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FP16 Execution produces non accurate results #41

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narendasan opened this issue Apr 23, 2020 · 0 comments · Fixed by #44
Closed

FP16 Execution produces non accurate results #41

narendasan opened this issue Apr 23, 2020 · 0 comments · Fixed by #44
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bug Something isn't working component: execution Issues re: Execution of engines priority: high

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@narendasan
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Right now the same workflow to run FP32 models when used in FP16 gives bad results.

@narendasan narendasan added bug Something isn't working component: execution Issues re: Execution of engines labels Apr 23, 2020
@narendasan narendasan self-assigned this Apr 23, 2020
narendasan added a commit to narendasan/TRTorch that referenced this issue Apr 24, 2020
- Now creates output tensors of the correct type to accept data
- There still may be a data race in the creation of the dataloader
iterator
- Quantization and Dynamic Shape right now don't play well together,
potential subsequent release of TRT may address this

Signed-off-by: Naren Dasan <naren@narendasan.com>
Signed-off-by: Naren Dasan <narens@nvidia.com>
frank-wei pushed a commit that referenced this issue Jun 4, 2022
…ical_xor (#41)

Summary:
Pull Request resolved: pytorch/fx2trt#41

fx2trt is a tool we use to create a TensorRT engine from a PyTorch model. The lowering is composed of 1) start the Pytorch model 2) frace model with acc tracer in acc_ops 3) Use TRT Interpreter to create a TensorRT engine

Here I:
1. Add corresponding acc ops
2. Add a converter for the acc op to acc_ops_converters.py.
3. Add a unit test for the converter in fbcode/deeplearning/trt/fx2trt_oss/test/converters/acc_op/test_logical_or/xor.py

Reviewed By: frank-wei

Differential Revision: D35237918

fbshipit-source-id: 82720b764f0c886749aafea84584cdcb5172d206
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