Uv conversion getting started (#3)

* uv for getting_started_with_intel_neural_compressor_for_quantization

* install uv on getting_started_with_intel_neural_compressor_for_quantization

* uv for intel_neural_compressor_accelerate_inference_with_intel_optimization_for_tensorflow

* uv for intel_extension_for_scikit_learn_getting_started

* Addin toml for intel_extension_for_tensorflow_getting_started

* uv for intel_extension_for_tensorflow_getting_started

Author: aemorabr

AI-and-Analytics/Getting-Started-Samples/INC-Quantization-Sample-for-PyTorch/pyproject.toml

@@ -0,0 +1,36 @@
+[project]
+name = "getting_started_with_intel_neural_compressor_for_quantization"
+version = "0.1.0"
+description = "This sample is a getting started guide for Intel® Neural Compressor to do INT8 quantization on a Huggingface BERT model. This allows us to achieve performance boosts on Intel hardware."
+authors = [
+    {name = "Copyright © 2023 Intel Corporation"}
+]
+license = {text = "MIT"}
+readme = "README.MD"
+requires-python = ">=3.11.11"
+dependencies = [
+    "datasets>=3.3.2",
+    "intel-extension-for-pytorch==2.5.0",
+    "neural-compressor==2.1",
+    "torch==2.5.0",
+    "transformers>=4.49.0",
+]
+
+[tool.uv.sources]
+torch = { index = "pytorch" }
+
+[dependency-groups]
+dev = [
+    "ipykernel>=6.29.5",
+    "jupyter>=1.1.1",
+]
+
+[[tool.uv.index]]
+url = "https://software.repos.intel.com/python/pypi"
+
+[[tool.uv.index]]
+name = "pytorch"
+# Required URL for the index.
+url = "https://download.pytorch.org/whl/cpu"
+explicit = true
+

AI-and-Analytics/Getting-Started-Samples/INC-Quantization-Sample-for-PyTorch/sample.json

@@ -11,15 +11,13 @@
       "linux": [
       {
           "env": ["apt-get update && apt-get install -y libgl1 libgl1-mesa-glx libglib2.0-0 libsm6 libxrender1 libxext6",
-            "source /intel/oneapi/intelpython/bin/activate",
-            "conda activate pytorch",
-            "pip install -r requirements.txt",
-            "pip install ipykernel jupyter",
-            "python -m ipykernel install --user --name=pytorch"
+            "pip install uv==0.6.3", 
+            "uv sync",
+            "uv run ipython kernel install --user --env VIRTUAL_ENV $(pwd)/.venv --name=pytorch-inc"
           ],
           "id": "quantize with inc",
           "steps": [
-              "jupyter nbconvert --ExecutePreprocessor.enabled=True --ExecutePreprocessor.kernel_name=pytorch --to notebook quantize_with_inc.ipynb"
+              "uv run jupyter nbconvert --ExecutePreprocessor.enabled=True --ExecutePreprocessor.kernel_name=pytorch-inc --to notebook quantize_with_inc.ipynb"
            ]
       }
        ]

AI-and-Analytics/Getting-Started-Samples/INC-Quantization-Sample-for-PyTorch/uv.lock

@@ -0,0 +1,21 @@
+[project]
+name = "intel_neural_compressor_accelerate_inference_with_intel_optimization_for_tensorflow"
+version = "0.1.0"
+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."
+authors = [
+    {name = "Copyright © 2023 Intel Corporation"}
+]
+license = {text = "MIT"}
+readme = "README.md"
+requires-python = ">=3.11"
+dependencies = [
+    "intel-extension-for-tensorflow[cpu]==2.15",
+    "matplotlib>=3.10.1",
+    "neural-compressor==3.1.1",
+]
+
+[dependency-groups]
+dev = [
+    "ipykernel>=6.29.5",
+    "jupyter>=1.1.1",
+]

AI-and-Analytics/Getting-Started-Samples/INC-Sample-for-Tensorflow/pyproject.toml

@@ -11,17 +11,14 @@
  "ciTests": {
 	"linux": [
 	{
-		"env": ["source /intel/oneapi/intelpython/bin/activate",
-				"conda activate tensorflow",
-				"conda install -n tensorflow -c conda-forge python-flatbuffers -y",
-				"conda install -n tensorflow -c https://software.repos.intel.com/python/conda/ -c conda-forge neural-compressor -y",
-				"conda install -n tensorflow -y",
-				"pip install jupyter ipykernel",
-				"python -m ipykernel install --user --name=tensorflow"
+		"env": [
+			"pip install uv==0.6.3", 
+            "uv sync",
+            "uv run ipython kernel install --user --env VIRTUAL_ENV $(pwd)/.venv --name=tensorflow-inc-quantize"
         ],
 		"id": "neural-compressor tensorflow",
 		"steps": [
-			"jupyter nbconvert --ExecutePreprocessor.enabled=True --ExecutePreprocessor.kernel_name=tensorflow --to notebook inc_sample_tensorflow.ipynb"
+			"uv run jupyter nbconvert --ExecutePreprocessor.enabled=True --ExecutePreprocessor.kernel_name=tensorflow-inc-quantize --to notebook inc_sample_tensorflow.ipynb"
 		 ]
 	}
     ]

AI-and-Analytics/Getting-Started-Samples/INC-Sample-for-Tensorflow/sample.json

@@ -0,0 +1,22 @@
+[project]
+name = "intel_extension_for_scikit_learn_getting_started"
+version = "0.1.0"
+description= "This sample illustrates how to do Image classification using SVM classifier from Python API package SKlearnex with the use of Intel® oneAPI Data Analytics Library (oneDAL)."
+authors = [
+    {name = "Copyright © 2023 Intel Corporation"}
+]
+license = {text = "MIT"}
+readme = "README.md"
+requires-python = ">=3.11"
+dependencies = [
+    "joblib>=1.4.2",
+    "matplotlib>=3.10.1",
+    "scikit-learn==1.5.2",
+    "scikit-learn-intelex>=2025.2.0",
+]
+
+[dependency-groups]
+dev = [
+    "ipykernel>=6.29.5",
+    "jupyter>=1.1.1",
+]

AI-and-Analytics/Getting-Started-Samples/INC-Sample-for-Tensorflow/uv.lock

@@ -13,13 +13,12 @@
 	"ciTests": {
 		"linux": [{
 			"env": [
-				"source /intel/oneapi/intelpython/bin/activate",
-				"conda activate base",
-				"pip install -r requirements.txt"
+				"pip install uv==0.6.3", 
+				"uv sync"
 			],
 			"id": "idp_sklex_gs_py",
 			"steps": [
-				"python Intel_Extension_For_SKLearn_GettingStarted.py"
+				"uv run Intel_Extension_For_SKLearn_GettingStarted.py"
 			]
 		}]
 	},