TensorRT-LLMs/cpp/tensorrt_llm/runtime/tllmBuffers.h
2023-09-20 00:29:41 -07:00

486 lines
13 KiB
C++

/*
* Copyright (c) 2022-2023, 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.
*/
#pragma once
#include "tensorrt_llm/common/assert.h"
#include "tensorrt_llm/common/cudaUtils.h"
#include "tensorrt_llm/common/logger.h"
#include "tensorrt_llm/runtime/common.h"
#include "tensorrt_llm/runtime/cudaStream.h"
#include "tensorrt_llm/runtime/iBuffer.h"
#include "tensorrt_llm/runtime/iTensor.h"
#include "tensorrt_llm/runtime/memoryCounters.h"
#include <NvInferRuntime.h>
#include <cuda_runtime_api.h>
#include <cstdlib>
#include <limits>
#include <memory>
#include <type_traits>
namespace tensorrt_llm::runtime
{
// CRTP base class
template <typename TDerived, MemoryType memoryType>
class BaseAllocator
{
public:
using ValueType = void;
using PointerType = ValueType*;
using SizeType = std::size_t;
PointerType allocate(SizeType n)
{
PointerType ptr{};
static_cast<TDerived*>(this)->allocateImpl(&ptr, n);
MemoryCounters::getInstance().allocate<memoryType>(n);
return ptr;
}
void deallocate(PointerType ptr, SizeType n)
{
if (ptr)
{
static_cast<TDerived*>(this)->deallocateImpl(ptr, n);
MemoryCounters::getInstance().deallocate<memoryType>(n);
}
}
[[nodiscard]] MemoryType constexpr getMemoryType() const
{
return memoryType;
}
};
class CudaAllocator : public BaseAllocator<CudaAllocator, MemoryType::kGPU>
{
friend class BaseAllocator<CudaAllocator, MemoryType::kGPU>;
public:
CudaAllocator() noexcept = default;
protected:
void allocateImpl(PointerType* ptr, SizeType n) // NOLINT(readability-convert-member-functions-to-static)
{
TLLM_CUDA_CHECK(::cudaMalloc(ptr, n));
}
void deallocateImpl( // NOLINT(readability-convert-member-functions-to-static)
PointerType ptr, [[gnu::unused]] SizeType n)
{
TLLM_CUDA_CHECK(::cudaFree(ptr));
}
};
class CudaAllocatorAsync : public BaseAllocator<CudaAllocatorAsync, MemoryType::kGPU>
{
friend class BaseAllocator<CudaAllocatorAsync, MemoryType::kGPU>;
public:
using CudaStreamPtr = std::shared_ptr<CudaStream>;
explicit CudaAllocatorAsync(CudaStreamPtr stream)
: mCudaStream(std::move(stream))
{
TLLM_CHECK_WITH_INFO(static_cast<bool>(mCudaStream), "Undefined CUDA stream");
}
CudaStreamPtr getCudaStream() const
{
return mCudaStream;
}
protected:
void allocateImpl(PointerType* ptr, SizeType n)
{
TLLM_CUDA_CHECK(::cudaMallocAsync(ptr, n, mCudaStream->get()));
}
void deallocateImpl(PointerType ptr, [[gnu::unused]] SizeType n)
{
TLLM_CUDA_CHECK(::cudaFreeAsync(ptr, mCudaStream->get()));
}
private:
CudaStreamPtr mCudaStream;
};
class PinnedAllocator : public BaseAllocator<PinnedAllocator, MemoryType::kPINNED>
{
friend class BaseAllocator<PinnedAllocator, MemoryType::kPINNED>;
public:
PinnedAllocator() noexcept = default;
protected:
void allocateImpl(PointerType* ptr, SizeType n) // NOLINT(readability-convert-member-functions-to-static)
{
TLLM_CUDA_CHECK(::cudaHostAlloc(ptr, n, cudaHostAllocDefault));
}
void deallocateImpl( // NOLINT(readability-convert-member-functions-to-static)
PointerType ptr, [[gnu::unused]] SizeType n)
{
TLLM_CUDA_CHECK(::cudaFreeHost(ptr));
}
};
class HostAllocator : public BaseAllocator<HostAllocator, MemoryType::kCPU>
{
friend class BaseAllocator<HostAllocator, MemoryType::kCPU>;
public:
HostAllocator() noexcept = default;
protected:
void allocateImpl(PointerType* ptr, SizeType n) // NOLINT(readability-convert-member-functions-to-static)
{
*ptr = std::malloc(n);
if (*ptr == nullptr)
{
throw std::bad_alloc();
}
}
void deallocateImpl( // NOLINT(readability-convert-member-functions-to-static)
PointerType ptr, [[gnu::unused]] SizeType n)
{
std::free(ptr);
}
};
template <MemoryType memoryType>
class BorrowingAllocator : public BaseAllocator<BorrowingAllocator<memoryType>, memoryType>
