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Convert python samples to use UV with uv.lock and .toml files also remove conda dependency #2610

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Convert python samples to use UV with uv.lock and .toml files also remove conda dependency #2610

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767bc89
Uv conversion getting started (#3)
aemorabr Mar 5, 2025
eaceca8
Merge branch 'oneapi-src:development' into development
eleemhui Mar 6, 2025
913084a
UV conversion Features-and-Functionality dir (#2)
eleemhui Mar 6, 2025
07b7e69
Merge branch 'oneapi-src:development' into development
eleemhui Mar 8, 2025
459902a
merge upstream
eleemhui Apr 2, 2025
ffcd7ea
Pr1 fixes (#6)
eleemhui Apr 11, 2025
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28 changes: 5 additions & 23 deletions ..._GPU_InferenceOptimization_with_AMP/IntelPyTorch_GPU_InferenceOptimization_with_AMP.ipynb
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Expand Up @@ -296,7 +296,7 @@
},
{
"cell_type": "markdown",
"id": "0d6d8fb4-983b-417f-88c3-dc2747de3d4a",
"id": "415587fc",
"metadata": {},
"source": [
"### Model Training on CPU(Optional, if device is CPU) "
Expand All @@ -305,7 +305,7 @@
{
"cell_type": "code",
"execution_count": null,
"id": "1ff86b79-9bc8-4e6e-8d43-b2cfa1eb500f",
"id": "69093d44",
"metadata": {},
"outputs": [],
"source": [
Expand Down Expand Up @@ -518,7 +518,7 @@
},
{
"cell_type": "markdown",
"id": "87063fd1",
"id": "7f5ef9d6",
"metadata": {},
"source": [
"Model Evaluation on CPU(optional, if trained on CPU)"
Expand All @@ -527,7 +527,7 @@
{
"cell_type": "code",
"execution_count": null,
"id": "8a59b600",
"id": "c84c5b1e",
"metadata": {},
"outputs": [],
"source": [
Expand Down Expand Up @@ -616,25 +616,7 @@
]
}
],
"metadata": {
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.9.15"
},
"vscode": {
"interpreter": {
"hash": "ed6ae0d06e7bec0fef5f1fb38f177ceea45508ce95c68ed2f49461dd6a888a39"
}
}
},
"metadata": {},
"nbformat": 4,
"nbformat_minor": 5
}
32 changes: 32 additions & 0 deletions ...Features-and-Functionality/IntelPyTorch_GPU_InferenceOptimization_with_AMP/pyproject.toml
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@@ -0,0 +1,32 @@
[project]
name = "intel_pytorch_gpu_inference_optimization_with_amp"
version = "0.1.0"
description = "This sample illustrates how to use AMP BFLOAT16 in PyTorch on Intel dGPU"
authors = [
{name = "Copyright © 2023 Intel Corporation"}
]
license = {text = "MIT"}
readme = "README.md"
requires-python = ">=3.11,<3.12"
dependencies = [
"deepspeed==0.15.4",
"intel-extension-for-pytorch==2.5.10",
"matplotlib>=3.10.1",
"neural-compressor==3.1.1",
"numpy==1.26.4",
"oneccl-bind-pt==2.5.0",
"requests>=2.32.3",
"torch==2.5.1",
"torchaudio==2.5.1",
"torchvision==0.20.1",
"tqdm>=4.67.1",
]


[dependency-groups]
dev = [
"jupyter>=1.1.1",
]

