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Release v2.14.1 of NNCF to master
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alexsu52 committed Dec 19, 2024
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4 changes: 0 additions & 4 deletions README.md
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Expand Up @@ -394,18 +394,14 @@ A list of notebooks demonstrating OpenVINO conversion and inference together wit
| [InstructPix2Pix](https://github.com/openvinotoolkit/openvino_notebooks/tree/latest/notebooks/instruct-pix2pix-image-editing) | Post-Training Quantization | OpenVINO | Image-to-Image |
| [CLIP](https://github.com/openvinotoolkit/openvino_notebooks/tree/latest/notebooks/clip-zero-shot-image-classification) | Post-Training Quantization | OpenVINO | Image-to-Text |
| [BLIP](https://github.com/openvinotoolkit/openvino_notebooks/tree/latest/notebooks/blip-visual-language-processing) | Post-Training Quantization | OpenVINO | Image-to-Text |
| [Segmind-VegaRT](https://github.com/openvinotoolkit/openvino_notebooks/blob/latest/notebooks/stable-diffusion-xl/segmind-vegart.ipynb) | Post-Training Quantization | OpenVINO | Text-to-Image |
| [Latent Consistency Model](https://github.com/openvinotoolkit/openvino_notebooks/tree/latest/notebooks/latent-consistency-models-image-generation) | Post-Training Quantization | OpenVINO | Text-to-Image |
| [Würstchen](https://github.com/openvinotoolkit/openvino_notebooks/tree/latest/notebooks/wuerstchen-image-generation) | Post-Training Quantization | OpenVINO | Text-to-Image |
| [ControlNet QR Code Monster](https://github.com/openvinotoolkit/openvino_notebooks/tree/latest/notebooks/qrcode-monster) | Post-Training Quantization | OpenVINO | Text-to-Image |
| [SDXL-turbo](https://github.com/openvinotoolkit/openvino_notebooks/tree/latest/notebooks/sdxl-turbo) | Post-Training Quantization | OpenVINO | Text-to-Image,<br>Image-to-Image |
| [ImageBind](https://github.com/openvinotoolkit/openvino_notebooks/tree/latest/notebooks/image-bind) | Post-Training Quantization | OpenVINO | Multi-Modal Retrieval |
| [Distil-Whisper](https://github.com/openvinotoolkit/openvino_notebooks/tree/latest/notebooks/distil-whisper-asr) | Post-Training Quantization | OpenVINO | Speech-to-Text |
| [Whisper](https://github.com/openvinotoolkit/openvino_notebooks/tree/latest/notebooks/whisper-subtitles-generation)<br>[![Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/openvinotoolkit/openvino_notebooks/blob/latest/notebooks/whisper-subtitles-generation/whisper-convert.ipynb) | Post-Training Quantization | OpenVINO | Speech-to-Text |
| [MMS Speech Recognition](https://github.com/openvinotoolkit/openvino_notebooks/tree/latest/notebooks/mms-massively-multilingual-speech) | Post-Training Quantization | OpenVINO | Speech-to-Text |
| [Grammar Error Correction](https://github.com/openvinotoolkit/openvino_notebooks/tree/latest/notebooks/grammar-correction) | Post-Training Quantization | OpenVINO | NLP, Grammar Correction |
| [LLM Instruction Following](https://github.com/openvinotoolkit/openvino_notebooks/tree/latest/notebooks/llm-question-answering) | Weight Compression | OpenVINO | NLP, Instruction Following |
| [Dolly 2.0](https://github.com/openvinotoolkit/openvino_notebooks/tree/latest/notebooks/dolly-2-instruction-following) | Weight Compression | OpenVINO | NLP, Instruction Following |
| [LLM Chat Bots](https://github.com/openvinotoolkit/openvino_notebooks/tree/latest/notebooks/llm-chatbot) | Weight Compression | OpenVINO | NLP, Chat Bot |

### Post-Training Quantization Examples
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8 changes: 8 additions & 0 deletions ReleaseNotes.md
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# Release Notes

## New in Release 2.14.1

Post-training Quantization:

- Bugfixes:
- (PyTorch) Fixed the `get_torch_compile_wrapper` function to match with the `torch.compile`.
- (OpenVINO) Updated cache statistics functionality to utilize the `safetensors` approach.

