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remove checking vs existing for pytorch quantization (openvinotoolkit#1799)
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‎notebooks/112-pytorch-post-training-quantization-nncf/112-pytorch-post-training-quantization-nncf.ipynb

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{
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"cells": [
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{
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"attachments": {},
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"> **NOTE**: This notebook requires that a C++ compiler is accessible on the default binary search path of the OS you are running the notebook.\n",
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"\n",
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"\n",
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"#### Table of contents:\n\n",
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"#### Table of contents:\n",
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"\n",
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"- [Preparations](#Preparations)\n",
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" - [Imports](#Imports)\n",
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" - [Settings](#Settings)\n",
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]
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},
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{
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"attachments": {},
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"outputs": [],
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"source": [
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"# Install openvino package\n",
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"%pip install -q \"openvino>=2023.1.0\" torch torchvision --extra-index-url https://download.pytorch.org/whl/cpu\n",
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"%pip install -q \"nncf>=2.6.0\""
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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": 2,
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"metadata": {
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"scrolled": true,
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"tags": []
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},
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"outputs": [],
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"source": [
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"# On Windows, this script adds the directory that contains cl.exe to the PATH to enable PyTorch to find the\n",
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"# required C++ tools. This code assumes that Visual Studio 2019 is installed in the default\n",
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"# directory. If you have a different C++ compiler, add the correct path to os.environ[\"PATH\"]\n",
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"# directly.\n",
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"\n",
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"# Adding the path to os.environ[\"LIB\"] is not always required - it depends on the system configuration.\n",
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"\n",
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"import sys\n",
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"\n",
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"if sys.platform == \"win32\":\n",
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" import distutils.command.build_ext\n",
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" import os\n",
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" from pathlib import Path\n",
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"\n",
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" VS_INSTALL_DIR = r\"C:/Program Files (x86)/Microsoft Visual Studio\"\n",
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" cl_paths = sorted(list(Path(VS_INSTALL_DIR).glob(\"**/Hostx86/x64/cl.exe\")))\n",
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" if len(cl_paths) == 0:\n",
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" raise ValueError(\n",
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" \"Cannot find Visual Studio. This notebook requires C++. If you installed \"\n",
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" \"a C++ compiler, please add the directory that contains cl.exe to \"\n",
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" \"`os.environ['PATH']`\"\n",
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" )\n",
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" else:\n",
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" # If multiple versions of MSVC are installed, get the most recent one.\n",
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" cl_path = cl_paths[-1]\n",
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" vs_dir = str(cl_path.parent)\n",
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" os.environ[\"PATH\"] += f\"{os.pathsep}{vs_dir}\"\n",
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" # The code for finding the library dirs is from\n",
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" # https://stackoverflow.com/questions/47423246/get-pythons-lib-path\n",
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" d = distutils.core.Distribution()\n",
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" b = distutils.command.build_ext.build_ext(d)\n",
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" b.finalize_options()\n",
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" os.environ[\"LIB\"] = os.pathsep.join(b.library_dirs)\n",
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" print(f\"Added {vs_dir} to PATH\")"
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"%pip install -q \"openvino>=2024.0.0\" torch torchvision --extra-index-url https://download.pytorch.org/whl/cpu\n",
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"%pip install -q \"nncf>=2.9.0\""
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]
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},
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{
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"attachments": {},
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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]
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},
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"attachments": {},
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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]
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},
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{
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"attachments": {},
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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]
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},
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{
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"attachments": {},
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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]
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},
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"attachments": {},
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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]
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},
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"attachments": {},
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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]
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},
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"attachments": {},
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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]
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},
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{
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"attachments": {},
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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]
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},
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"attachments": {},
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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]
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},
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{
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"attachments": {},
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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]
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},
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{
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"attachments": {},
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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]
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},
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{
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"attachments": {},
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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]
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},
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{
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"attachments": {},
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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]
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},
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{
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"attachments": {},
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"It should be noted that the inference time for the quantized PyTorch model is longer than that of the original model, as fake quantizers are added to the model by NNCF. However, the model's performance will significantly improve when it is in the OpenVINO Intermediate Representation (IR) format."
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]
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},
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{
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"attachments": {},
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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]
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},
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"attachments": {},
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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]
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},
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{
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"attachments": {},
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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]
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},
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"attachments": {},
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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]
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},
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"attachments": {},
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"provenance": []
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},
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"kernelspec": {
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"display_name": "Python 3",
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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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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.11.5"
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"version": "3.8.10"
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},
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"openvino_notebooks": {
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"imageUrl": "",
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},
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"widgets": {
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"GPU",
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"AUTO"
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],
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"layout": "IPY_MODEL_5ba51a4155a94f2f9b2021414519d2fd",
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"style": "IPY_MODEL_88897c3f697f4cef82e9b7c3e0064fa4"
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"state": {},
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}
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"nbformat": 4,
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