mirror of
https://github.com/NVIDIA/TensorRT-LLM.git
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57 lines
2.0 KiB
C++
57 lines
2.0 KiB
C++
/*
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* Copyright (c) 2019-2023, 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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#pragma once
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#include "tensorrt_llm/common/quantization.h"
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#include <cuda_fp16.h>
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#include <cuda_runtime.h>
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namespace tensorrt_llm
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{
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#define PadUpFn(X, Y) ((X + Y - 1) / (Y) * (Y))
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// totalCloumn should be in SFMatrix, not activation Matrix, so no sfVecSize needed.
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inline int computeSFSize(int totalRow, int totalColumn)
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{
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int paddedRow = PadUpFn(totalRow, 128);
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int paddedColumn = PadUpFn(totalColumn, 4);
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return paddedRow * paddedColumn;
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}
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namespace kernels
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{
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template <typename T>
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void invokeQuantization(
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int8_t* dst, T const* src, int64_t const size, float const* scalePtr, cudaStream_t stream = 0, int maxGirdSize = 0);
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template <typename T, typename QuantT>
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void invokePerTokenQuantization(QuantT* dst, T const* src, int64_t const numRows, int64_t const numCols,
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float const* clampPtr, float* scalePtr, float* sumPtr, tensorrt_llm::common::QuantMode quantMode,
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cudaStream_t stream = 0);
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template <typename T>
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void invokeFP4Quantization(int m, int n, T const* input, float const* globalScale, int64_t* output, int32_t* SFOuput,
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bool useUE8M0, int multiProcessorCount, cudaStream_t stream = 0);
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template <typename T>
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void invokeBatchedFP4Quantization(int b, int m, int n, T const* input, float const* globalScale, int64_t* output,
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int32_t* SFOuput, bool useUE8M0, int multiProcessorCount, cudaStream_t stream = 0);
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} // namespace kernels
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} // namespace tensorrt_llm
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