mirror of
https://github.com/NVIDIA/TensorRT-LLM.git
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4bb65f216f
* Update TensorRT-LLM --------- Co-authored-by: meghagarwal <16129366+megha95@users.noreply.github.com> Co-authored-by: Shixiaowei02 <39303645+Shixiaowei02@users.noreply.github.com>
305 lines
14 KiB
C++
305 lines
14 KiB
C++
/*
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* SPDX-FileCopyrightText: Copyright (c) 1993-2022 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
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* SPDX-License-Identifier: Apache-2.0
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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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#pragma once
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#include "tensorrt_llm/common/workspace.h"
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#include "tensorrt_llm/plugins/api/tllmPlugin.h"
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#include "tensorrt_llm/plugins/common/checkMacrosPlugin.h"
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#include <NvInferRuntime.h>
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#include <NvInferRuntimeBase.h>
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#include <cstring>
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#include <cublasLt.h>
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#include <cublas_v2.h>
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#include <cuda_runtime.h>
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#include <iostream>
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#include <map>
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#include <memory>
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#if ENABLE_MULTI_DEVICE
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#include <nccl.h>
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#endif // ENABLE_MULTI_DEVICE
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#include <optional>
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#include <set>
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#include <sstream>
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#include <string>
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#include <unordered_map>
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namespace tensorrt_llm::plugins
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{
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class BasePlugin : public nvinfer1::IPluginV2DynamicExt
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{
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public:
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void setPluginNamespace(char const* libNamespace) noexcept override
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{
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mNamespace = libNamespace;
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}
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[[nodiscard]] char const* getPluginNamespace() const noexcept override
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{
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return mNamespace.c_str();
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}
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protected:
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std::string mNamespace{api::kDefaultNamespace};
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};
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class BaseCreator : public nvinfer1::IPluginCreator
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{
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public:
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void setPluginNamespace(char const* libNamespace) noexcept override
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{
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mNamespace = libNamespace;
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}
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[[nodiscard]] char const* getPluginNamespace() const noexcept override
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{
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return mNamespace.c_str();
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}
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protected:
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std::string mNamespace{api::kDefaultNamespace};
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};
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// Write values into buffer
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template <typename T>
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void write(char*& buffer, T const& val)
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{
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std::memcpy(buffer, &val, sizeof(T));
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buffer += sizeof(T);
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}
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// Read values from buffer
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template <typename T>
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void read(char const*& buffer, T& val)
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{
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std::memcpy(&val, buffer, sizeof(T));
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buffer += sizeof(T);
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}
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inline size_t typeSize(nvinfer1::DataType type)
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{
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switch (type)
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{
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case nvinfer1::DataType::kBOOL: return 1UL;
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case nvinfer1::DataType::kFP8: return 1UL;
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case nvinfer1::DataType::kHALF: return 2UL;
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case nvinfer1::DataType::kBF16: return 2UL;
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case nvinfer1::DataType::kFLOAT: return 4UL;
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case nvinfer1::DataType::kINT8: return 1UL;
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case nvinfer1::DataType::kUINT8: return 1UL;
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case nvinfer1::DataType::kINT32: return 4UL;
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case nvinfer1::DataType::kINT64: return 8UL;
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}
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TLLM_THROW("Unknown dtype %d", static_cast<int>(type));
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return 0;
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}
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inline cudaDataType_t trtToCublasDtype(nvinfer1::DataType type)
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{
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switch (type)
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{
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case nvinfer1::DataType::kFLOAT: return CUDA_R_32F;
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case nvinfer1::DataType::kHALF: return CUDA_R_16F;
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#if defined(NV_TENSORRT_MAJOR) && NV_TENSORRT_MAJOR >= 9
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case nvinfer1::DataType::kBF16: return CUDA_R_16BF;
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#endif
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default: TLLM_THROW("Not supported data type for cuBLAS");
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}
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}
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// Like std::unique_ptr, but does not prevent generation of default copy constructor when used as class members.
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// The copy constructor produces nullptr. So the plugin default copy constructor will not really copy this, and
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// your clone() implementation is responsible for initializing such data members.
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// With this we can simplify clone() implementation when there are many data members including at least one unique_ptr.
