sample.json

{
    "guid": "7B206827-2FAD-4D02-87D8-95E611D603EF",
    "name": "Leveraging Intel Extension for TensorFlow with LSTM for Text Generation",
    "categories": ["Toolkit/oneAPI AI And Analytics/Features and Functionality"],
    "description": "This sample demonstrates how to train your model with LSTM (Long short-term memory) faster by using Intel Extension for TensorFlow's LSTM training layer on Intel platform",
    "builder": ["cli"],
    "toolchain": ["jupyter"],
    "languages": [{"python":{}}],
    "os": ["linux"],
    "targetDevice": ["GPU"],
    "gpuRequired": ["pvc"],
    "ciTests": {
      "linux": [
        {
            "env": [
                "source /intel/oneapi/intelpython/bin/activate",
                "conda activate tensorflow-gpu",
                "pip install uv notebook",
                "uv init",
                "uv python pin $(which python)",
                "uv venv --system-site-packages",
                "uv add -r requirements.txt",
                "uv add --dev ipykernel",
                "uv run ipython kernel install --user --name=tensorflow-gpu"
            ],
            "id": "inc_text_generation_lstm_py",
            "steps": [
                "export ITEX_ENABLE_NEXTPLUGGABLE_DEVICE=0",
                "ITEX_NUM_EPOCHS=5 KERAS_NUM_EPOCHS=5 uv run TextGenerationModelTraining.py"
             ]
        }
      ]
    },
    "expertise": "Concepts and Functionality"
}