sample.json

{
 "guid": "82e7612f-2810-4d12-9c75-c17fcbb946fa",
 "name": "Intel® Neural Compressor Accelerate Inference with Intel® Optimization for TensorFlow*",
 "categories": ["Toolkit/oneAPI AI And Analytics/Getting Started"],
 "description": "This sample illustrates how to run Intel® Neural Compressor to quantize the FP32 model trained by Keras on Tensorflow to INT8 model to speed up the inference.",
 "languages": [{"python":{}}],
 "dependencies": ["tensorflow","neural-compressor"],
 "os": ["linux"],
 "builder": ["cli"],
 "targetDevice": ["CPU"],
 "ciTests": {
	"linux": [
	{
		"env": ["source /intel/oneapi/intelpython/bin/activate",
				"conda activate tensorflow",
				"pip install uv",
				"uv init",
				"uv python pin $(which python)",
				"uv venv --system-site-packages",
				"uv add -r requirements.txt",
				"uv add flatbuffers",
				"uv add neural-compressor",
				"pip install notebook",
				"uv add --dev ipykernel",
				"uv run ipython kernel install --user --name tensorflow"

        ],
		"id": "neural-compressor tensorflow",
		"steps": [
			"jupyter nbconvert --ExecutePreprocessor.enabled=True --ExecutePreprocessor.kernel_name=tensorflow --to notebook inc_sample_tensorflow.ipynb"
		 ]
	}
    ]
 },
 "expertise": "Getting Started"
}