{
friend class BaseAllocator<BorrowingAllocator<memoryType>, memoryType>;
public:
using Base = BaseAllocator<BorrowingAllocator<memoryType>, memoryType>;
using typename Base::PointerType;
using typename Base::SizeType;
BorrowingAllocator(void* ptr, SizeType capacity)
: mPtr(ptr)
, mCapacity(capacity)
{
TLLM_CHECK_WITH_INFO(capacity == 0 || static_cast<bool>(mPtr), "Undefined pointer");
TLLM_CHECK_WITH_INFO(mCapacity >= 0, "Capacity must be non-negative");
}
protected:
void allocateImpl(PointerType* ptr, SizeType n) // NOLINT(readability-convert-member-functions-to-static)
{
if (n <= mCapacity)
{
*ptr = mPtr;
}
else
{
throw std::bad_alloc();
}
}
void deallocateImpl( // NOLINT(readability-convert-member-functions-to-static)
[[gnu::unused]] PointerType ptr, [[gnu::unused]] SizeType n)
{
}
private:
typename Base::PointerType mPtr;
typename Base::SizeType mCapacity;
};
using CpuBorrowingAllocator = BorrowingAllocator<MemoryType::kCPU>;
using GpuBorrowingAllocator = BorrowingAllocator<MemoryType::kGPU>;
using PinnedBorrowingAllocator = BorrowingAllocator<MemoryType::kPINNED>;
// Adopted from https://github.com/NVIDIA/TensorRT/blob/release/8.6/samples/common/buffers.h
//!
//! \brief The GenericBuffer class is a templated class for buffers.
//!
//! \details This templated RAII (Resource Acquisition Is Initialization) class handles the allocation,
//! deallocation, querying of buffers on both the device and the host.
//! It can handle data of arbitrary types because it stores byte buffers.
//! The template parameters AllocFunc and FreeFunc are used for the
//! allocation and deallocation of the buffer.
//! AllocFunc must be a functor that takes in (void** ptr, size_t size)
//! and returns bool. ptr is a pointer to where the allocated buffer address should be stored.
//! size is the amount of memory in bytes to allocate.
//! The boolean indicates whether or not the memory allocation was successful.
//! FreeFunc must be a functor that takes in (void* ptr) and returns void.
//! ptr is the allocated buffer address. It must work with nullptr input.
//!
template <typename TAllocator>
class GenericBuffer : virtual public IBuffer
{
public:
using AllocatorType = TAllocator;
//!
//! \brief Construct an empty buffer.
//!
explicit GenericBuffer(nvinfer1::DataType type, TAllocator allocator = {})
: GenericBuffer{0, type, std::move(allocator)} {};
//!
//! \brief Construct a buffer with the specified allocation size in number of elements.
//!
explicit GenericBuffer(std::size_t size, nvinfer1::DataType type, TAllocator allocator = {})
: GenericBuffer{size, size, type, std::move(allocator)} {};
GenericBuffer(GenericBuffer&& buf) noexcept
: mSize{buf.mSize}
, mCapacity{buf.mCapacity}
, mType{buf.mType}
, mAllocator{std::move(buf.mAllocator)}
, mBuffer{buf.mBuffer}
{
buf.mSize = 0;
buf.mCapacity = 0;
buf.mBuffer = nullptr;
}
GenericBuffer& operator=(GenericBuffer&& buf) noexcept
{
if (this != &buf)
{
mAllocator.deallocate(mBuffer, toBytes(mCapacity));
mSize = buf.mSize;
mCapacity = buf.mCapacity;
mType = buf.mType;
mAllocator = std::move(buf.mAllocator);
mBuffer = buf.mBuffer;
// Reset buf.
buf.mSize = 0;
buf.mCapacity = 0;
buf.mBuffer = nullptr;
}
return *this;
}
//!
//! \brief Returns pointer to underlying array.
//!
void* data() override
{
return mBuffer;
}
//!
//! \brief Returns pointer to underlying array.
//!
const void* data() const override
{
return mBuffer;
}
//!
//! \brief Returns the size (in number of elements) of the buffer.
//!
std::size_t getSize() const override
{
return mSize;
}
//!
//! \brief Returns the capacity of the buffer.
//!
std::size_t getCapacity() const override
{
return mCapacity;
}
//!
//! \brief Returns the type of the buffer.
