Bump torch to 2.11.0

.github/workflows/call_precommit.yml

@@ -169,8 +169,8 @@ jobs:
           sudo apt-get --assume-yes install build-essential ninja-build libgl1-mesa-dev libglib2.0-0 wget make
       - name: Download CUDA
         run: |
-          wget -q https://developer.download.nvidia.com/compute/cuda/12.6.3/local_installers/cuda_12.6.3_560.35.05_linux.run
-          sudo sh cuda_12.6.3_560.35.05_linux.run --toolkit --silent
+          wget -q https://developer.download.nvidia.com/compute/cuda/13.2.1/local_installers/cuda_13.2.1_595.58.03_linux.run
+          sudo sh cuda_13.2.1_595.58.03_linux.run --toolkit --silent
       - name: Runner info
         continue-on-error: true
         run: |

.github/workflows/examples.yml

@@ -110,8 +110,8 @@ jobs:
           sudo apt-get --assume-yes install build-essential ninja-build libgl1-mesa-dev libglib2.0-0 wget make
       - name: Download CUDA
         run: |
-          wget -q https://developer.download.nvidia.com/compute/cuda/12.6.3/local_installers/cuda_12.6.3_560.35.05_linux.run
-          sudo sh cuda_12.6.3_560.35.05_linux.run --toolkit --silent
+          wget -q https://developer.download.nvidia.com/compute/cuda/13.2.1/local_installers/cuda_13.2.1_595.58.03_linux.run
+          sudo sh cuda_13.2.1_595.58.03_linux.run --toolkit --silent
       - name: Runner info
         continue-on-error: true
         run: |

.github/workflows/install.yml

@@ -59,8 +59,8 @@ jobs:
           sudo apt-get --assume-yes install build-essential ninja-build libgl1-mesa-dev libglib2.0-0 wget make virtualenv
       - name: Download CUDA
         run: |
-          wget -q https://developer.download.nvidia.com/compute/cuda/12.6.3/local_installers/cuda_12.6.3_560.35.05_linux.run
-          sudo sh cuda_12.6.3_560.35.05_linux.run --toolkit --silent
+          wget -q https://developer.download.nvidia.com/compute/cuda/13.2.1/local_installers/cuda_13.2.1_595.58.03_linux.run
+          sudo sh cuda_13.2.1_595.58.03_linux.run --toolkit --silent
       - name: Runner info
         continue-on-error: true
         run: |

README.md

@@ -164,7 +164,7 @@ calibration_dataset = nncf.Dataset(dataset_loader, transform_fn)
 
 # Step 3: Export model to TorchFX
 input_shape = (1, 3, 224, 224)
-fx_model = torch.export.export_for_training(model, args=(ex_input,)).module()
+fx_model = torch.export.export(model, args=(ex_input,)).module()
 # or
 # fx_model = torch.export.export(model, args=(ex_input,)).module()
 

constraints.txt

@@ -2,16 +2,16 @@
 openvino==2026.1.0
 
 # Pytorch
-torch==2.10.0
-torchvision==0.25.0
+torch==2.11.0
+torchvision==0.26.0
 torchao==0.17.0
 
 # ONNX
 onnx==1.21.0
-onnx-ir==0.1.15
+onnx-ir==0.2.1
 onnxruntime==1.23.2; python_version < '3.11'
 onnxruntime==1.24.3; python_version >= '3.11'
-onnxscript==0.6.2
+onnxscript==0.7.0
 
 # Tests and examples
 pytest==9.0.3

docs/Installation.md

@@ -48,7 +48,7 @@ as well as the supported versions of Python:
 
 | NNCF      | OpenVINO   | PyTorch  | ONNX     | TensorFlow | Python |
 |-----------|------------|----------|----------|------------|--------|
-| `develop` | `2026.1.0` | `2.10.0` | `1.21.0` |            | `3.12` |
+| `develop` | `2026.1.0` | `2.11.0` | `1.21.0` |            | `3.12` |
 | `3.1.0`   | `2026.1.0` | `2.10.0` | `1.21.0` |            | `3.10` |
 | `3.0.0`   | `2026.0.0` | `2.9.0`  | `1.17.0` |            | `3.10` |
 | `2.19.0`  | `2025.4.0` | `2.8.0`  | `1.17.0` | `2.15.1`   | `3.10` |
@@ -72,4 +72,4 @@ as well as the supported versions of Python:
 