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template <typename T, typename Del = std::default_delete<T>>
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class UniqPtrWNullCopy : public std::unique_ptr<T, Del>
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{
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public:
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using std::unique_ptr<T, Del>::unique_ptr;
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// for compatibility with std::make_unique
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explicit UniqPtrWNullCopy(std::unique_ptr<T, Del>&& src)
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: std::unique_ptr<T, Del>::unique_ptr{std::move(src)}
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{
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}
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// copy constructor produces nullptr
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UniqPtrWNullCopy(UniqPtrWNullCopy const&)
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: std::unique_ptr<T, Del>::unique_ptr{}
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{
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}
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};
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// for testing only
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void* getCommSessionHandle();
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} // namespace tensorrt_llm::plugins
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inline bool isBuilding()
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{
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auto constexpr key = "IS_BUILDING";
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auto const val = getenv(key);
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return val != nullptr && std::string(val) == "1";
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}
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#if ENABLE_MULTI_DEVICE
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#define NCCLCHECK(cmd) \
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do \
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{ \
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ncclResult_t r = cmd; \
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if (r != ncclSuccess) \
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{ \
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printf("Failed, NCCL error %s:%d '%s'\n", __FILE__, __LINE__, ncclGetErrorString(r)); \
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exit(EXIT_FAILURE); \
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} \
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} while (0)
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std::unordered_map<nvinfer1::DataType, ncclDataType_t>* getDtypeMap();
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std::map<std::set<int>, ncclComm_t>* getCommMap();
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void initCommMap(std::set<int> const& group);
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#endif // ENABLE_MULTI_DEVICE
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//! To save GPU memory, all the plugins share the same cublas and cublasLt handle globally.
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//! Get cublas and cublasLt handle for current cuda context
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std::shared_ptr<cublasHandle_t> getCublasHandle();
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std::shared_ptr<cublasLtHandle_t> getCublasLtHandle();
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#ifndef DEBUG
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#define PLUGIN_CHECK(status) \
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do \
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{ \
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if (status != 0) \
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abort(); \
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} while (0)
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#define ASSERT_PARAM(exp) \
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do \
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{ \
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if (!(exp)) \
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return STATUS_BAD_PARAM; \
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} while (0)
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#define ASSERT_FAILURE(exp) \
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do \
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{ \
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if (!(exp)) \
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return STATUS_FAILURE; \
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} while (0)
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#define CSC(call, err) \
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do \
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{ \
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cudaError_t cudaStatus = call; \
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if (cudaStatus != cudaSuccess) \
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{ \
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return err; \
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} \
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} while (0)
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#define DEBUG_PRINTF(...) \
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do \
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{ \
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} while (0)
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#else
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#define ASSERT_PARAM(exp) \
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do \
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{ \
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if (!(exp)) \
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{ \
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fprintf(stderr, "Bad param - " #exp ", %s:%d\n", __FILE__, __LINE__); \
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return STATUS_BAD_PARAM; \
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} \
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} while (0)
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#define ASSERT_FAILURE(exp) \
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do \
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{ \
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if (!(exp)) \
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{ \
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fprintf(stderr, "Failure - " #exp ", %s:%d\n", __FILE__, __LINE__); \
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return STATUS_FAILURE; \
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} \
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} while (0)
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#define CSC(call, err) \
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do \
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{ \
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cudaError_t cudaStatus = call; \
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if (cudaStatus != cudaSuccess) \
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{ \
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printf("%s %d CUDA FAIL %s\n", __FILE__, __LINE__, cudaGetErrorString(cudaStatus)); \
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return err; \
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} \
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} while (0)
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#define PLUGIN_CHECK(status) \
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{ \
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if (status != 0) \
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{ \
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DEBUG_PRINTF("%s %d CUDA FAIL %s\n", __FILE__, __LINE__, cudaGetErrorString(status)); \
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abort(); \
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} \
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}
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#define DEBUG_PRINTF(...) \
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do \
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{ \
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printf(__VA_ARGS__); \
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} while (0)
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#endif // DEBUG
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// Init with O(n) and retrieve with O(1)
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class PluginFieldParser
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{
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public:
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// field array must remain valid when calling getScalar() later.
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PluginFieldParser(int32_t nbFields, nvinfer1::PluginField const* fields);
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// delete to remind accidental mis-use (copy) which may result in false-alarm warnings about unused fields.
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PluginFieldParser(PluginFieldParser const&) = delete;
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PluginFieldParser& operator=(PluginFieldParser const&) = delete;
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// check if all fields are retrieved and emit warning if some of them are not.
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~PluginFieldParser();
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template <typename T>
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std::optional<T> getScalar(std::string_view const& name);
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private:
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nvinfer1::PluginField const* mFields;
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struct Record
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{
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Record(int32_t idx)
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: index{idx}
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{
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}
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int32_t const index;
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bool retrieved{false};
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};
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std::unordered_map<std::string_view, Record> mMap;
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};
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