Merge pull request #66 from Talmaj/talmaj/updates

Fix instance norm tests
Update pre-commit config
Update tox.ini
Fix test_clip
Add lint_and_test GitHub action
Remove circleci

.github/workflows/lint_and_test.yml

@@ -0,0 +1,43 @@
+name: Lint and Test
+
+on: [pull_request]
+
+jobs:
+  test:
+    runs-on: ubuntu-latest
+    strategy:
+      matrix:
+        python-version: [ '3.9', '3.10', '3.11', '3.12' ]
+
+    steps:
+      - name: Checkout code
+        uses: actions/checkout@v4
+
+      - name: Set up Python ${{ matrix.python-version }}
+        uses: actions/setup-python@v5
+        with:
+          python-version: ${{ matrix.python-version }}
+
+      - name: Cache dependencies
+        uses: actions/cache@v4
+        with:
+          path: ~/.cache/pip
+          key: ${{ runner.os }}-pip-${{ matrix.python-version }}-${{ hashFiles('**/requirements.txt') }}
+          restore-keys: |
+            ${{ runner.os }}-pip-${{ matrix.python-version }}-
+            ${{ runner.os }}-pip-
+
+      - name: Install dependencies
+        run: |
+          pip install tox tox-gh-actions
+
+      - name: Run tests
+        run: |
+          bash download_fixtures.sh
+          tox
+
+      - name: Upload coverage to GitHub Artifacts
+        uses: actions/upload-artifact@v4
+        with:
+          name: coverage-${{ matrix.python-version }}
+          path: htmlcov/

.pre-commit-config.yaml

@@ -1,6 +1,6 @@
 repos:
   - repo: https://github.com/psf/black
-    rev: stable
+    rev: 24.8.0
     hooks:
       - id: black
-        language_version: python3.8
+        language_version: python3.10

README.md

@@ -1,6 +1,6 @@
 # ONNX to PyTorch
 ![PyPI - License](https://img.shields.io/pypi/l/onnx2pytorch?color)
-[![CircleCI](https://circleci.com/gh/ToriML/onnx2pytorch.svg?style=shield)](https://app.circleci.com/pipelines/github/ToriML/onnx2pytorch)
+[![Lint and Test](https://github.com/Talmaj/onnx2pytorch/actions/workflows/lint_and_test.yml/badge.svg)](https://github.com/Talmaj/onnx2pytorch/actions/workflows/lint_and_test.yml)
 [![Downloads](https://pepy.tech/badge/onnx2pytorch)](https://pepy.tech/project/onnx2pytorch)
 ![PyPI](https://img.shields.io/pypi/v/onnx2pytorch)
 

download_fixtures.sh

@@ -9,7 +9,7 @@ fi
 
 if [[ ! -f shufflenet_v2.onnx ]]; then
   echo Downloading shufflenet_v2
-  curl -LJo shufflenet_v2.onnx https://github.com/onnx/models/blob/master/vision/classification/shufflenet/model/shufflenet-v2-10.onnx\?raw\=true
+  curl -LJo shufflenet_v2.onnx https://github.com/onnx/models/raw/main/validated/vision/classification/shufflenet/model/shufflenet-v2-10.onnx
 fi
 
 if [[ $1 == "--all" ]]; then
@@ -20,32 +20,32 @@ if [[ $1 == "--all" ]]; then
 
   if [[ ! -f bertsquad-10.onnx ]]; then
     echo Downloading bertsquad-10
-    curl -LJo bertsquad-10.onnx https://github.com/onnx/models/blob/master/text/machine_comprehension/bert-squad/model/bertsquad-10.onnx\?raw\=true
+    curl -LJo bertsquad-10.onnx https://github.com/onnx/models/raw/main/validated/text/machine_comprehension/bert-squad/model/bertsquad-10.onnx
   fi
 
   if [[ ! -f yolo_v4.onnx ]]; then
     echo Downloading yolo_v4
-    curl -LJo yolo_v4.onnx https://github.com/onnx/models/blob/master/vision/object_detection_segmentation/yolov4/model/yolov4.onnx\?raw\=true
+    curl -LJo yolo_v4.onnx https://github.com/onnx/models/raw/main/validated/vision/object_detection_segmentation/yolov4/model/yolov4.onnx
   fi
 
   if [[ ! -f super_res.onnx ]]; then
     echo Downloading super_res
-    curl -LJo super_res.onnx https://github.com/onnx/models/blob/master/vision/super_resolution/sub_pixel_cnn_2016/model/super-resolution-10.onnx\?raw\=true
+    curl -LJo super_res.onnx https://github.com/onnx/models/raw/main/validated/vision/super_resolution/sub_pixel_cnn_2016/model/super-resolution-10.onnx
   fi
 
   if [[ ! -f fast_neural_style.onnx ]]; then
     echo Downloading fast_neural_style
-    curl -LJo fast_neural_style.onnx https://github.com/onnx/models/blob/master/vision/style_transfer/fast_neural_style/model/rain-princess-9.onnx\?raw\=true
+    curl -LJo fast_neural_style.onnx https://github.com/onnx/models/raw/main/validated/vision/style_transfer/fast_neural_style/model/rain-princess-9.onnx
   fi
 
   if [[ ! -f efficientnet-lite4.onnx ]]; then
     echo Downloading efficientnet-lite4
-    curl -LJo efficientnet-lite4.onnx https://github.com/onnx/models/blob/master/vision/classification/efficientnet-lite4/model/efficientnet-lite4-11.onnx\?raw\=true
+    curl -LJo efficientnet-lite4.onnx https://github.com/onnx/models/raw/main/validated/vision/classification/efficientnet-lite4/model/efficientnet-lite4-11.onnx
   fi
 
   if [[ ! -f mobilenetv2-7.onnx ]]; then
     echo Downloading mobilenetv2-7
-    curl -LJo mobilenetv2-7.onnx https://github.com/onnx/models/raw/master/vision/classification/mobilenet/model/mobilenetv2-7.onnx\?raw\=true
+    curl -LJo mobilenetv2-7.onnx https://github.com/onnx/models/raw/main/validated/vision/classification/mobilenet/model/mobilenetv2-7.onnx
   fi
 
 fi

onnx2pytorch/operations/instancenorm.py

@@ -7,16 +7,13 @@
     from torch.nn.modules.batchnorm import _LazyNormBase
 
     class _LazyInstanceNorm(_LazyNormBase, _InstanceNorm):
-
         cls_to_become = _InstanceNorm
 
