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https://github.com/NVIDIA/TensorRT-LLM.git
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d9522c5906
* chore: update cutlass to v3.8.0 Signed-off-by: Robin Kobus <19427718+Funatiq@users.noreply.github.com> * refactor: update include directives for consistency and organization in weightOnlyBatchedGemv headers Signed-off-by: Robin Kobus <19427718+Funatiq@users.noreply.github.com> * Fix fpA_intB_gemm compilation Signed-off-by: Robin Kobus <19427718+Funatiq@users.noreply.github.com> --------- Signed-off-by: Robin Kobus <19427718+Funatiq@users.noreply.github.com>
83 lines
3.1 KiB
C++
83 lines
3.1 KiB
C++
/*
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* Copyright (c) 2022-2024, 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 <cutlass/cutlass.h>
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#include <cutlass/numeric_conversion.h>
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#include <cutlass_extensions/interleaved_numeric_conversion.h>
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namespace tensorrt_llm
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{
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namespace kernels
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{
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namespace weight_only
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{
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template <typename AType, int WElemBits, bool Interleave>
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struct I2FConverter;
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template <typename AType, int WElemBits>
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struct I2FConverter<AType, WElemBits, true>
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{
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static_assert(std::is_same_v<AType, half> || std::is_same_v<AType, __nv_bfloat16>);
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static_assert(WElemBits == 4 || WElemBits == 8);
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using CutlassAType = std::conditional_t<std::is_same_v<AType, half>, cutlass::half_t, cutlass::bfloat16_t>;
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using CutlassWType = std::conditional_t<WElemBits == 4, cutlass::uint4b_t, uint8_t>;
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static constexpr int kConvertCount = 32 / WElemBits;
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using Converter = cutlass::FastInterleavedAndBiasedNumericArrayConverter<CutlassAType, CutlassWType, kConvertCount>;
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using CvtSrcType = typename Converter::source_type;
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using CvtResType = typename Converter::result_type;
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template <int N>
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__device__ __forceinline__ static void convert(void* src, void* dst)
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{
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static_assert(N % kConvertCount == 0);
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#pragma unroll
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for (int ii = 0; ii < N / kConvertCount; ++ii)
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{
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reinterpret_cast<CvtResType*>(dst)[ii] = Converter::convert(reinterpret_cast<CvtSrcType*>(src)[ii]);
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}
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}
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};
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template <typename AType, int WElemBits>
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struct I2FConverter<AType, WElemBits, false>
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{
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static_assert(std::is_same_v<AType, half> || std::is_same_v<AType, __nv_bfloat16>);
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static_assert(WElemBits == 4 || WElemBits == 8);
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using CutlassAType = std::conditional_t<std::is_same_v<AType, half>, cutlass::half_t, cutlass::bfloat16_t>;
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using CutlassWType = std::conditional_t<WElemBits == 4, cutlass::int4b_t, int8_t>;
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static constexpr int kConvertCount = 32 / WElemBits;
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using Converter = cutlass::NumericArrayConverter<CutlassAType, CutlassWType, kConvertCount>;
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using CvtSrcType = typename Converter::source_type;
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using CvtResType = typename Converter::result_type;
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template <int N>
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__device__ __forceinline__ static void convert(void* src, void* dst)
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{
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static_assert(N % kConvertCount == 0);
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#pragma unroll
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for (int ii = 0; ii < N / kConvertCount; ++ii)
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{
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reinterpret_cast<CvtResType*>(dst)[ii] = Converter::convert(reinterpret_cast<CvtSrcType*>(src)[ii]);
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}
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}
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};
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} // namespace weight_only
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} // namespace kernels
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} // namespace tensorrt_llm
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