 > (*) Python 3.9 or higher is required for TensorFlow 2.15.1
 
-This repository is tested on Python* 3.12, PyTorch* 2.10.0 (NVidia CUDA\* Toolkit 12.6).
+This repository is tested on Python* 3.12, PyTorch* 2.11.0 (NVidia CUDA\* Toolkit 13.2).

examples/llm_compression/onnx/tiny_llama/requirements.txt

@@ -6,4 +6,4 @@ optimum==2.1.0
 onnx==1.21.0
 onnxruntime==1.23.2; python_version < '3.11'
 onnxruntime==1.24.3; python_version >= '3.11'
-torch==2.10.0
+torch==2.11.0

examples/llm_compression/onnx/tiny_llama_scale_estimation/requirements.txt

@@ -1,4 +1,4 @@
-torch==2.10.0
+torch==2.11.0
 transformers==4.53.0
 openvino==2026.1.0
 optimum-intel[openvino]==1.27.0

examples/llm_compression/openvino/smollm2_360m_adaptive_codebook/requirements.txt

@@ -5,5 +5,5 @@ optimum-onnx==0.1.0
 optimum==2.1.0
 transformers==4.53.0
 onnx==1.21.0
-torch==2.10.0
-torchvision==0.25.0
+torch==2.11.0
+torchvision==0.26.0

examples/llm_compression/openvino/smollm2_360m_codebook/requirements.txt

@@ -4,5 +4,5 @@ optimum-onnx==0.1.0
 optimum==2.1.0
 transformers==4.53.0
 onnx==1.21.0
-torch==2.10.0
-torchvision==0.25.0
+torch==2.11.0
+torchvision==0.26.0

examples/llm_compression/openvino/smollm2_360m_fp8/requirements.txt

@@ -5,4 +5,4 @@ optimum-onnx==0.1.0
 optimum==2.1.0
 transformers==4.53.0
 onnx==1.21.0
-torch==2.10.0
+torch==2.11.0

examples/llm_compression/openvino/tiny_llama/requirements.txt

@@ -4,5 +4,5 @@ openvino==2026.1.0
 optimum-intel[openvino]==1.27.0
 optimum-onnx==0.1.0
 optimum==2.1.0
-torch==2.10.0
+torch==2.11.0
 transformers==4.53.0

examples/llm_compression/openvino/tiny_llama_find_hyperparams/requirements.txt

@@ -6,4 +6,4 @@ optimum-onnx==0.1.0
 optimum==2.1.0
 transformers==4.53.0
 onnx==1.21.0
-torch==2.10.0
+torch==2.11.0

examples/llm_compression/openvino/tiny_llama_synthetic_data/requirements.txt

@@ -1,4 +1,4 @@
-torch==2.10.0
+torch==2.11.0
 datasets==4.6.1
 numpy>=1.23.5,<2
 openvino==2026.1.0

examples/llm_compression/torch/distillation_qat_with_lora/requirements.txt

@@ -1,5 +1,5 @@
 tensorboard==2.20.0
-torch==2.10.0
+torch==2.11.0
 torchao==0.17.0
 numpy>=1.23.5,<2
 openvino==2026.1.0

examples/llm_compression/torch/downstream_qat_with_nls/requirements.txt

@@ -1,5 +1,5 @@
 tensorboard==2.20.0
-torch==2.10.0
+torch==2.11.0
 numpy>=1.23.5,<2
 openvino==2026.1.0
 optimum-intel==1.27.0

examples/llm_compression/torch_fx/tiny_llama/modelling.py

@@ -106,7 +106,7 @@ def convert_and_export_with_cache(model: PreTrainedModel) -> tuple[ExportedProgr
 
     dynamic_shapes = {"input_ids": {1: torch.export.Dim.DYNAMIC}, "cache_position": {0: torch.export.Dim.DYNAMIC}}
 
