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Google colab updates. Documentation updates, verifaction script updat…
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* Google colab updates. Documentation updates, verifaction script updates

Signed-off-by: Joel Polizzi <quic_jpolizzi@quicinc.com>

* Correct typos and provide further documentation comments

Signed-off-by: Joel Polizzi <quic_jpolizzi@quicinc.com>

---------

Signed-off-by: Joel Polizzi <quic_jpolizzi@quicinc.com>
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quic-jpolizzi authored Feb 26, 2024
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330 changes: 330 additions & 0 deletions packaging/google_colab/Install_AIMET_GoogleColab.ipynb
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{
"cells": [
{
"cell_type": "markdown",
"metadata": {
"id": "783-amyMv50Y"
},
"source": [
"# Aimet Installation and test\n",
"Welcome to aimet!\n",
"This colab environment can be used to experiment with aimet.\n",
"If you are testing a GPU variant of aimet you will need to select a T4 GPU runtime from the dropdown menu to the right.\n",
"\n",
"*Please note there are limitations in Google Colab and this is documented for short and quick aimet tests and not intended to be leveraged for any production purpose."
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "xlxmatutwx2L"
},
"source": [
"To get started we first will run this cell to install the proper conda environment."
]
},
{
"cell_type": "code",
"execution_count": 63,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "8YVW5OljfovQ",
"outputId": "752f91d6-c680-479e-c438-756bd8e97e83"
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"['Python 3.8.3']\n"
]
}
],
"source": [
"python_ver = !python --version\n",
"print(python_ver)\n",
"if('Python 3.8' not in python_ver[0]):\n",
" print(python_ver)\n",
" !wget -O mini.sh https://repo.anaconda.com/miniconda/Miniconda3-py38_4.8.3-Linux-x86_64.sh\n",
" !chmod +x mini.sh\n",
" !bash ./mini.sh -b -f -p /usr/local\n",
" !conda install -q -y jupyter\n",
" !conda install -q -y google-colab -c conda-forge\n",
" !python -m ipykernel install --user --name=\"py38\""
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "9I3_ZZ45xAIH"
},
"source": [
"Here you can see that when calling python through bash we can access python 3.8, which is required for aimet."
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"id": "5Ol64M4Lfue_"
},
"outputs": [],
"source": [
"!which python\n",
"!echo $PYTHONPATH\n",
"import sys\n",
"!python -c \"import sys; print(sys.version)\"\n",
"print(sys.version)"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "Gpvyh4SvxMwr"
},
"source": [
"Next, we will set our PYTHONPATH environment variable"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"id": "6cuOtbfShwdX"
},
"outputs": [],
"source": [
"%env PYTHONPATH=\"/env/python:/usr/local/lib/python3.8/site-packages\""
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "scCYapn-yH7X"
},
"source": [
"Here we will set the aimet variant and release_tag we are using.\n",
"Variants can be found in the Aimet documentation: https://quic.github.io/aimet-pages/releases/latest/install/index.html\n",
"\n",
"Release tags can be found here: https://github.com/quic/aimet/releases"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {
"id": "EBPO13XxiDQo"
},
"outputs": [],
"source": [
"import os\n",
"os.environ[\"AIMET_VARIANT\"] = \"torch_gpu\"\n",
"os.environ[\"release_tag\"] = \"1.28.0\""
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "QpTw20v5kBS6"
},
"source": [
"Now we will remove the existing nvidia-ml.list and nvidia-machine-learning.list and replace it in our install script\n",
"* You may skip this step when using a cpu variant"
]
},
{
"cell_type": "code",
"execution_count": 64,
"metadata": {
"id": "1CLd8BMqoyyz"
},
"outputs": [],
"source": [
"!rm -rf /etc/apt/sources.list.d/nvidia-ml.list /etc/apt/sources.list.d/nvidia-machine-learning.list"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"id": "nGpT1h7as9Xx"
},
"outputs": [],
"source": [
"!apt-get update"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "BsKtA8N0kUYO"
},
"source": [
"Lets wget o"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"id": "tp0aU80aUw6H"
},
"outputs": [],
"source": [
"!git clone https://github.com/quic/aimet.git"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "a6b2OFtqkaR2"
},
"source": [
"This script will run our installation based on th3e variables we provided in earlier steps"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "rNqBqhzey3hJ"
},
"source": [
"Run the installation script"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"id": "tLZ3-M0ajkVn"
},
"outputs": [],
"source": [
"\n",
"!/bin/bash aimet/develop/packaging/verification/aimet-os-install.sh"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "QSNlJS8r0Ptj"
},
"source": [
"In order to acces our environment inside colab we need to use the %%bash magic command to call python in the cell. Lets test some imports"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"id": "T9bHRI6Allmh"
},
"outputs": [],
"source": [
"%%bash\n",
"sh /usr/local/lib/python3.8/site-packages/aimet_common/bin/envsetup.sh\n",
"python -c \"\n",
"\n",
"from aimet_common.defs import QuantScheme\n",
"import aimet_common.defs as aimet_common_defs\n",
"import aimet_common.libpymo as libpymo\n",
"\n",
"import torch\n",
"from aimet_torch.quantsim import QuantizationSimModel\n",
"from aimet_torch.compress import ModelCompressor\n",
"\n",
"from aimet_torch.adaround.adaround_weight import Adaround, AdaroundParameters\n",
"from aimet_torch.batch_norm_fold import fold_all_batch_norms\n",
"from aimet_torch.quantsim import QuantizationSimModel\n",
"\n",
"\""
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "7mA-M7y7UxlS"
},
"source": [
"Now that we can import Aimet lets install pytest and run one of our tests"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"id": "iOPur82rbqwV"
},
"outputs": [],
"source": [
"!pip install pytest"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "lOJO6i6hoQ5n"
},
"source": [
"Lets run our tests from the test directory and create our data directory"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"id": "aflR_DJCek8u"
},
"outputs": [],
"source": [
"if os.getcwd() != os.path.abspath(\"/content/aimet/TrainingExtensions/torch/test/python\"):\n",
" os.chdir(\"aimet/TrainingExtensions/torch/test/python\")\n",
"else:\n",
" print(\"Already located at aimet/TrainingExtensions/torch/test/python\")\n",
"\n",
"if not os.path.exists(\"./data\"):\n",
" os.mkdir(\"./data\")\n",
"else:\n",
" print(\"Path exists\")\n"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "R2NT7yA5pRRX"
},
"source": [
"Lets run a quantizer test for torch gpu"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"id": "j95Nuz_DatK3"
},
"outputs": [],
"source": [
"!pytest test_quantizer_GPU.py"
]
}
],
"metadata": {
"accelerator": "GPU",
"colab": {
"gpuType": "T4",
"provenance": []
},
"kernelspec": {
"display_name": "Python 3",
"name": "python3"
},
"language_info": {
"name": "python"
}
},
"nbformat": 4,
"nbformat_minor": 0
}
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