mirror of
https://github.com/NVIDIA/TensorRT-LLM.git
synced 2026-01-14 06:27:45 +08:00
118 lines
3.6 KiB
C++
118 lines
3.6 KiB
C++
/*
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* Copyright (c) 2020-2023, NVIDIA CORPORATION. All rights reserved.
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*
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* Licensed under the Apache License, Version 2.0 (the "License");
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* you may not use this file except in compliance with the License.
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* You may obtain a copy of the License at
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*
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* http://www.apache.org/licenses/LICENSE-2.0
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*
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* Unless required by applicable law or agreed to in writing, software
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* distributed under the License is distributed on an "AS IS" BASIS,
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* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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* See the License for the specific language governing permissions and
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* limitations under the License.
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*/
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#include "tensorrt_llm/thop/thUtils.h"
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#include <NvInferRuntime.h>
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#include <array>
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TRTLLM_NAMESPACE_BEGIN
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namespace torch_ext
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{
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tensorrt_llm::runtime::ITensor::Shape convert_shape(torch::Tensor tensor)
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{
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constexpr auto trtMaxDims = nvinfer1::Dims::MAX_DIMS;
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auto const torchTensorNumDims = tensor.dim();
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TLLM_CHECK_WITH_INFO(torchTensorNumDims <= trtMaxDims,
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"TensorRT supports at most %i tensor dimensions. Found a Torch tensor with %li dimensions.", trtMaxDims,
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torchTensorNumDims);
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auto result = nvinfer1::Dims{};
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result.nbDims = static_cast<int32_t>(torchTensorNumDims);
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for (int i = 0; i < torchTensorNumDims; i++)
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{
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result.d[i] = static_cast<int64_t>(tensor.size(i));
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}
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return result;
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}
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template <typename T>
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tensorrt_llm::runtime::ITensor::UniquePtr convert_tensor(torch::Tensor tensor)
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{
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return tensorrt_llm::runtime::ITensor::wrap(
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get_ptr<T>(tensor), tensorrt_llm::runtime::TRTDataType<T>::value, convert_shape(tensor));
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}
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// Template instantiations
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template tensorrt_llm::runtime::ITensor::UniquePtr convert_tensor<int32_t*>(torch::Tensor tensor);
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template tensorrt_llm::runtime::ITensor::UniquePtr convert_tensor<int32_t>(torch::Tensor tensor);
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template tensorrt_llm::runtime::ITensor::UniquePtr convert_tensor<uint8_t>(torch::Tensor tensor);
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template tensorrt_llm::runtime::ITensor::UniquePtr convert_tensor<int8_t>(torch::Tensor tensor);
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template tensorrt_llm::runtime::ITensor::UniquePtr convert_tensor<float>(torch::Tensor tensor);
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template tensorrt_llm::runtime::ITensor::UniquePtr convert_tensor<half>(torch::Tensor tensor);
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#ifdef ENABLE_BF16
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template tensorrt_llm::runtime::ITensor::UniquePtr convert_tensor<__nv_bfloat16>(torch::Tensor tensor);
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#endif
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template tensorrt_llm::runtime::ITensor::UniquePtr convert_tensor<bool>(torch::Tensor tensor);
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std::optional<float> getFloatEnv(char const* name)
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{
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char const* const env = std::getenv(name);
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if (env == nullptr)
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{
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return std::nullopt;
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}
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try
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{
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float value = std::stof(env);
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return {value};
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}
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catch (std::invalid_argument const& e)
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{
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return std::nullopt;
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}
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catch (std::out_of_range const& e)
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{
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return std::nullopt;
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}
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};
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int nextPowerOfTwo(int v)
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{
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--v;
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v |= v >> 1;
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v |= v >> 2;
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v |= v >> 4;
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v |= v >> 8;
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v |= v >> 16;
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return ++v;
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}
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cudaDataType_t convert_torch_dtype(torch::ScalarType dtype)
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{
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switch (dtype)
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{
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case torch::kInt32: return CUDA_R_32I;
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case torch::kFloat: return CUDA_R_32F;
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#ifdef ENABLE_BF16
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case torch::kBFloat16: return CUDA_R_16BF;
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#endif
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case torch::kHalf: return CUDA_R_16F;
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#ifdef ENABLE_FP8
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case torch::kFloat8_e4m3fn: return CUDA_R_8F_E4M3;
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case torch::kFloat8_e5m2: return CUDA_R_8F_E5M2;
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#endif
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case torch::kByte: return CUDA_R_8U;
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case torch::kChar: return CUDA_R_8I;
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case torch::kBool: return CUDA_R_8U;
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default: TLLM_THROW("Unsupported torch dtype %s to convert", c10::toString(dtype));
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}
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}
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} // namespace torch_ext
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TRTLLM_NAMESPACE_END
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