mirror of https://github.com/hpcaitech/ColossalAI
aibig-modeldata-parallelismdeep-learningdistributed-computingfoundation-modelsheterogeneous-traininghpcinferencelarge-scalemodel-parallelismpipeline-parallelism
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44 lines
1.7 KiB
44 lines
1.7 KiB
/*This code from NVIDIA Megatron: |
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* with minor changes. */ |
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#include <cuda_fp16.h> |
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#include <torch/extension.h> |
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#include <vector> |
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torch::Tensor fwd_cuda(torch::Tensor const& input, float scale_factor); |
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torch::Tensor bwd_cuda(torch::Tensor const& output_grads, |
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torch::Tensor const& softmax_results, |
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float scale_factor); |
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torch::Tensor fwd(torch::Tensor const& input, float scale_factor) { |
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AT_ASSERTM(input.dim() == 3, "expected 3D tensor"); |
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AT_ASSERTM((input.scalar_type() == at::ScalarType::Half) || |
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(input.scalar_type() == at::ScalarType::BFloat16), |
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"Only fp16 and bf16 are supported"); |
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return fwd_cuda(input, scale_factor); |
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} |
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torch::Tensor bwd(torch::Tensor const& output_grads, |
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torch::Tensor const& softmax_results, float scale_factor) { |
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AT_ASSERTM(output_grads.dim() == 3, "expected 3D tensor"); |
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AT_ASSERTM(softmax_results.dim() == 3, "expected 3D tensor"); |
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AT_ASSERTM((output_grads.scalar_type() == at::ScalarType::Half) || |
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(output_grads.scalar_type() == at::ScalarType::BFloat16), |
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"Only fp16 and bf16 are supported"); |
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AT_ASSERTM((softmax_results.scalar_type() == at::ScalarType::Half) || |
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(softmax_results.scalar_type() == at::ScalarType::BFloat16), |
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"Only fp16 and bf16 are supported"); |
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return bwd_cuda(output_grads, softmax_results, scale_factor); |
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} |
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PYBIND11_MODULE(TORCH_EXTENSION_NAME, m) { |
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m.def("forward", &fwd, |
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"Self Multihead Attention scaled, time masked softmax -- Forward."); |
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m.def("backward", &bwd, |
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"Self Multihead Attention scaled, time masked softmax -- Backward."); |
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}
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