Add NNCFProfiler implementation

tests/tools/requirements.txt

@@ -1,4 +1,6 @@
 matplotlib
+nbclient
+nbformat
 psutil
 pytest
 pandas

tests/tools/test_profiler.py

@@ -0,0 +1,46 @@
+# Copyright (c) 2025 Intel Corporation
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#      http://www.apache.org/licenses/LICENSE-2.0
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+import os
+import tempfile
+from pathlib import Path
+
+import nbformat
+from nbclient import NotebookClient
+
+
+def test_tiny_llama_profiling_notebook():
+    """Test that the tiny_llama_profiling.ipynb notebook runs successfully."""
+    notebook_path = Path(__file__).parent.parent.parent / "tools" / "profiler" / "tiny_llama_profiling.ipynb"
+    profiler_dir = Path(__file__).parent.parent.parent / "tools" / "profiler"
+
+    # Check if notebook exists
+    assert notebook_path.exists(), f"Notebook not found at {notebook_path}"
+
+    # Read the notebook
+    with open(notebook_path) as f:
+        nb = nbformat.read(f, as_version=4)
+
+    # Execute the notebook using nbclient with a temporary IPython config directory
+    with tempfile.TemporaryDirectory() as tmpdir:
+        os.environ['IPYTHONDIR'] = tmpdir
+        # Save original working directory
+        original_cwd = os.getcwd()
+        try:
+            # Change to profiler directory for notebook execution
+            os.chdir(str(profiler_dir))
+            client = NotebookClient(nb, timeout=600)
+            client.execute()
+        finally:
+            # Clean up: restore working directory and environment variable
+            os.chdir(original_cwd)
+            if 'IPYTHONDIR' in os.environ:
+                del os.environ['IPYTHONDIR']

tools/README.md

@@ -153,3 +153,17 @@ The input file should contain the following columns:
 ```shell
 python visualize_compression_results.py --input-file data/llama2_asym.csv --output-dir output_dir
 ```
+
+## Profiler
+
+The Profiler is a tool for collecting and analyzing activation statistics from OpenVINO models. It enables layer-by-layer profiling of model activations using NNCF infrastructure, making it useful for debugging quantization and compression issues, comparing model variants, and understanding activation distributions.
+
+Key features:
+
+- Collect raw activations at input and output of specific layers using regex pattern matching
+- Calculate custom statistics (min, max, mean, std, percentiles, etc.) on collected activations
+- Compare activations between two model variants (e.g., FP32 vs INT8) with built-in and custom metrics
+- Visualize activation distributions and comparison results with matplotlib
+- Extensible architecture allowing registration of custom statistics, comparators, and visualizers
+
+See [tiny_llama_profiling.ipynb](profiler/tiny_llama_profiling.ipynb) for a complete usage example demonstrating how to profile an OpenVino model, collect activation statistics, and compare FP32 vs INT8 quantized variants.