Enable pointer-generator T5 models in BeamSearch#23134
Enable pointer-generator T5 models in BeamSearch#23134tianleiwu merged 3 commits intomicrosoft:mainfrom
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| bool has_hidden_state = subgraph_inputs[2]->Name() == "encoder_hidden_states" ? true : false; | ||
| SetPastInputIndex(has_hidden_state); | ||
| bool has_encoder_input_ids = subgraph_inputs[1]->Name() == "encoder_input_ids"; | ||
| bool has_hidden_state = subgraph_inputs[2 + has_encoder_input_ids]->Name() == "encoder_hidden_states"; |
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Arithmetic overflow: Using operator '+' on a 4 byte value and then casting the result to a 8 byte value. Cast the value to the wider type before calling operator '+' to avoid overflow (io.2).
onnxruntime/contrib_ops/cpu/transformers/subgraph_t5_decoder.cc
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/azp run Windows ARM64 QNN CI Pipeline,Windows x64 QNN CI Pipeline,Windows CPU CI Pipeline,Windows GPU CUDA CI Pipeline,Windows GPU DML CI Pipeline,Windows GPU Doc Gen CI Pipeline,Windows GPU TensorRT CI Pipeline,ONNX Runtime Web CI Pipeline,Linux CPU CI Pipeline,Linux CPU Minimal Build E2E CI Pipeline |
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/azp run Linux GPU CI Pipeline,Linux GPU TensorRT CI Pipeline,Linux OpenVINO CI Pipeline,Linux QNN CI Pipeline,MacOS CI Pipeline,orttraining-linux-gpu-ci-pipeline,onnxruntime-binary-size-checks-ci-pipeline,Big Models,Linux Android Emulator QNN CI Pipeline,Android CI Pipeline |
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/azp run iOS CI Pipeline,ONNX Runtime React Native CI Pipeline,CoreML CI Pipeline,Linux DNNL CI Pipeline,Linux MIGraphX CI Pipeline,Linux ROCm CI Pipeline |
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Azure Pipelines successfully started running 6 pipeline(s). |
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Azure Pipelines successfully started running 9 pipeline(s). |
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Azure Pipelines successfully started running 10 pipeline(s). |
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@tianleiwu I don't think I got which is the problem on the iOS failure. All the involved tests seems passing there. Do you have some insights? |
onnxruntime/contrib_ops/cpu/transformers/subgraph_t5_decoder.cc
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/azp run Windows ARM64 QNN CI Pipeline,Windows x64 QNN CI Pipeline,Windows CPU CI Pipeline,Windows GPU CUDA CI Pipeline,Windows GPU DML CI Pipeline,Windows GPU Doc Gen CI Pipeline,Windows GPU TensorRT CI Pipeline,ONNX Runtime Web CI Pipeline,Linux CPU CI Pipeline,Linux CPU Minimal Build E2E CI Pipeline |
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/azp run Linux GPU CI Pipeline,Linux GPU TensorRT CI Pipeline,Linux OpenVINO CI Pipeline,Linux QNN CI Pipeline,MacOS CI Pipeline,orttraining-linux-ci-pipeline,orttraining-linux-gpu-ci-pipeline,onnxruntime-binary-size-checks-ci-pipeline,Big Models,Linux Android Emulator QNN CI Pipeline |
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/azp run Android CI Pipeline,iOS CI Pipeline,ONNX Runtime React Native CI Pipeline,CoreML CI Pipeline,Linux DNNL CI Pipeline,Linux MIGraphX CI Pipeline,Linux ROCm CI Pipeline |
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Azure Pipelines successfully started running 7 pipeline(s). |
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Azure Pipelines successfully started running 8 pipeline(s). |
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Azure Pipelines successfully started running 10 pipeline(s). |
### Description Introduces a new optional input (encoder_ibnput_ids) in the decoder graph of the T5 implementation for BeamSearch. This allows usage of pointer generator networks in decoder graph. ### Motivation and Context - Fixes microsoft#23123
### Description Introduces a new optional input (encoder_ibnput_ids) in the decoder graph of the T5 implementation for BeamSearch. This allows usage of pointer generator networks in decoder graph. ### Motivation and Context - Fixes #23123
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Description
Introduces a new optional input (encoder_input_ids) in the decoder graph of the T5 implementation for BeamSearch. This allows usage of pointer generator networks in decoder graph.
Motivation and Context