mirror of https://github.com/hpcaitech/ColossalAI
98 lines
3.8 KiB
C++
98 lines
3.8 KiB
C++
#include <torch/extension.h>
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torch::Tensor moe_dispatch_cuda_forward(int s, int ec, int h,
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torch::Tensor batch_tokens,
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torch::Tensor mask,
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torch::Tensor dest_idx);
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torch::Tensor moe_dispatch_cuda_backward(int s, int ec, int h,
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torch::Tensor expert_grad,
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torch::Tensor mask,
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torch::Tensor dest_idx);
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torch::Tensor moe_combine_cuda_forward(int s, int e, int c, int h,
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torch::Tensor expert_tokens,
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torch::Tensor logits, torch::Tensor mask,
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torch::Tensor dest_idx);
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std::vector<torch::Tensor> moe_combine_cuda_backward(
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int s, int e, int c, int h, torch::Tensor tokens_grad,
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torch::Tensor expert_tokens, torch::Tensor logits, torch::Tensor mask,
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torch::Tensor dest_idx);
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torch::Tensor cumsum_sub_one_in_dim0(torch::Tensor mask);
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#define CHECK_CUDA(x) \
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TORCH_CHECK(x.device().is_cuda(), #x " must be a CUDA tensor")
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#define CHECK_CONTIGUOUS(x) \
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TORCH_CHECK(x.is_contiguous(), #x " must be contiguous")
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#define CHECK_INPUT(x) \
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CHECK_CUDA(x); \
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CHECK_CONTIGUOUS(x)
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torch::Tensor moe_dispatch_forward(int s, int ec, int h,
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torch::Tensor batch_tokens,
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torch::Tensor mask, torch::Tensor dest_idx) {
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CHECK_INPUT(batch_tokens);
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CHECK_CUDA(mask);
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CHECK_CUDA(dest_idx);
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return moe_dispatch_cuda_forward(s, ec, h, batch_tokens, mask, dest_idx);
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}
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torch::Tensor moe_dispatch_backward(int s, int ec, int h,
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torch::Tensor expert_grad,
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torch::Tensor mask,
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torch::Tensor dest_idx) {
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CHECK_INPUT(expert_grad);
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CHECK_CUDA(mask);
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CHECK_CUDA(dest_idx);
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return moe_dispatch_cuda_backward(s, ec, h, expert_grad, mask, dest_idx);
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}
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torch::Tensor moe_combine_forward(int s, int e, int c, int h,
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torch::Tensor expert_tokens,
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torch::Tensor logits, torch::Tensor mask,
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torch::Tensor dest_idx) {
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CHECK_INPUT(expert_tokens);
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CHECK_INPUT(logits);
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CHECK_CUDA(mask);
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CHECK_CUDA(dest_idx);
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return moe_combine_cuda_forward(s, e, c, h, expert_tokens, logits, mask,
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dest_idx);
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}
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std::vector<torch::Tensor> moe_combine_backward(int s, int e, int c, int h,
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torch::Tensor tokens_grad,
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torch::Tensor expert_tokens,
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torch::Tensor logits,
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torch::Tensor mask,
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torch::Tensor dest_idx) {
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CHECK_INPUT(tokens_grad);
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CHECK_INPUT(logits);
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CHECK_CUDA(mask);
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CHECK_CUDA(dest_idx);
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return moe_combine_cuda_backward(s, e, c, h, tokens_grad, expert_tokens,
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logits, mask, dest_idx);
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}
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torch::Tensor moe_cumsum(torch::Tensor mask) {
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CHECK_INPUT(mask);
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return cumsum_sub_one_in_dim0(mask);
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}
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PYBIND11_MODULE(TORCH_EXTENSION_NAME, m) {
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m.def("cumsum_sub_one", &moe_cumsum, "Fast cumsum operation in dim0");
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m.def("dispatch_forward", &moe_dispatch_forward,
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"Forward operation in MoE dispatch function");
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m.def("dispatch_backward", &moe_dispatch_backward,
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"Backward operation in MoE dispatch function");
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m.def("combine_forward", &moe_combine_forward,
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"Combine operation in MoE combine function");
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m.def("combine_backward", &moe_combine_backward,
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"Combine operation in MoE combine function");
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}
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