n",
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" )\n",
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"\n",
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"\n",
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"def draw():\n",
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" renderer.render(scene, camera)\n",
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" canvas.request_draw()\n",
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"\n",
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"\n",
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"def print_nvidia(msg):\n",
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" print(msg)\n",
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" print(\n",
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" subprocess.check_output([\"nvidia-smi\", \"--format=csv\", \"--query-gpu=memory.used\"]).decode().split(\"\\n\")[1]\n",
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" )\n",
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" print()\n",
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"\n",
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"\n",
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"def add_img(*args):\n",
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" print_nvidia(\"Before creating image\")\n",
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" img = make_image()\n",
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" print_nvidia(\"After creating image\")\n",
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" scene.add(img)\n",
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" img.add_event_handler(remove_img, \"click\")\n",
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" draw()\n",
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" print_nvidia(\"After add image to scene\")\n",
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"\n",
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"\n",
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"def remove_img(*args):\n",
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" img = scene.children[0]\n",
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" scene.remove(img)\n",
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" draw()\n",
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" print_nvidia(\"After remove image from scene\")\n",
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" del img\n",
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" draw()\n",
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" print_nvidia(\"After del image\")\n",
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"\n",
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"\n",
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"renderer.add_event_handler(add_img, \"double_click\")\n",
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"canvas"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "2599f430-8b00-4490-9e11-774897be6e77",
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"metadata": {},
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"outputs": [],
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"source": [
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"import numpy as np\n",
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"from wgpu.gui.auto import WgpuCanvas, run\n",
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"import pygfx as gfx\n",
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"import subprocess\n",
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"\n",
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"canvas = WgpuCanvas()\n",
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"renderer = gfx.WgpuRenderer(canvas)\n",
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"scene = gfx.Scene()\n",
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"camera = gfx.OrthographicCamera(5000, 5000)\n",
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"camera.position.x = 2048\n",
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"camera.position.y = 2048\n",
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"\n",
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"\n",
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"def make_image():\n",
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" data = np.random.rand(4096, 4096).astype(np.float32)\n",
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"\n",
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" return gfx.Image(\n",
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" gfx.Geometry(grid=gfx.Texture(data, dim=2)),\n",
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" gfx.ImageBasicMaterial(clim=(0, 1)),\n",
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" )"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "3ec10f26-6544-4ad3-80c1-aa34617dc826",
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"metadata": {},
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"outputs": [],
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"source": [
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"import weakref"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "acc819a3-cd50-4fdd-a0b5-c442d80847e2",
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"metadata": {},
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"outputs": [],
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"source": [
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"img = make_image()\n",
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"img_ref = weakref.ref(img)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "f89da335-3372-486b-b773-9f103d6a9bbd",
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"metadata": {},
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"outputs": [],
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"source": [
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"img_ref()"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "c22904ad-d674-43e6-83bb-7a2f7b277c06",
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"metadata": {},
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"outputs": [],
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"source": [
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"del img"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "573566d7-eb91-4690-958c-d00dd495b3e4",
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"metadata": {},
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"outputs": [],
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"source": [
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"import gc"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "aaef3e89-2bfd-43af-9b8f-824a3f89b85f",
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"metadata": {},
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"outputs": [],
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"source": [
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"img_ref()"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "3380f35e-fcc9-43f6-80d2-7e9348cd13b4",
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"metadata": {},
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"outputs": [],
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"source": [
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"draw()"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "a27bf7c7-f3ef-4ae8-8ecf-31507f8c0449",
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"metadata": {},
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"outputs": [],
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"source": [
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"print(\n",
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" subprocess.check_output([\"nvidia-smi\", \"--format=csv\", \"--query-gpu=memory.used\"]).decode().split(\"\\n\")[1]\n",
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" )"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "e4bf2711-8a83-4d9c-a4f7-f50de7ae1715",
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"metadata": {},
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"outputs": [],
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"source": []
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "Python 3 (ipykernel)",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.10.5"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 5
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}

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