-
 except ImportError:
     from torch.nn.modules.lazy import LazyModuleMixin
     from torch.nn.parameter import UninitializedBuffer, UninitializedParameter
 
     class _LazyInstanceNorm(LazyModuleMixin, _InstanceNorm):
-
         weight: UninitializedParameter  # type: ignore[assignment]
         bias: UninitializedParameter  # type: ignore[assignment]
 
@@ -78,24 +75,29 @@ def initialize_parameters(self, input) -> None:  # type: ignore[override]
                 self.reset_parameters()
 
 
-class LazyInstanceNormUnsafe(_LazyInstanceNorm):
+class InstanceNormMixin:
     """Skips dimension check."""
 
     def __init__(self, *args, affine=True, **kwargs):
+        self.no_batch_dim = None  # no_batch_dim has to be set at runtime
         super().__init__(*args, affine=affine, **kwargs)
 
+    def set_no_dim_batch_dim(self, no_batch_dim):
+        self.no_batch_dim = no_batch_dim
+
     def _check_input_dim(self, input):
         return
 
+    def _get_no_batch_dim(self):
+        return self.no_batch_dim
 
-class InstanceNormUnsafe(_InstanceNorm):
-    """Skips dimension check."""
 
-    def __init__(self, *args, affine=True, **kwargs):
-        super().__init__(*args, affine=affine, **kwargs)
+class LazyInstanceNormUnsafe(InstanceNormMixin, _LazyInstanceNorm):
+    pass
 
-    def _check_input_dim(self, input):
-        return
+
+class InstanceNormUnsafe(InstanceNormMixin, _InstanceNorm):
+    pass
 
 
 class InstanceNormWrapper(torch.nn.Module):
@@ -120,4 +122,7 @@ def forward(self, input, scale=None, B=None):
         if B is not None:
             getattr(self.inu, "bias").data = B
 
+        if self.inu.no_batch_dim is None:
+            self.inu.set_no_dim_batch_dim(input.dim() - 1)
+
         return self.inu.forward(input)

tests/onnx2pytorch/convert/test_lstm.py

@@ -52,17 +52,17 @@ def test_single_layer_lstm(
     o2p_lstm = ConvertModel(onnx_lstm, experimental=True)
     with torch.no_grad():
         o2p_output, o2p_h_n, o2p_c_n = o2p_lstm(input, h_0, c_0)
-        assert torch.equal(o2p_output, output)
-        assert torch.equal(o2p_h_n, h_n)
-        assert torch.equal(o2p_c_n, c_n)
+        torch.testing.assert_allclose(o2p_output, output, rtol=1e-6, atol=1e-6)
+        torch.testing.assert_allclose(o2p_h_n, h_n, rtol=1e-6, atol=1e-6)
+        torch.testing.assert_allclose(o2p_c_n, c_n, rtol=1e-6, atol=1e-6)
 
     onnx_lstm = onnx.ModelProto.FromString(bitstream_data)
     o2p_lstm = ConvertModel(onnx_lstm, experimental=True)
     with torch.no_grad():
         o2p_output, o2p_h_n, o2p_c_n = o2p_lstm(h_0=h_0, input=input, c_0=c_0)
-        assert torch.equal(o2p_output, output)
-        assert torch.equal(o2p_h_n, h_n)
-        assert torch.equal(o2p_c_n, c_n)
+        torch.testing.assert_allclose(o2p_output, output, rtol=1e-6, atol=1e-6)
+        torch.testing.assert_allclose(o2p_h_n, h_n, rtol=1e-6, atol=1e-6)
+        torch.testing.assert_allclose(o2p_c_n, c_n, rtol=1e-6, atol=1e-6)
         with pytest.raises(KeyError):
             o2p_output, o2p_h_n, o2p_c_n = o2p_lstm(h_0=h_0, input=input)
         with pytest.raises(Exception):

tests/onnx2pytorch/operations/test_clip.py

@@ -20,11 +20,11 @@ def test_clip():
     assert torch.equal(op(x), exp_y)
 
     op = Clip(max=0)
-    exp_y_np = np.clip(x_np, np.NINF, 0)
+    exp_y_np = np.clip(x_np, -np.inf, 0)
     exp_y = torch.from_numpy(exp_y_np)
     assert torch.equal(op(x), exp_y)
 
     op = Clip()
-    exp_y_np = np.clip(x_np, np.NINF, np.inf)
+    exp_y_np = np.clip(x_np, -np.inf, np.inf)
     exp_y = torch.from_numpy(exp_y_np)
     assert torch.equal(op(x), exp_y)

tox.ini

@@ -4,7 +4,14 @@
 # and then run "tox" from this directory.
 
 [tox]
-envlist = clean,py36,py37,py38,py38-torch19,py39
+envlist = clean,py39,py310,py311,py312
+
+[gh-actions]
+python =
+    3.9: py39
+    3.10: py310
+    3.11: py311
+    3.12: py312
 
 [testenv]
 passenv =