TensorRT-LLMs/cpp/tensorrt_llm/thop/userbuffersTensor.cpp
Yihan Wang 9df4dad3b6
[None][fix] Introduce inline namespace to avoid symbol collision (#9541)
Signed-off-by: Yihan Wang <yihwang@nvidia.com>
2025-12-12 23:32:15 +08:00

57 lines
1.9 KiB
C++

/*
* Copyright (c) 2025, 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 "userbuffersTensor.h"
TRTLLM_NAMESPACE_BEGIN
namespace torch_ext
{
std::pair<torch::Tensor, tensorrt_llm::runtime::ub::UBBuffer> create_userbuffers_tensor(
at::IntArrayRef shape, torch::ScalarType dtype)
{
int64_t buffer_size
= std::accumulate(shape.begin(), shape.end(), 1, std::multiplies<int64_t>()) * torch::elementSize(dtype);
std::vector<int64_t> strides_vec(shape.size());
strides_vec[shape.size() - 1] = 1;
for (int64_t i = static_cast<int64_t>(shape.size()) - 1; i >= 1; --i)
{
strides_vec[i - 1] = strides_vec[i] * shape[i];
}
auto [ptr, ub] = tensorrt_llm::runtime::ub::UserBuffersManager::get_instance().allocate_userbuffers(buffer_size);
auto& deleter = ptr.get_deleter();
return std::make_pair(
torch::from_blob(ptr.release(), shape, strides_vec, deleter, torch::dtype(dtype).device(torch::kCUDA)), ub);
}
// Custom op interface for create_userbuffers_tensor.
// Python side does not need the UBBuffer object.
torch::Tensor create_userbuffers_tensor_op(at::IntArrayRef shape, torch::ScalarType dtype)
{
return create_userbuffers_tensor(shape, dtype).first;
}
} // namespace torch_ext
TRTLLM_NAMESPACE_END
TORCH_LIBRARY_FRAGMENT(trtllm, m)
{
m.def("create_userbuffers_tensor", &tensorrt_llm::torch_ext::create_userbuffers_tensor_op);
}