## New in Release 2.14.0

Post-training Quantization:
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2 changes: 1 addition & 1 deletion constraints.txt
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# Openvino
openvino==2024.5.0
openvino==2024.6.0

# Pytorch
torch==2.5.1
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5 changes: 3 additions & 2 deletions docs/Installation.md
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Expand Up @@ -2,7 +2,7 @@

We suggest to install or use the package in the [Python virtual environment](https://docs.python.org/3/tutorial/venv.html).

If you want to optimize a model from PyTorch, install PyTorch by following [PyTorch installation guide](https://pytorch.org/get-started/locally/#start-locally). For other backend follow: [TensorFlow installation guide](https://www.tensorflow.org/install/), [ONNX installation guide](https://onnxruntime.ai/docs/install/), [OpenVINO installation guide](https://docs.openvino.ai/latest/openvino_docs_install_guides_overview.html).
If you want to optimize a model from PyTorch, install PyTorch by following [PyTorch installation guide](https://pytorch.org/get-started/locally/#start-locally). For other backend follow: [TensorFlow installation guide](https://www.tensorflow.org/install/), [ONNX installation guide](https://onnxruntime.ai/docs/install/), [OpenVINO installation guide](https://docs.openvino.ai/2024/get-started/install-openvino.html).

## As a PyPI package

Expand Down Expand Up @@ -43,7 +43,8 @@ as well as the supported versions of Python:

| NNCF | OpenVINO | PyTorch | ONNX | TensorFlow | Python |
|-----------|------------|----------|----------|------------|--------|
| `develop` | `2024.5.0` | `2.5.1` | `1.17.0` | `2.15.1` | `3.10` |
| `develop` | `2024.6.0` | `2.5.1` | `1.17.0` | `2.15.1` | `3.10` |
| `2.14.1` | `2024.6.0` | `2.5.1` | `1.17.0` | `2.15.1` | `3.10` |
| `2.14.0` | `2024.5.0` | `2.5.1` | `1.17.0` | `2.15.1` | `3.10` |
| `2.13.0` | `2024.4.0` | `2.4.0` | `1.16.0` | `2.15.1` | `3.8`* |
| `2.12.0` | `2024.3.0` | `2.3.0` | `1.16.0` | `2.15.1` | `3.8`* |
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2 changes: 1 addition & 1 deletion docs/PyPiPublishing.md
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[![GitHub Release](https://img.shields.io/github/v/release/openvinotoolkit/nncf?color=green)](https://github.com/openvinotoolkit/nncf/releases)
[![Website](https://img.shields.io/website?up_color=blue&up_message=docs&url=https%3A%2F%2Fdocs.openvino.ai%2Flatest%2Fopenvino_docs_model_optimization_guide.html)](https://docs.openvino.ai/nncf)
[![Website](https://img.shields.io/website?up_color=blue&up_message=docs&url=https%3A%2F%2Fdocs.openvino.ai%2Fnncf)](https://docs.openvino.ai/nncf)
[![Apache License Version 2.0](https://img.shields.io/badge/license-Apache_2.0-green.svg)](https://github.com/openvinotoolkit/nncf?tab=Apache-2.0-1-ov-file#readme)
[![PyPI Downloads](https://static.pepy.tech/badge/nncf)](https://pypi.org/project/nncf/)

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11 changes: 7 additions & 4 deletions docs/api/source/conf.py
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Expand Up @@ -75,7 +75,8 @@ def collect_api_entities() -> APIInfo:
except Exception as e:
skipped_modules[modname] = str(e)

from nncf.common.utils.api_marker import api
from nncf.common.utils.api_marker import API_MARKER_ATTR
from nncf.common.utils.api_marker import CANONICAL_ALIAS_ATTR

canonical_imports_seen = set()

Expand All @@ -86,7 +87,7 @@ def collect_api_entities() -> APIInfo:
if (
objects_module == modname
and (inspect.isclass(obj) or inspect.isfunction(obj))
and hasattr(obj, api.API_MARKER_ATTR)
and hasattr(obj, API_MARKER_ATTR)
):
marked_object_name = obj._nncf_api_marker
# Check the actual name of the originally marked object
Expand All @@ -95,8 +96,8 @@ def collect_api_entities() -> APIInfo:
if marked_object_name != obj.__name__:
continue
fqn = f"{modname}.{obj_name}"
if hasattr(obj, api.CANONICAL_ALIAS_ATTR):
canonical_import_name = getattr(obj, api.CANONICAL_ALIAS_ATTR)
if hasattr(obj, CANONICAL_ALIAS_ATTR):
canonical_import_name = getattr(obj, CANONICAL_ALIAS_ATTR)
if canonical_import_name in canonical_imports_seen:
assert False, f"Duplicate canonical_alias detected: {canonical_import_name}"
retval.fqn_vs_canonical_name[fqn] = canonical_import_name
Expand Down Expand Up @@ -142,6 +143,8 @@ def collect_api_entities() -> APIInfo:
"nncf.tensor.functions.numpy_linalg",
"nncf.tensor.functions.torch_numeric",
"nncf.tensor.functions.torch_linalg",
"nncf.tensor.functions.torch_io",
"nncf.tensor.functions.numpy_io",
]

