NVIDIA / NVIDIA/TensorRT

trt10.5 pytorch-quantization has compile bug

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Description

Description

trt10.5 pytorch-quantization has compile bug.

https://github.com/NVIDIA/TensorRT/blob/release/10.5/tools/pytorch-quantization/src/tensor_quant_gpu.cu#L28-L37
define two macro AT_DISPATCH_CASE_FLOATING_TYPES and AT_DISPATCH_FLOATING_TYPES

#define AT_DISPATCH_CASE_FLOATING_TYPES(...)   \
  AT_DISPATCH_CASE(at::ScalarType::Double, __VA_ARGS__)  \
  AT_DISPATCH_CASE(at::ScalarType::Float, __VA_ARGS__)  \
  AT_DISPATCH_CASE(at::ScalarType::Half, __VA_ARGS__)   \
  AT_DISPATCH_CASE(at::ScalarType::BFloat16, __VA_ARGS__)

#define AT_DISPATCH_FLOATING_TYPES(TYPE, NAME, ...) \
  AT_DISPATCH_SWITCH(                                        \
      TYPE, NAME, AT_DISPATCH_CASE_FLOATING_TYPES(__VA_ARGS__))

but in https://github.com/NVIDIA/TensorRT/blob/release/10.5/tools/pytorch-quantization/src/tensor_quant_gpu.cu#L18
#include <ATen/ATen.h> --> #include <ATen/Dispatch.h> --> has already defined these two macros.
I check torch1.13 and torch2.4.1, both the same case.

two macros duplicate definition. @moraxu
need use

#undef AT_DISPATCH_CASE_FLOATING_TYPES(...)  
#undef AT_DISPATCH_FLOATING_TYPES(TYPE, NAME, ...)  

before #define in tensor_quant_gpu.cu

Environment

TensorRT Version:10.5

NVIDIA GPU:rtx2000

NVIDIA Driver Version:

CUDA Version:11.8

CUDNN Version:9.1

Operating System:

Python Version (if applicable):3.8

PyTorch Version (if applicable):1.13 or 2.4.1

Contributor guide

Open the contributing guide

First steps

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  3. Fork the repository and make your change on a branch.
  4. Open a pull request that references the issue number.

Research direction

Start in tools/pytorch-quantization/src/tensor_quant_gpu.cu, especially the include near line 18 and the macro definitions around lines 28-37. Reproduce the compile with PyTorch 1.13 or 2.4.1 and verify that the duplicate macro definitions are resolved without introducing new build errors.

Written by the indexing model from the issue text.

Assessment

Tech stack
cpp, pytorch
Domain
build-system, machine-learning
Issue type
Bug
Difficulty
2/5
Estimated time
1-3 hours
Activity status
Stale
Clarity
Clearly specified
Newbie friendliness
45/100

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