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/* 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 <torch/extension.h>
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.");
}
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