-    exported_program = torch.export.export_for_training(
+    exported_program = torch.export.export(
         model,
         args=(
             example_input_ids,

examples/llm_compression/torch_fx/tiny_llama/requirements.txt

@@ -2,6 +2,6 @@ transformers==4.53.0
 datasets==4.6.1
 openvino==2026.1.0
 optimum==2.1.0
-torch==2.10.0
-torchvision==0.25.0
+torch==2.11.0
+torchvision==0.26.0
 torchao==0.17.0

examples/post_training_quantization/onnx/mobilenet_v2/requirements.txt

@@ -1,5 +1,5 @@
-torch==2.10.0
-torchvision==0.25.0
+torch==2.11.0
+torchvision==0.26.0
 fastdownload==0.0.7
 fastprogress==1.0.5
 fastcore==1.11.5

examples/post_training_quantization/onnx/yolov8_quantize_with_accuracy_control/requirements.txt

@@ -3,4 +3,4 @@ onnx==1.21.0
 onnxruntime==1.23.2; python_version < '3.11'
 onnxruntime==1.24.3; python_version >= '3.11'
 openvino==2026.1.0
-torch==2.10.0
+torch==2.11.0

examples/post_training_quantization/openvino/yolo26/requirements.txt

@@ -1,4 +1,4 @@
 ultralytics==8.4.21
 onnx==1.21.0
 openvino==2026.1.0
-torch==2.10.0
+torch==2.11.0

examples/post_training_quantization/openvino/yolov8_quantize_with_accuracy_control/requirements.txt

@@ -1,4 +1,4 @@
 ultralytics==8.3.221
 onnx==1.21.0
 openvino==2026.1.0
-torch==2.10.0
+torch==2.11.0

examples/post_training_quantization/torch/mobilenet_v2/requirements.txt

@@ -3,5 +3,5 @@ fastprogress==1.0.5
 fastcore==1.11.5
 openvino==2026.1.0
 scikit-learn
-torch==2.10.0
-torchvision==0.25.0
+torch==2.11.0
+torchvision==0.26.0

examples/post_training_quantization/torch/ssd300_vgg16/requirements.txt

@@ -4,7 +4,7 @@ fastcore==1.11.5
 onnx==1.21.0
 openvino==2026.1.0
 pycocotools==2.0.7
-torch==2.10.0
+torch==2.11.0
 torchmetrics==1.0.1
-torchvision==0.25.0
+torchvision==0.26.0
 numpy<2

examples/post_training_quantization/torch_fx/resnet18/requirements.txt

@@ -2,6 +2,6 @@ fastdownload==0.0.7
 fastprogress==1.0.5
 fastcore==1.11.5
 openvino==2026.1.0
-torch==2.10.0
-torchvision==0.25.0
+torch==2.11.0
+torchvision==0.26.0
 torchao==0.17.0

examples/pruning/torch/resnet18/requirements.txt

@@ -2,5 +2,5 @@ fastdownload==0.0.7
 fastprogress==1.0.5
 fastcore==1.11.5
 openvino==2026.1.0
-torch==2.10.0
-torchvision==0.25.0
+torch==2.11.0
+torchvision==0.26.0

examples/quantization_aware_training/torch/anomalib/requirements.txt

@@ -1,5 +1,5 @@
 anomalib==2.2.0
-torch==2.10.0
+torch==2.11.0
 openvino==2025.3.0
 requests==2.33.0
 matplotlib==3.10.7

examples/quantization_aware_training/torch/resnet18/requirements.txt

@@ -2,5 +2,5 @@ fastdownload==0.0.7
 fastprogress==1.0.5
 fastcore==1.11.5
 openvino==2026.1.0
-torch==2.10.0
-torchvision==0.25.0
+torch==2.11.0
+torchvision==0.26.0