Use uv tool for isolate cicd env

AI-and-Analytics/End-to-end-Workloads/JobRecommendationSystem/JobRecommendationSystem.ipynb

@@ -904,6 +904,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
+    "import numpy as np\n",
     "import intel_extension_for_tensorflow as itex\n",
     "\n",
     "itex.experimental_ops_override()"

AI-and-Analytics/End-to-end-Workloads/JobRecommendationSystem/JobRecommendationSystem.py

@@ -428,6 +428,7 @@ def lemmatize_text(text):
 # Now, let us import Intel Extension for TensorFlow*. We are using Python API `itex.experimental_ops_override()`. It automatically replace some TensorFlow operators by Custom Operators under `itex.ops` namespace, as well as to be compatible with existing trained parameters.
 
 # %%
+import numpy as np
 import intel_extension_for_tensorflow as itex
 
 itex.experimental_ops_override()

AI-and-Analytics/End-to-end-Workloads/JobRecommendationSystem/pyproject.toml

@@ -0,0 +1,19 @@
+[project]
+name = "jobrecommendationsystem"
+version = "0.1.0"
+description = "Add your description here"
+readme = "README.md"
+requires-python = ">=3.11"
+dependencies = [
+    "accelerate>=1.4.0",
+    "datasets>=3.3.2",
+    "jinja2>=3.1.5",
+    "matplotlib>=3.10.1",
+    "nltk>=3.9.1",
+    "numpy==1.26.4",
+    "seaborn>=0.13.2",
+    "sentence-transformers>=3.4.1",
+    "spacy>=3.8.4",
+    "transformers>=4.49.0",
+    "wordcloud>=1.9.4",
+]

AI-and-Analytics/End-to-end-Workloads/JobRecommendationSystem/sample.json

@@ -15,12 +15,13 @@
         "id": "JobRecommendationSystem_py",
         "steps": [
           "source /intel/oneapi/intelpython/bin/activate",
-          "conda env remove -n user_tensorflow-gpu",
-          "conda create --name user_tensorflow-gpu --clone tensorflow-gpu",
-          "conda activate user_tensorflow-gpu",
-          "pip install -r requirements.txt",
-          "python -m ipykernel install --user --name=user_tensorflow-gpu",
-          "python JobRecommendationSystem.py"
+          "conda activate tensorflow-gpu",
+          "pip install uv",
+          "uv python pin $(which python)",
+          "uv venv --system-site-packages",
+          "uv sync",
+          "uv run python -m spacy download en_core_web_sm",
+          "uv run python JobRecommendationSystem.py"
         ]
       }
     ]

AI-and-Analytics/Features-and-Functionality/INC_QuantizationAwareTraining_TextClassification/pyproject.toml

@@ -0,0 +1,16 @@
+[project]
+name = "inc-quantizationawaretraining-textclassification"
+version = "0.1.0"
+description = "Add your description here"
+readme = "README.md"
+requires-python = ">=3.11"
+dependencies = [
+    "accelerate>=1.4.0",
+    "datasets>=3.3.2",
+    "evaluate>=0.4.3",
+    "neural-compressor>=3.2",
+    "optimum[neural-compressor]>=1.24.0",
+    "torch==2.5.0",
+    "torchvision==0.20.0",
+    "transformers>=4.45.2",
+]

AI-and-Analytics/Features-and-Functionality/INC_QuantizationAwareTraining_TextClassification/sample.json

@@ -14,11 +14,14 @@
             "env": [
                 "source /intel/oneapi/intelpython/bin/activate", 
                 "conda activate pytorch",
-                "pip install -r requirements.txt"
+                "pip install uv",
+                "uv python pin $(which python)",
+                "uv venv --system-site-packages",
+                "uv sync"
             ],
             "id": "inc_text_classification_quantization_py",
             "steps": [
-              "python INC_QuantizationAwareTraining_TextClassification.py"
+              "uv run INC_QuantizationAwareTraining_TextClassification.py"
              ]
         }
       ]

AI-and-Analytics/Features-and-Functionality/IntelPyTorch_GPU_InferenceOptimization_with_AMP/pyproject.toml

@@ -0,0 +1,12 @@
+[project]
+name = "intelpytorch-gpu-inferenceoptimization-with-amp"
+version = "0.1.0"
+description = "Add your description here"
+readme = "README.md"
+requires-python = ">=3.11"
+dependencies = [
+    "matplotlib>=3.10.1",
+    "numpy==1.26.4",
+    "requests>=2.32.3",
+    "tqdm>=4.67.1",
+]

AI-and-Analytics/Features-and-Functionality/IntelPyTorch_GPU_InferenceOptimization_with_AMP/sample.json

