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The SplitToSequence refactor added a special case for element_size when it's a string, but this stops the computation of the A offset on line 510 from advancing as the offset is zero. So it copies the same string into each sequence element. This PR removes that check and adds a test for the string split behaviour.
I'm not sure why the special case on line 456 was added in the original PR (#18594), but all the tests pass in the new PR so presumably it isn't necessary.
Motivation and Context
SplitToSequence didn't work on string tensors, fixes#19726.
/azp run Linux CPU CI Pipeline,Linux CPU Minimal Build E2E CI Pipeline,Linux GPU CI Pipeline,Linux GPU TensorRT CI Pipeline,Linux OpenVINO CI Pipeline,Linux QNN CI Pipeline,MacOS CI Pipeline,ONNX Runtime Web CI Pipeline,Windows ARM64 QNN CI Pipeline
/azp run Windows CPU CI Pipeline,Windows GPU CI Pipeline,Windows GPU TensorRT CI Pipeline,Windows x64 QNN CI Pipeline,orttraining-linux-ci-pipeline,orttraining-linux-gpu-ci-pipeline,orttraining-ortmodule-distributed,onnxruntime-binary-size-checks-ci-pipeline
The Windows GPU TensorRT failure says that it couldn't find a CUDA device in tests other than the one I added, and they don't appear at first glance to use SplitToSequence either. Maybe it hit some dodgy hardware?
/azp run ONNX Runtime Web CI Pipeline,orttraining-amd-gpu-ci-pipeline,Big Models,Android CI Pipeline,iOS CI Pipeline,ONNX Runtime React Native CI Pipeline
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Description
The SplitToSequence refactor added a special case for element_size when it's a string, but this stops the computation of the
Aoffset on line 510 from advancing as the offset is zero. So it copies the same string into each sequence element. This PR removes that check and adds a test for the string split behaviour.I'm not sure why the special case on line 456 was added in the original PR (#18594), but all the tests pass in the new PR so presumably it isn't necessary.
Motivation and Context
SplitToSequence didn't work on string tensors, fixes #19726.
cc @pranavsharma