/* coding=utf-8 * Copyright (c) 2024, NVIDIA CORPORATION. All rights reserved. * * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. * You may obtain a copy of the License at * * http://www.apache.org/licenses/LICENSE-2.0 * * Unless required by applicable law or agreed to in writing, software * distributed under the License is distributed on an "AS IS" BASIS, * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. * See the License for the specific language governing permissions and * limitations under the License. */ #include namespace fused_rope { torch::Tensor fwd_cuda(const torch::Tensor& input, const torch::Tensor& freqs, const bool transpose_output); torch::Tensor bwd_cuda(const torch::Tensor& output_grads, const torch::Tensor& freqs, const bool transpose_output); torch::Tensor fwd_cached_cuda(const torch::Tensor& input, const torch::Tensor& cos, const torch::Tensor& sin, const bool transpose_output); torch::Tensor bwd_cached_cuda(const torch::Tensor& output_grads, const torch::Tensor& cos, const torch::Tensor& sin, const bool transpose_output); torch::Tensor fwd(const at::Tensor& input, const at::Tensor& freqs, const bool transpose_output) { TORCH_CHECK(input.dim() == 4, "expected 4D tensor"); TORCH_CHECK(freqs.dim() == 4, "expected 4D tensor"); TORCH_CHECK(input.size(0) == freqs.size(0), "expected input and freqs tensor have the same sequence length"); TORCH_CHECK(freqs.size(1) == 1 && freqs.size(2) == 1, "expected the second and third dims of the freqs tensor equal 1"); TORCH_CHECK(input.size(3) >= freqs.size(3), "expected the last dim of the input tensor equals or is " "greater than the freqs tensor"); TORCH_CHECK(freqs.scalar_type() == at::ScalarType::Float, "Dtype of the freqs tensor must be float"); return fwd_cuda(input, freqs, transpose_output); } torch::Tensor bwd(const torch::Tensor& output_grads, const at::Tensor& freqs, const bool transpose_output) { TORCH_CHECK(output_grads.dim() == 4, "expected 4D tensor"); TORCH_CHECK(freqs.dim() == 4, "expected 4D tensor"); TORCH_CHECK(output_grads.size(0) == freqs.size(0), "expected output_grads and freqs tensor have the same sequence length"); TORCH_CHECK(freqs.size(1) == 1 && freqs.size(2) == 1, "expected the second and third dims of the freqs tensor equal 1"); TORCH_CHECK(output_grads.size(3) >= freqs.size(3), "expected the last dim of the output_grads tensor equals or is " "greater than the freqs tensor"); TORCH_CHECK(freqs.scalar_type() == at::ScalarType::Float, "Dtype of the freqs tensor must be float"); return bwd_cuda(output_grads, freqs, transpose_output); } torch::Tensor fwd_cached(const at::Tensor& input, const at::Tensor& cos, const at::Tensor& sin, const bool transpose_output) { TORCH_CHECK(input.dim() == 4, "expected 4D tensor"); TORCH_CHECK(cos.dim() == 4, "expected 4D tensor"); TORCH_CHECK(sin.dim() == 4, "expected 4D tensor"); TORCH_CHECK(input.size(0) == cos.size(0), "expected input and cos tensor have the same sequence length"); TORCH_CHECK(input.size(0) == sin.size(0), "expected input and sin tensor have the same sequence length"); TORCH_CHECK(cos.size(1) == 1 && cos.size(2) == 1, "expected the second and third dims of the cos tensor equal 1"); TORCH_CHECK(sin.size(1) == 1 && sin.size(2) == 1, "expected the second and third dims of the sin tensor equal 1"); TORCH_CHECK(cos.size(3) == sin.size(3), "expected cos and sin tensor have the same last dim"); TORCH_CHECK(input.size(3) >= cos.size(3), "expected the last dim of the input tensor equals or is " "greater than the cos tensor"); TORCH_CHECK(cos.scalar_type() == sin.scalar_type(), "expected cos and sin tensor have the same dtype"); return fwd_cached_cuda(input, cos, sin, transpose_output); } torch::Tensor bwd_cached(const torch::Tensor& output_grads, const at::Tensor& cos, const at::Tensor& sin, const bool transpose_output) { TORCH_CHECK(output_grads.dim() == 4, "expected 4D tensor"); TORCH_CHECK(cos.dim() == 4, "expected 4D tensor"); TORCH_CHECK(sin.dim() == 4, "expected 4D tensor"); TORCH_CHECK(output_grads.size(0) == cos.size(0), "expected output_grads and cos tensor have the same sequence length"); TORCH_CHECK(output_grads.size(0) == sin.size(0), "expected output_grads and sin tensor have the same sequence length"); TORCH_CHECK(cos.size(1) == 1 && cos.size(2) == 1, "expected the second and third dims of the cos tensor equal 1"); TORCH_CHECK(sin.size(1) == 1 && sin.size(2) == 1, "expected the second and third dims of the sin tensor equal 1"); TORCH_CHECK(cos.size(3) == sin.size(3), "expected cos and sin tensor have the same last dim"); TORCH_CHECK(output_grads.size(3) >= cos.size(3), "expected the last dim of the output_grads tensor equals or is " "greater than the cos tensor"); TORCH_CHECK(cos.scalar_type() == sin.scalar_type(), "expected cos and sin tensor have the same dtype"); return bwd_cached_cuda(output_grads, cos, sin, transpose_output); } } // end namespace fused_rope PYBIND11_MODULE(TORCH_EXTENSION_NAME, m) { m.def("forward", &fused_rope::fwd, "Fused Rotary Positional Embedding -- Forward."); m.def("backward", &fused_rope::bwd, "Fused Rotary Positional Embedding -- Backward."); m.def("forward_cached", &fused_rope::fwd_cached, "Fused Rotary Positional Embedding Cached -- Forward."); m.def("backward_cached", &fused_rope::bwd_cached, "Fused Rotary Positional Embedding Cached -- Backward."); }