@@ -11,14 +11,17 @@
   "ciTests": {
     "linux": [
     {
+        "env": [
+            "source /intel/oneapi/intelpython/bin/activate",
+            "conda activate pytorch-gpu",
+            "pip install uv",
+            "uv python pin $(which python)",
+            "uv venv --system-site-packages",
+            "uv sync"
+        ],
         "id": "intel pytorch gpu inference optimization with amp",
         "steps": [
-            "source /intel/oneapi/intelpython/bin/activate",
-            "source activate pytorch-gpu",
-            "pip install -r requirements.txt",
-            "pip install jupyter ipykernel",  
-            "python -m ipykernel install --user --name=pytorch-gpu",
-            "python IntelPyTorch_GPU_InferenceOptimization_with_AMP.py"
+            "uv run IntelPyTorch_GPU_InferenceOptimization_with_AMP.py"
          ]
     }
      ]

AI-and-Analytics/Features-and-Functionality/IntelPyTorch_TrainingOptimizations_AMX_BF16/pyproject.toml

@@ -0,0 +1,13 @@
+[project]
+name = "intelpytorch-trainingoptimizations-amx-bf16"
+version = "0.1.0"
+description = "Add your description here"
+readme = "README.md"
+requires-python = ">=3.11"
+dependencies = [
+    "ipykernel>=6.29.5",
+    "matplotlib>=3.10.1",
+    "notebook>=7.3.2",
+    "py-cpuinfo>=9.0.0",
+    "transformers>=4.49.0",
+]

AI-and-Analytics/Features-and-Functionality/IntelPyTorch_TrainingOptimizations_AMX_BF16/sample.json

@@ -11,15 +11,20 @@
     "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": [
-              "source /intel/oneapi/intelpython/bin/activate",
-              "conda activate pytorch",
-              "python -m pip install -r requirements.txt",
-              "python -m ipykernel install --user --name=pytorch",
-              "python pytorch_training_avx512_bf16.py",
-              "python pytorch_training_amx_bf16.py",
-              "jupyter nbconvert --ExecutePreprocessor.enabled=True --ExecutePreprocessor.kernel_name=pytorch --to notebook IntelPyTorch_TrainingOptimizations_AMX_BF16.ipynb"
+            "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"
            ]
       }
        ]

AI-and-Analytics/Features-and-Functionality/IntelPython_GPU_dpnp_Genetic_Algorithm/pyproject.toml

@@ -0,0 +1,9 @@
+[project]
+name = "intelpython-gpu-dpnp-genetic-algorithm"
+version = "0.1.0"
+description = "Add your description here"
+readme = "README.md"
+requires-python = ">=3.11"
+dependencies = [
+    "matplotlib>=3.10.1",
+]

AI-and-Analytics/Features-and-Functionality/IntelPython_GPU_dpnp_Genetic_Algorithm/sample.json

@@ -9,18 +9,21 @@
   "os":["linux"],
   "targetDevice": ["GPU"],
   "ciTests": {
-  	"linux": [
+    "linux": [
     {
-  		"env": [
+      "env": [
         "source /intel/oneapi/intelpython/bin/activate",
         "conda activate base",
-        "pip install -r requirements.txt"
+        "pip install uv",
+        "uv python pin $(which python)",
+        "uv venv --system-site-packages",
+        "uv sync"
       ],
-  		"id": "idp_ga_dpnp_py",
-  		"steps": [
-         "python IntelPython_GPU_dpnp_Genetic_Algorithm.py" 
-  		 ]
-  	}
+      "id": "idp_ga_dpnp_py",
+      "steps": [
+         "uv run python IntelPython_GPU_dpnp_Genetic_Algorithm.py"
+      ]
+    }
     ]
 },
 "expertise": "Code Optimization"

AI-and-Analytics/Features-and-Functionality/IntelPython_Numpy_Numba_dpnp_kNN/pyproject.toml

@@ -0,0 +1,9 @@
+[project]
+name = "intelpython-numpy-numba-dpnp-knn"
+version = "0.1.0"
+description = "Add your description here"
+readme = "README.md"
+requires-python = ">=3.11"
+dependencies = [
+    "numba>=0.61.0",
+]

AI-and-Analytics/Features-and-Functionality/IntelPython_Numpy_Numba_dpnp_kNN/sample.json

@@ -14,13 +14,16 @@
   		"env": [
         "source /intel/oneapi/intelpython/bin/activate",
         "conda activate base", 
-        "pip install numba"
+        "pip install uv",
+        "uv python pin $(which python)",
+        "uv venv --system-site-packages",
+        "uv sync"
       ],
-  		"id": "idp_numpy_numba_dpnp_gs_py",
-  		"steps": [
-         "python IntelPython_Numpy_Numba_dpnp_kNN.py" 
-  		 ]
-  	}
+      "id": "idp_numpy_numba_dpnp_gs_py",
+      "steps": [
+         "uv run python IntelPython_Numpy_Numba_dpnp_kNN.py"
+      ]
+    }
     ]
 },
 "expertise": "Code Optimization"

AI-and-Analytics/Features-and-Functionality/IntelPython_XGBoost_Performance/pyproject.toml

@@ -0,0 +1,14 @@
+[project]
+name = "intelpython-xgboost-performance"
+version = "0.1.0"
+description = "Add your description here"
+readme = "README.md"
+requires-python = ">=3.11"
+dependencies = [
+    "matplot>=0.1.9",
+    "notebook>=7.3.2",
+    "numpy==1.26.4",
+    "pandas>=2.2.3",
+    "scikit-learn>=1.6.1",
+    "xgboost==0.82",
+]

