sample.json

{
    "guid": "A4D97FA0-D515-4944-9970-C6742A85257F",
    "name": "Intel® Extension for PyTorch* Training Optimizations for Bfloat16",
    "categories": ["Toolkit/oneAPI AI And Analytics/Features and Functionality"],
    "description": "This sample illustrates how to train a PyTorch model using Advanced Matrix Extensions Bfloat16",
    "builder": ["cli"],
    "languages": [{"python":{}}],
    "os":["linux"],
    "targetDevice": ["CPU"],
    "cpuInstructionSets": ["AVX512", "AMX"],
    "ciTests": {
      "linux": [
      {
          "env": [
            "source /intel/oneapi/intelpython/bin/activate",
            "conda activate pytorch",
            "pip install uv",
            "uv python pin $(which python)",
            "uv venv --system-site-packages",
            "uv sync",
            "uv run ipython kernel install --user --name pytorch"
          ],
          "id": "intel amx bf16 training",
          "steps": [
            "uv run python pytorch_training_avx512_bf16.py",
            "uv run python pytorch_training_amx_bf16.py",
            "uv run jupyter nbconvert --ExecutePreprocessor.enabled=True --ExecutePreprocessor.kernel_name=pytorch --to notebook IntelPyTorch_TrainingOptimizations_AMX_BF16.ipynb"
           ]
      }
       ]
    },
    "expertise": "Code Optimization"
  }