[5676209][ONNX][Autocast] Add check for input bs vs calibration data bs #652
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Signed-off-by: gcunhase <[email protected]>
Signed-off-by: gcunhase <[email protected]>
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Tests failing on this PR. @gcunhase PTAL |
Signed-off-by: gcunhase <[email protected]>
Codecov Report✅ All modified and coverable lines are covered by tests. Additional details and impacted files@@ Coverage Diff @@
## main #652 +/- ##
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- Coverage 74.57% 74.46% -0.11%
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Files 183 183
Lines 18451 18413 -38
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kevalmorabia97
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Dec 11, 2025
…bs (#652) ## What does this PR do? **Type of change:** Bug fix **Overview:** Autocast crashes if the input batch size in the ONNX model is different to the calibration data input batch size. For example: calibration data has shape `[10, 6, 3, 480, 800]` and ONNX model has shape `[1, 6, 3, 480, 800]`. The quantization workflow interprets this as 10 calibration samples, so ideally, Autocast would also interpret them similarly. This PR just allows Autocast to exit gracefully with a custom message. ## Usage ```python $ python -m modelopt.onnx.autocast --onnx_path=$MODEL_NAME.onnx --calibration_data=calib_data_10.npz ``` ## Testing See bug 5676209. ## Before your PR is "*Ready for review*" <!-- If you haven't finished some of the above items you can still open `Draft` PR. --> - **Make sure you read and follow [Contributor guidelines](https://github.com/NVIDIA/TensorRT-Model-Optimizer/blob/main/CONTRIBUTING.md)** and your commits are signed. - **Is this change backward compatible?**: Yes - **Did you write any new necessary tests?**: No - **Did you add or update any necessary documentation?**: Yes - **Did you update [Changelog](https://github.com/NVIDIA/TensorRT-Model-Optimizer/blob/main/CHANGELOG.rst)?**: No ## Additional Information Original error: ```sh polygraphy.exception.exception.PolygraphyException: Input tensor: image | Received incompatible shape: (10, 6, 3, 480, 800). Note: Expected a shape compatible with: BoundedShape([1, 6, 3, 480, 800], min=None, max=None) ``` Autocast error: ```sh ValueError: Input shape from 'image' does not match provided input shape: [1, 6, 3, 480, 800] vs [10, 6, 3, 480, 800]. Please make sure that your calibration data matches the ONNX input shapes. ``` --------- Signed-off-by: gcunhase <[email protected]>
b7r6
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Dec 18, 2025
…bs (NVIDIA#652) ## What does this PR do? **Type of change:** Bug fix **Overview:** Autocast crashes if the input batch size in the ONNX model is different to the calibration data input batch size. For example: calibration data has shape `[10, 6, 3, 480, 800]` and ONNX model has shape `[1, 6, 3, 480, 800]`. The quantization workflow interprets this as 10 calibration samples, so ideally, Autocast would also interpret them similarly. This PR just allows Autocast to exit gracefully with a custom message. ## Usage ```python $ python -m modelopt.onnx.autocast --onnx_path=$MODEL_NAME.onnx --calibration_data=calib_data_10.npz ``` ## Testing See bug 5676209. ## Before your PR is "*Ready for review*" <!-- If you haven't finished some of the above items you can still open `Draft` PR. --> - **Make sure you read and follow [Contributor guidelines](https://github.com/NVIDIA/TensorRT-Model-Optimizer/blob/main/CONTRIBUTING.md)** and your commits are signed. - **Is this change backward compatible?**: Yes - **Did you write any new necessary tests?**: No - **Did you add or update any necessary documentation?**: Yes - **Did you update [Changelog](https://github.com/NVIDIA/TensorRT-Model-Optimizer/blob/main/CHANGELOG.rst)?**: No ## Additional Information Original error: ```sh polygraphy.exception.exception.PolygraphyException: Input tensor: image | Received incompatible shape: (10, 6, 3, 480, 800). Note: Expected a shape compatible with: BoundedShape([1, 6, 3, 480, 800], min=None, max=None) ``` Autocast error: ```sh ValueError: Input shape from 'image' does not match provided input shape: [1, 6, 3, 480, 800] vs [10, 6, 3, 480, 800]. Please make sure that your calibration data matches the ONNX input shapes. ``` --------- Signed-off-by: gcunhase <[email protected]>
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What does this PR do?
Type of change: Bug fix
Overview: Autocast crashes if the input batch size in the ONNX model is different to the calibration data input batch size. For example: calibration data has shape
[10, 6, 3, 480, 800]and ONNX model has shape[1, 6, 3, 480, 800]. The quantization workflow interprets this as 10 calibration samples, so ideally, Autocast would also interpret them similarly. This PR just allows Autocast to exit gracefully with a custom message.Usage
Testing
See bug 5676209.
Before your PR is "Ready for review"
Additional Information
Original error:
polygraphy.exception.exception.PolygraphyException: Input tensor: image | Received incompatible shape: (10, 6, 3, 480, 800). Note: Expected a shape compatible with: BoundedShape([1, 6, 3, 480, 800], min=None, max=None)Autocast error:
ValueError: Input shape from 'image' does not match provided input shape: [1, 6, 3, 480, 800] vs [10, 6, 3, 480, 800]. Please make sure that your calibration data matches the ONNX input shapes.