[[tool.uv.index]]
url = "https://pytorch-extension.intel.com/release-whl/stable/xpu/cn/"
13 changes: 5 additions & 8 deletions ...cs/Features-and-Functionality/IntelPyTorch_GPU_InferenceOptimization_with_AMP/sample.json
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Expand Up @@ -13,15 +13,12 @@
{
"id": "intel pytorch gpu inference optimization with amp",
"steps": [
"source /intel/oneapi/intelpython/bin/activate",
"source activate pytorch-gpu",
"pip install -r requirements.txt",
"pip install jupyter ipykernel",
"python -m ipykernel install --user --name=pytorch-gpu",
"python IntelPyTorch_GPU_InferenceOptimization_with_AMP.py"
]
"pip install uv==0.6.3",
"uv sync",
"uv run jupyter nbconvert --ExecutePreprocessor.enabled=True --to notebook IntelPyTorch_GPU_InferenceOptimization_with_AMP.ipynb"
]
}
]
]
},
"expertise": "Code Optimization"
}
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2,285 changes: 2,285 additions & 0 deletions ...lytics/Features-and-Functionality/IntelPyTorch_GPU_InferenceOptimization_with_AMP/uv.lock
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51 changes: 11 additions & 40 deletions ...lPyTorch_TrainingOptimizations_AMX_BF16/IntelPyTorch_TrainingOptimizations_AMX_BF16.ipynb
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Expand Up @@ -127,9 +127,7 @@
"id": "2f7486b6",
"metadata": {},
"outputs": [],
"source": [
"os.environ[\"ONEDNN_MAX_CPU_ISA\"] = \"AVX512_CORE_BF16\""
]
"source": []
},
{
"cell_type": "code",
Expand All @@ -152,6 +150,13 @@
" training_time: the time in seconds it takes to train the model\n",
" \"\"\"\n",
"\n",
" if amx:\n",
" # Set the environment variable to enable Intel® AMX\n",
" os.environ[\"ONEDNN_MAX_CPU_ISA\"] = \"AVX512_CORE_AMX\"\n",
" else:\n",
" # Set the environment variable to disable Intel® AMX\n",
" os.environ[\"ONEDNN_MAX_CPU_ISA\"] = \"AVX512_CORE_BF16\"\n",
"\n",
" # Initialize the model \n",
" model = torchvision.models.resnet50()\n",
" model = model.to(memory_format=torch.channels_last)\n",
Expand Down Expand Up @@ -265,18 +270,7 @@
"outputs": [],
"source": [
"print(\"Training model with BF16 with AVX512\")\n",
"!python pytorch_training_avx512_bf16.py"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "a9bd6dec",
"metadata": {},
"outputs": [],
"source": [
"# Record the training time for BF16 using AVX512\n",
"bf16_avx512_training_time = None #TODO: enter in training time"
"bf16_avx512_training_time = trainModel(train_loader, amx=False, modelName=\"bf16_withAmx\", dataType=\"bf16\")"
]
},
{
Expand All @@ -287,7 +281,7 @@
"outputs": [],
"source": [
"print(\"Training model with BF16 with Intel® AMX\")\n",
"bf16_amx_training_time = trainModel(train_loader, modelName=\"bf16_withAmx\", dataType=\"bf16\")"
"bf16_amx_training_time = trainModel(train_loader, amx=True, modelName=\"bf16_noAmx\", dataType=\"bf16\")"
]
},
{
Expand Down Expand Up @@ -389,30 +383,7 @@
]
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3.8.10 64-bit (microsoft store)",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.8.10"
},
"vscode": {
"interpreter": {
"hash": "ed6ae0d06e7bec0fef5f1fb38f177ceea45508ce95c68ed2f49461dd6a888a39"
}
}
},
"metadata": {},
"nbformat": 4,
"nbformat_minor": 5
}
45 changes: 45 additions & 0 deletions ...ics/Features-and-Functionality/IntelPyTorch_TrainingOptimizations_AMX_BF16/pyproject.toml
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@@ -0,0 +1,45 @@
[project]
name = "intelpytorch-trainingoptimizations-amx-bf16"
version = "0.1.0"
description = "This sample illustrates how to train a PyTorch model using Advanced Matrix Extensions Bfloat16"
authors = [
{name = "Copyright © 2020 Intel Corporation"}
]
license = {text = "MIT"}
readme = "README.md"
requires-python = ">=3.11,<3.12"
dependencies = [
"deepspeed==0.15.4",
"intel-extension-for-pytorch==2.5.0",
"ipykernel>=6.29.5",
"ipywidgets>=8.1.5",
"jupyter>=1.1.1",
"matplotlib>=3.10.1",
"neural-compressor==3.1.1",
"numpy==1.26.4",
"onnxruntime==1.19.2",
"py-cpuinfo>=9.0.0",
"setuptools>=75.8.2",
"torch==2.5.0",
"torchaudio==2.5.0",
"torchvision>=0.20.0",
"transformers>=4.49.0",
]

[tool.uv.sources]
torch = { index = "pytorch" }
torchvision = { index = "pytorch" }

[[tool.uv.index]]
name = "pytorch"
# Required URL for the index.
url = "https://download.pytorch.org/whl/cpu"
explicit = true

[[tool.uv.index]]
url = "https://software.repos.intel.com/python/pypi"

[dependency-groups]
dev = [
"jupyter>=1.1.1",
]
10 changes: 3 additions & 7 deletions ...lytics/Features-and-Functionality/IntelPyTorch_TrainingOptimizations_AMX_BF16/sample.json
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Expand Up @@ -13,13 +13,9 @@
{
"id": "intel amx bf16 training",
"steps": [
"source /intel/oneapi/intelpython/bin/activate",
"conda activate pytorch",
"python -m pip install -r requirements.txt",
"python -m ipykernel install --user --name=pytorch",
"python pytorch_training_avx512_bf16.py",
"python pytorch_training_amx_bf16.py",
"jupyter nbconvert --ExecutePreprocessor.enabled=True --ExecutePreprocessor.kernel_name=pytorch --to notebook IntelPyTorch_TrainingOptimizations_AMX_BF16.ipynb"
"pip install uv==0.6.3",
"uv sync",
"uv run jupyter nbconvert --ExecutePreprocessor.enabled=True --to notebook IntelPyTorch_TrainingOptimizations_AMX_BF16.ipynb"
]
}
]
Expand Down
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