Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/33563
When NVCC or Clang are driving CUDA compilation many math functions are declared by default, with a small difference: Clang marks them as `__device__` only, while NVCC uses both `__host__` and `__device__`. This makes every un-elaborated `min` or `max` function call from a `__host__` function generate a syntax error when Clang is used.
Fix the errors by using `std::min` and `std::max` from `<algorithm>`, since C++14 they are `constexpr` and can be used in the `__device__` code [1].
1. https://llvm.org/docs/CompileCudaWithLLVM.html#algorithm
Test Plan:
```lang=bash
buck build mode/opt -c fbcode.cuda_use_clang=true //fblearner/flow/projects/dper:workflow
buck build mode/opt //fblearner/flow/projects/dper:workflow
```
Execute tests on devgpu:
```
buck test mode/dev-nosan -j 8 //caffe2/caffe2/python/operator_test/... //caffe2/test:cuda
```
Reviewed By: ngimel
Differential Revision: D20005795
fbshipit-source-id: 98a3f35e8a96c15d3ad3d2066396591f5cca1696
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/19660
Implementation of aggregated Scale operator.
The operator takes a list of tensors as an input and scales all of them them with the argument float value.
The tensor sizes can be different, therefore bookkeeping of the sizes and pointers to the tensors are
necessary for the GPU version of the kernel.
Reviewed By: BIT-silence
Differential Revision: D14984233
fbshipit-source-id: 37cc97159a4f2c38cd6fff4f5710ab7d3a773611
