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Some Shape Related Fusions #19832
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Some Shape Related Fusions #19832
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tianleiwu
reviewed
Mar 8, 2024
tianleiwu
reviewed
Mar 8, 2024
tianleiwu
reviewed
Mar 8, 2024
zhijxu-MS
previously approved these changes
Mar 11, 2024
zhijxu-MS
approved these changes
Mar 12, 2024
mszhanyi
added a commit
that referenced
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Jun 27, 2024
### Description ### Motivation and Context The pipeline is green even Llama2 parity_check fails. The PR should be merged after the below exception is solved. ''' 2024-06-25 03:49:43.621298481 [E:onnxruntime:, sequential_executor.cc:514 ExecuteKernel] Non-zero status code returned while running Expand node. Name:'/model/Expand' Status Message: /model/Expand: left operand cannot broadcast on dim 3 LeftShape: {1,1,9,9}, RightShape: {2,1,9,17} An error occurred while verifying parity: Error in execution: Non-zero status code returned while running Expand node. Name:'/model/Expand' Status Message: /model/Expand: left operand cannot broadcast on dim 3 LeftShape: {1,1,9,9}, RightShape: {2,1,9,17} Traceback (most recent call last): File "/workspace/onnxruntime/python/tools/transformers/models/llama/convert_to_onnx.py", line 1043, in main parity_check(parity_cmd) File "/workspace/onnxruntime/python/tools/transformers/models/llama/llama_parity.py", line 298, in main verify_parity(args, location, use_auth_token, kv_cache_ortvalues, pytorch_model=llama, config=config) File "/workspace/onnxruntime/python/tools/transformers/models/llama/llama_parity.py", line 137, in verify_parity ort_model.run_with_iobinding(io_binding) File "/home/onnxruntimedev/.local/lib/python3.8/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 331, in run_with_iobinding self._sess.run_with_iobinding(iobinding._iobinding, run_options) RuntimeError: Error in execution: Non-zero status code returned while running Expand node. Name:'/model/Expand' Status Message: /model/Expand: left operand cannot broadcast on dim 3 LeftShape: {1,1,9,9}, RightShape: {2,1,9,17} ''' The exception looks caused by #19832
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This PR adds below shape related fusions, which is helpful for some transformer models: