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fix: ONNX model shape inference cannot handle batch with shape [-1] #1906
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Signed-off-by: Jason Wang <jasowang@microsoft.com>
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@svotaw the root cause of issue #1902 is that the shape inference code throws an error when the input batch looks like a one-dimensional array. I'm not sure why the original implementation throws "Image batch is not a sequence" error, but this error causes the code to fail when the input batch is one-dimensional. |
Codecov Report
@@ Coverage Diff @@
## master #1906 +/- ##
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- Coverage 86.82% 86.70% -0.12%
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Files 301 301
Lines 15596 15596
Branches 815 815
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- Hits 13541 13523 -18
- Misses 2055 2073 +18
... and 8 files with indirect coverage changes Help us with your feedback. Take ten seconds to tell us how you rate us. Have a feature suggestion? Share it here. |
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Signed-off-by: Jason Wang <jasowang@microsoft.com>
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Azure Pipelines successfully started running 1 pipeline(s). |
@svotaw please take a look at the changes. |
@mhamilton723 please merge. The fix was verified by customer. |
Related Issues/PRs
#1902
What changes are proposed in this pull request?
Add support in ONNX model shape inference when the input batch has shape [-1].
How is this patch tested?
Does this PR change any dependencies?
Does this PR add a new feature? If so, have you added samples on website?
website/docs/documentation
folder.Make sure you choose the correct class
estimators/transformers
and namespace.DocTable
points to correct API link.yarn run start
to make sure the website renders correctly.<!--pytest-codeblocks:cont-->
before each python code blocks to enable auto-tests for python samples.WebsiteSamplesTests
job pass in the pipeline.