//!
nvinfer1::DataType getDataType() const override
{
return mType;
}
//!
//! \brief Returns the memory type of the buffer.
//!
MemoryType getMemoryType() const override
{
return mAllocator.getMemoryType();
}
//!
//! \brief Resizes the buffer. This is a no-op if the new size is smaller than or equal to the current capacity.
//!
void resize(std::size_t newSize) override
{
if (newSize == 0)
{
release();
}
else if (mCapacity < newSize)
{
mAllocator.deallocate(mBuffer, toBytes(mCapacity));
mBuffer = mAllocator.allocate(toBytes(newSize));
mCapacity = newSize;
}
mSize = newSize;
}
//!
//! \brief Releases the buffer.
//!
void release() override
{
mAllocator.deallocate(mBuffer, toBytes(mCapacity));
mSize = 0;
mCapacity = 0;
mBuffer = nullptr;
}
~GenericBuffer() override
{
try
{
mAllocator.deallocate(mBuffer, toBytes(mCapacity));
}
catch (std::exception& e)
{
TLLM_LOG_EXCEPTION(e);
}
}
protected:
explicit GenericBuffer(std::size_t size, std::size_t capacity, nvinfer1::DataType type, TAllocator allocator = {})
: mSize{size}
, mCapacity{capacity}
, mType{type}
, mAllocator{std::move(allocator)}
, mBuffer{capacity > 0 ? mAllocator.allocate(toBytes(capacity)) : nullptr}
{
TLLM_CHECK(size <= capacity);
TLLM_CHECK(capacity == 0 || size > 0);
}
private:
std::size_t mSize{0}, mCapacity{0};
nvinfer1::DataType mType;
TAllocator mAllocator;
void* mBuffer;
};
using DeviceBuffer = GenericBuffer<CudaAllocatorAsync>;
using HostBuffer = GenericBuffer<HostAllocator>;
using PinnedBuffer = GenericBuffer<PinnedAllocator>;
template <typename T>
typename std::make_unsigned<T>::type nonNegative(T value)
{
TLLM_CHECK_WITH_INFO(value >= 0, "Value must be non-negative");
return static_cast<typename std::make_unsigned<T>::type>(value);
}
template <typename TAllocator>
class GenericTensor : virtual public ITensor, public GenericBuffer<TAllocator>
{
public:
using Base = GenericBuffer<TAllocator>;
//!
//! \brief Construct an empty tensor.
//!
explicit GenericTensor(nvinfer1::DataType type, TAllocator allocator = {})
: Base{type, std::move(allocator)}
{
mDims.nbDims = 0;
}
//!
//! \brief Construct a tensor with the specified allocation dimensions.
//!
explicit GenericTensor(nvinfer1::Dims const& dims, nvinfer1::DataType type, TAllocator allocator = {})
: Base{nonNegative(volume(dims)), type, std::move(allocator)}
, mDims{dims}
{
}
explicit GenericTensor(
nvinfer1::Dims const& dims, std::size_t capacity, nvinfer1::DataType type, TAllocator allocator = {})
: Base{nonNegative(volume(dims)), capacity, type, std::move(allocator)}
, mDims{dims}
{
}
GenericTensor(GenericTensor&& tensor) noexcept
: Base{std::move(tensor)}
, mDims{tensor.dims}
{
tensor.mDims.nbDims = 0;
}
GenericTensor& operator=(GenericTensor&& tensor) noexcept
{
if (this != &tensor)
{
Base::operator=(std::move(tensor));
mDims = tensor.dims;
// Reset tensor.
tensor.mDims.nbDims = 0;
}
return *this;
}
nvinfer1::Dims const& getShape() const override
{
return mDims;
}
void reshape(nvinfer1::Dims const& dims) override
{
Base::resize(nonNegative(volume(dims)));
mDims = dims;
}
void resize(std::size_t newSize) override
{
if (newSize != getSize())
{
using dimType = std::remove_reference_t<decltype(mDims.d[0])>;
auto constexpr max_size = std::numeric_limits<dimType>::max();
TLLM_CHECK_WITH_INFO(newSize <= max_size, "New size is too large. Use reshape() instead.");
Base::resize(newSize);
mDims.nbDims = 1;
mDims.d[0] = static_cast<dimType>(newSize);
}
}
void release() override
{
Base::release();
mDims.nbDims = 0;
}
private:
nvinfer1::Dims mDims{};
};
using DeviceTensor = GenericTensor<CudaAllocatorAsync>;
using HostTensor = GenericTensor<HostAllocator>;
using PinnedTensor = GenericTensor<PinnedAllocator>;
} // namespace tensorrt_llm::runtime