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🔨Update imports causing import warnings #2698

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🔨Update imports causing import warnings #2698

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d93edd4
update openvino.runtime imports
rajeshgangireddy May 12, 2025
de37959
Update pyproject.toml
rajeshgangireddy May 12, 2025
00801ad
Update torch.onnx.export to use dynamo
rajeshgangireddy May 13, 2025
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2 changes: 1 addition & 1 deletion docs/source/markdown/guides/how_to/models/post_processor.md
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Expand Up @@ -144,7 +144,7 @@ One key advantage of Anomalib's post-processor design is that it becomes part of
```python
from anomalib.models import Patchcore
from anomalib.post_processing import PostProcessor
from openvino.runtime import Core
from openvino import Core
import numpy as np

# Training: Post-processor is part of the model
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5 changes: 1 addition & 4 deletions pyproject.toml
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Expand Up @@ -52,10 +52,7 @@ core = [
"lightning>=2.2",
"torch>=2",
"torchmetrics>=1.3.2",
# NOTE: open-clip-torch throws the following error on v2.26.1
# torch.onnx.errors.UnsupportedOperatorError: Exporting the operator
# 'aten::_native_multi_head_attention' to ONNX opset version 14 is not supported
"open-clip-torch>=2.23.0,<2.26.1",
"open-clip-torch>=2.32.0",
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i think vlm model was broken when we installed >2.32.0. @ashwinvaidya17, can you confirm?

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Here is where the tests fail when we use a newer clip version

FAILED tests/integration/model/test_models.py::TestAPI::test_export[onnx-win_clip] - torch.onnx.errors.UnsupportedOperatorError: Exporting the operator 'aten::_native_multi_head_attention' to ONNX opset version 14 is not supported. Please feel free to request support or submit a pull request on PyTorch GitHub: https://github.com/pytorch/pytorch/issues.
FAILED tests/integration/model/test_models.py::TestAPI::test_export[openvino-win_clip] - torch.onnx.errors.UnsupportedOperatorError: Exporting the operator 'aten::_native_multi_head_attention' to ONNX opset version 14 is not supported. Please feel free to request support or submit a pull request on PyTorch GitHub: https://github.com/pytorch/pytorch/issues.
===== 2 failed, 182 passed, 16 skipped, 972 warnings in 1506.18s (0:25:06) =====

"fvcore",
]
openvino = ["openvino>=2024.0", "nncf>=2.10.0", "onnx>=1.16.0"]
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2 changes: 1 addition & 1 deletion src/anomalib/deploy/inferencers/openvino_inferencer.py
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Expand Up @@ -56,7 +56,7 @@
import numpy as np
import torch
from lightning_utilities.core.imports import module_available
from openvino.runtime.utils.data_helpers.wrappers import OVDict
from openvino.utils.data_helpers.wrappers import OVDict
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As far as I can see OVDict is only used for annotation. Maybe we could have the import something like this

if TYPE_CHECKING:
    from openvino.utils.data_helpers.wrappers import OVDict

....

def post_process(predictions: "OVDict") -> dict:

from PIL.Image import Image as PILImage

from anomalib.data import NumpyImageBatch
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1 change: 1 addition & 0 deletions src/anomalib/models/components/base/export_mixin.py
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Expand Up @@ -159,6 +159,7 @@ def to_onnx(
dynamic_axes=dynamic_axes,
input_names=["input"],
output_names=output_names,
dynamo=True,
)

return onnx_path
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