sample.json

{
	"guid": "B213F6A4-E0C4-4268-8D0C-DDA5073A3F24",
	"name": "Performance_Analysis_using_model_zoo_for_Intel_Architecture",
	"categories": ["Toolkit/oneAPI AI And Analytics/Features And Functionality"],
	"description": "This sample contains one Jupyter notebook from this GitHub Repo and four Jupyter Notebooks from the Model Zoo for Intel® Architecture to help users analyze the performance difference among different Tensorflow enviroments such as Stock vs Intel.",
	"builder": ["cli"],
	"languages": [{
		"python": {}
	}],
	"os": ["linux"],
	"targetDevice": ["CPU"],
	"ciTests": {
		"linux": [{
			"id": "tensorflow_performance_analysis",
			"steps": [
				"pip install uv",
				"uv venv intel-tensorflow --python 3.10.12",
				"source intel-tensorflow/bin/activate",
				"uv sync --active",
				"uv run --active python -m ipykernel install --user --name=intel-tensorflow",
				"uv run --active jupyter nbconvert --to notebook --execute TF_PerfAnalysis.ipynb"
			]
		}]
	},
    "expertise": "Performance Analysis"
}