modified reduce_max reduce_min reduce_prod for higher_performance and fix a bug in reduce_op.cuh #32974
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| // module function designed for global function |
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感觉模板可以再简化一下，一些参数没有必要通过模板传，比如ReduceType。关于ReduceType的if判断只执行一次，并没有在循环里面，所以通过输入参数传也不会多影响性能。减少一些模板，应该能够剪短一些编译时间。
对于TransformOp，感觉LaunchReduceKernel和LaunchKernel这两个函数是不需要将TransformOp作为模板的？ReduceKernelFunction看起来是需要的。另外，LaunchReduceKernel和LaunchKernel函数命名缺乏辨识度，不能准确地表达函数的功能。
| : reduce_dims_origin(origin_reduce_dims), x_dim(x_dim) {} | ||
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| // get the parameters of reduceKernel | ||
| void Run() { |
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L170的comment：输入参数都建议改成const std::vector &类型。
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| ReduceKernelFunction< | ||
| Ty, Ty, ReduceOp, detail::IdentityFunctor<Ty>, 128, kRank, kReduceRank, | ||
| ReduceType::kReduceHigherDim><<<grid, block, 0, stream>>>( |
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L597 - L599 comment：直接写成CUB_REDUCE_TYPE_CASE(ReduceType::kReduceLastDim)这样？若ReduceType不作为模板，也就不需要这个swith case了。
| framework::TensorCopy(x, y->place(), y); | ||
| y->Resize(out_dims); | ||
| return; | ||
| } |
| } | ||
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| template <typename T, template <typename, typename> class ReduceOp> |
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上面的实现都可能需要复用到别的算子里面（比如broadcast反向），但ReduceCudaKernel只用于reduce_xxx算子的实现，所以L749 - L771最好不要放到这个头文件里面。
| int, ops::ProdFunctor>, | ||
| ops::ReduceKernel<paddle::platform::CUDADeviceContext, | ||
| int64_t, ops::ProdFunctor>); | ||
| REGISTER_OP_CUDA_KERNEL( |
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从注释来看，原来之所以加这个ifdef是因为原来的reduce采用Eigen实现，而Eigen对double的支持有问题。我们已经全部改成了cuda+cub的方式，或许这个ifdef可以去掉。
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Function optimization
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Describe
modified reduce_min reduce_max reduce_prod reduce_all reduce_any
ctest结果：
Test project /paddle_test/commit/Paddle/build
Start 709: test_max_op
100% tests passed, 0 tests failed out of 1
Total Test time (real) = 7.51 sec
Test project /paddle_test/commit/Paddle/build
Start 719: test_min_op
100% tests passed, 0 tests failed out of 1
Total Test time (real) = 6.81 sec
Test project /paddle_test/commit/Paddle/build
Start 826: test_prod_op
100% tests passed, 0 tests failed out of 1
Total Test time (real) = 7.78 sec
以max 为例进行性能比对：
benchmark性能数据如下：