72 lines
3.2 KiB
C++
72 lines
3.2 KiB
C++
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#include <torch/torch.h>
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#include <torch/script.h>
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#include "ATen/cuda/CUDAContext.h"
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#include "triton/driver/stream.h"
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#include "triton/dnn/batchnorm.h"
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std::vector<torch::Tensor>
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batchnorm_ymv(const torch::Tensor fw_x,
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const torch::Tensor fw_g,
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const torch::Tensor fw_b,
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float eps) {
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// Wrap CUDA handles
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c10::DeviceIndex device = fw_x.storage().device().index();
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CUstream custream = (CUstream)at::cuda::getCurrentCUDAStream(device).stream();
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triton::driver::cu_stream stream(custream, false);
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triton::driver::context* ctx = stream.context();
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// get sizes
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int C = fw_x.size(0);
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int H = fw_x.size(1);
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int W = fw_x.size(2);
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int B = fw_x.size(3);
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// allocate outputs
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torch::Tensor fw_y = torch::empty(fw_x.sizes()).cuda();
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torch::Tensor fw_m = torch::empty(fw_g.sizes()).cuda();
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torch::Tensor fw_v = torch::empty(fw_g.sizes()).cuda();
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triton::driver::cu_buffer x(ctx, (CUdeviceptr)fw_x.storage().data(), false);
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triton::driver::cu_buffer g(ctx, (CUdeviceptr)fw_g.storage().data(), false);
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triton::driver::cu_buffer b(ctx, (CUdeviceptr)fw_b.storage().data(), false);
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triton::driver::cu_buffer y(ctx, (CUdeviceptr)fw_y.storage().data(), false);
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triton::driver::cu_buffer m(ctx, (CUdeviceptr)fw_m.storage().data(), false);
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triton::driver::cu_buffer v(ctx, (CUdeviceptr)fw_v.storage().data(), false);
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// create template
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triton::dnn::batchnorm_forward batchnorm(C, 1, H, W, B, "fp32", eps);
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batchnorm.enqueue(&stream, {&y, &m, &v, &x, &g, &b});
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return {fw_y, fw_m, fw_v};
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}
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std::vector<torch::Tensor>
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batchnorm_dxdgdb(const torch::Tensor fw_dy,
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const torch::Tensor fw_x,
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const torch::Tensor fw_g,
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const torch::Tensor fw_m,
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const torch::Tensor fw_v,
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float eps) {
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// Wrap CUDA handles
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c10::DeviceIndex device = fw_x.storage().device().index();
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CUstream custream = (CUstream)at::cuda::getCurrentCUDAStream(device).stream();
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triton::driver::cu_stream stream(custream, false);
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triton::driver::context* ctx = stream.context();
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// get sizes
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int C = fw_x.size(0);
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int H = fw_x.size(1);
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int W = fw_x.size(2);
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int B = fw_x.size(3);
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// allocate outputs
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torch::Tensor fw_dx = torch::empty(fw_x.sizes()).cuda();
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torch::Tensor fw_dg = torch::empty(fw_g.sizes()).cuda();
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torch::Tensor fw_db = torch::empty(fw_g.sizes()).cuda();
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// triton handles
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triton::driver::cu_buffer dy(ctx, (CUdeviceptr)fw_dy.storage().data(), false);
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triton::driver::cu_buffer x(ctx, (CUdeviceptr) fw_x.storage().data(), false);
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triton::driver::cu_buffer g(ctx, (CUdeviceptr) fw_g.storage().data(), false);
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triton::driver::cu_buffer m(ctx, (CUdeviceptr) fw_m.storage().data(), false);
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triton::driver::cu_buffer v(ctx, (CUdeviceptr) fw_v.storage().data(), false);
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triton::driver::cu_buffer dx(ctx, (CUdeviceptr)fw_dx.storage().data(), false);
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triton::driver::cu_buffer dg(ctx, (CUdeviceptr)fw_dg.storage().data(), false);
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triton::driver::cu_buffer db(ctx, (CUdeviceptr)fw_db.storage().data(), false);
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// create config
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triton::dnn::batchnorm_backward batchnorm(C, 1, H, W, B, "fp32", eps);
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batchnorm.enqueue(&stream, {&dx, &dg, &db, &dy, &x, &g, &m, &v});
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}
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