with mock(mock_modules):
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Expand Up @@ -218,8 +218,6 @@ compressed_model = compress_weights(

When `statistics_path` is provided, the system first checks if the specified path exists. If it does, the statistics are loaded from this path. If the path does not exist, the statistics are computed and saved to this path for future use.

> **NOTE**: Use the `statistics_path` option only in the secure environment to avoid any substitution of the files with statistics.
### Evaluation results

#### Data-free Mixed-Precision on Lambada OpenAI dataset
Expand Down Expand Up @@ -688,5 +686,4 @@ Accuracy/footprint trade-off for `microsoft/Phi-3-mini-4k-instruct`:
List of notebooks demonstrating OpenVINO conversion and inference together with NNCF weight compression for models from various domains:

- [LLM Instruction Following](https://github.com/openvinotoolkit/openvino_notebooks/tree/latest/notebooks/llm-question-answering)
- [Dolly 2.0](https://github.com/openvinotoolkit/openvino_notebooks/tree/latest/notebooks/dolly-2-instruction-following)
- [LLM Chat Bots](https://github.com/openvinotoolkit/openvino_notebooks/tree/latest/notebooks/llm-chatbot)
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datasets
whowhatbench @ git+https://github.com/andreyanufr/who_what_benchmark.git
numpy>=1.23.5
openvino==2024.5
openvino==2024.6
optimum-intel[openvino]>=1.13.0
transformers>=4.35.2
onnx==1.17.0
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@@ -1,7 +1,7 @@
torch==2.5.1
datasets==3.0.1
numpy>=1.23.5
openvino==2024.5
openvino==2024.6
optimum-intel[openvino]>=1.13.0
transformers>=4.35.2
onnx==1.17.0
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Expand Up @@ -4,5 +4,5 @@ scikit-learn
fastdownload
onnx==1.17.0
onnxruntime==1.19.2
openvino==2024.5
openvino==2024.6
numpy<2
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@@ -1,3 +1,3 @@
ultralytics==8.3.22
onnx==1.17.0
openvino==2024.5
openvino==2024.6
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@@ -1,4 +1,4 @@
anomalib==0.6.0
openvino==2024.5
openvino==2024.6
setuptools<=72.1.0
numpy<2
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Expand Up @@ -2,4 +2,4 @@ torchvision
tqdm
scikit-learn
fastdownload
openvino==2024.5
openvino==2024.6
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@@ -1,3 +1,3 @@
ultralytics==8.3.22
onnx==1.17.0
openvino==2024.5
openvino==2024.6
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@@ -1,3 +1,3 @@
ultralytics==8.3.22
onnx==1.17.0
openvino==2024.5
openvino==2024.6
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Expand Up @@ -2,4 +2,4 @@ tensorflow~=2.12.0; python_version < '3.9'
tensorflow~=2.15.1; python_version >= '3.9'
tensorflow-datasets
tqdm
openvino==2024.5
openvino==2024.6
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@@ -1,5 +1,5 @@
fastdownload==0.0.7
openvino==2024.5
openvino==2024.6
scikit-learn
torch==2.5.1
torchvision==0.20.1
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@@ -1,6 +1,6 @@
fastdownload==0.0.7
onnx==1.17.0
openvino==2024.5
openvino==2024.6
pycocotools==2.0.7
torch==2.5.1
torchmetrics==1.0.1
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@@ -1,4 +1,4 @@
fastdownload==0.0.7
openvino==2024.5
openvino==2024.6
torch==2.5.1
torchvision==0.20.1
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@@ -1,2 +1,3 @@
anomalib[core,openvino]==1.0.1
setuptools<=72.1.0
matplotlib<3.10.0
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@@ -1,5 +1,5 @@
fastdownload==0.0.7
openvino==2024.5
openvino==2024.6
torch==2.5.1
torchvision==0.20.1
setuptools<=72.1.0
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