mirror of
https://github.com/zebrajr/pytorch.git
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008ba18c5b
* Also pass torch includes to nvcc build * Export ATen/cuda headers with install * Refactor flags common to C++ and CUDA * Improve tests for C++/CUDA extensions * Export .cuh files under THC * Refactor and clean cpp_extension.py slightly * Include ATen in cuda extension test * Clarifying comment in cuda_extension.cu * Replace cuda_extension.cu with cuda_extension_kernel.cu in setup.py * Copy compile args in C++ extension and add second kernel * Conditionally add -std=c++11 to cuda_flags * Also export cuDNN headers * Add comment about deepcopy
30 lines
1.1 KiB
Plaintext
30 lines
1.1 KiB
Plaintext
// NOTE: This is a copy of cuda_extension_kernel.cu. It's kept here to test
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// collision handling when a C++ file and CUDA file share the same filename.
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// Setuptools can't deal with this at all, so the setup.py-based test uses
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// cuda_extension_kernel.cu and the JIT test uses this file. Symlinks don't
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// work well on Windows, so this is the most thorough solution right now.
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#include <cuda.h>
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#include <cuda_runtime.h>
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#include <ATen/ATen.h>
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__global__ void sigmoid_add_kernel(
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const float* __restrict__ x,
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const float* __restrict__ y,
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float* __restrict__ output,
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const int size) {
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const int index = blockIdx.x * blockDim.x + threadIdx.x;
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if (index < size) {
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const float sigmoid_x = 1.0f / (1.0f + __expf(-x[index]));
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const float sigmoid_y = 1.0f / (1.0f + __expf(-y[index]));
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output[index] = sigmoid_x + sigmoid_y;
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}
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}
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void sigmoid_add_cuda(const float* x, const float* y, float* output, int size) {
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const int threads = 1024;
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const int blocks = (size + threads - 1) / threads;
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sigmoid_add_kernel<<<blocks, threads>>>(x, y, output, size);
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}
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