AI-and-Analytics/Features-and-Functionality/IntelPython_XGBoost_Performance/requirements.txt

@@ -1,6 +1,6 @@
 ###### Requirements ######
 notebook
 matplot
-xgboost==0.81
+xgboost==0.82
 scikit-learn
 pandas

AI-and-Analytics/Features-and-Functionality/IntelPython_XGBoost_Performance/sample.json

@@ -9,17 +9,22 @@
   "os":["linux"],
   "targetDevice": ["CPU"],
   "ciTests": {
-  	"linux": [
+    "linux": [
     {
-  		"id": "idp_xgb_performance",
-  		"steps": [
-         	"source /intel/oneapi/intelpython/bin/activate",
-          "python IntelPython_XGBoost_Performance.py",
-          "conda remove xgboost --y",
-          "pip install -r requirements.txt",
-          "python IntelPython_XGBoost_Performance.py"		 
-  		 ]
-  	}
+      "env": [
+        "source /intel/oneapi/intelpython/bin/activate",
+        "conda activate base"
+      ],
+      "id": "idp_xgb_performance",
+      "steps": [
+        "python IntelPython_XGBoost_Performance.py",
+        "pip install uv",
+        "uv python pin $(which python)",
+        "uv venv --system-site-packages",
+        "uv sync",
+        "uv run python IntelPython_XGBoost_Performance.py"
+      ]
+    }
     ]
 },
 "expertise": "Code Optimization"

AI-and-Analytics/Features-and-Functionality/IntelPython_daal4py_DistributedKMeans/pyproject.toml

@@ -0,0 +1,12 @@
+[project]
+name = "intelpython-daal4py-distributedkmeans"
+version = "0.1.0"
+description = "Add your description here"
+readme = "README.md"
+requires-python = ">=3.11"
+dependencies = [
+    "joblib>=1.4.2",
+    "notebook>=7.3.2",
+    "numpy==1.26.4",
+    "pandas>=2.2.3",
+]

AI-and-Analytics/Features-and-Functionality/IntelPython_daal4py_DistributedKMeans/sample.json

@@ -15,11 +15,14 @@
 			"env": [
 				"source /intel/oneapi/intelpython/bin/activate",
 				"conda activate base",
-				"pip install -r requirements.txt"
+				"pip install uv",
+				"uv python pin $(which python)",
+				"uv venv --system-site-packages",
+				"uv sync"
 			],
 			"id": "idp_d4p_KM_Dist",
 			"steps": [
-				"mpirun -n 4 python ./IntelPython_daal4py_Distributed_Kmeans.py"
+				"uv run mpirun -n 4 python ./IntelPython_daal4py_Distributed_Kmeans.py"
 			]
 		}]
 	},

AI-and-Analytics/Features-and-Functionality/IntelPython_daal4py_DistributedLinearRegression/pyproject.toml

@@ -0,0 +1,11 @@
+[project]
+name = "intelpython-daal4py-distributedlinearregression"
+version = "0.1.0"
+description = "Add your description here"
+readme = "README.md"
+requires-python = ">=3.11"
+dependencies = [
+    "joblib>=1.4.2",
+    "numpy==1.26.4",
+    "pandas>=2.2.3",
+]

AI-and-Analytics/Features-and-Functionality/IntelPython_daal4py_DistributedLinearRegression/sample.json

@@ -13,13 +13,17 @@
 	"ciTests": {
 		"linux": [{
 			"env": [
-				"source /intel/oneapi/intelpython/bin/activate",
-				"pip install -r requirements.txt"
+                "source /intel/oneapi/intelpython/bin/activate", 
+                "conda activate base", 
+                "pip install uv", 
+                "uv python pin $(which python)", 
+                "uv venv --system-site-packages", 
+                "uv sync"
 			],
 			"id": "idp_d4p_Linear_Regression_Dist",
 			"steps": [
-				"python download_data.py",
-				"mpirun -n 4 python ./IntelPython_daal4py_Distributed_LinearRegression.py"
+				"uv run python download_data.py",
+				"uv run mpirun -n 4 python ./IntelPython_daal4py_Distributed_LinearRegression.py"
 			]
 		}]
 	},

AI-and-Analytics/Features-and-Functionality/IntelTensorFlow_AMX_BF16_Inference/pyproject.toml

@@ -0,0 +1,15 @@
+[project]
+name = "inteltensorflow-amx-bf16-inference"
+version = "0.1.0"
+description = "Add your description here"
+readme = "README.md"
+requires-python = ">=3.11"
+dependencies = [
+    "jupyter>=1.1.1",
+    "notebook>=7.3.2",
+    "numpy==1.26.4",
+    "pillow>=11.1.0",
+    "py-cpuinfo>=9.0.0",
+    "requests>=2.32.3",
+    "tensorflow-hub==0.16",
+]