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https://github.com/PaddlePaddle/FastDeploy.git
synced 2026-04-23 00:17:25 +08:00
gongweibao
67 lines
2.3 KiB
C++
67 lines
2.3 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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#pragma once
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#include "cute/tensor.hpp"
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#include "cutlass_extensions/gemm_configs.h"
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#include "common/cudaUtils.h"
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namespace kernels {
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namespace cutlass_kernels {
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template <class TileShape, class ClusterShape, class ActivationType>
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struct should_filter_sm90_gemm_problem_shape {
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#ifdef FAST_BUILD
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constexpr static int TILE_K =
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128 * 8 / cutlass::sizeof_bits<ActivationType>::value;
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using SupportedCtaShape =
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cute::Shape<cute::_128, cute::_128, cute::Int<TILE_K>>;
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using SupportedCgaShape = cute::Shape<cute::_1, cute::_1, cute::_1>;
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constexpr static bool value =
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!cute::is_same_v<SupportedCtaShape, TileShape> ||
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!cute::is_same_v<SupportedCgaShape, ClusterShape>;
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#else
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constexpr static bool value = false;
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#endif
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};
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template <class TileShape, class ClusterShape, class ActivationType>
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constexpr static bool should_filter_sm90_gemm_problem_shape_v =
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should_filter_sm90_gemm_problem_shape<TileShape,
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ClusterShape,
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ActivationType>::value;
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std::vector<cutlass_extensions::CutlassGemmConfig> get_candidate_configs(
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int sm,
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int const max_split_k,
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cutlass_extensions::CutlassGemmConfig::CandidateConfigTypeParam const);
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cutlass_extensions::CutlassGemmConfig estimate_best_config_from_occupancies(
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std::vector<cutlass_extensions::CutlassGemmConfig> const& candidate_configs,
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std::vector<int> const& occupancies,
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int64_t const m,
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int64_t const n,
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int64_t const k,
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int64_t const num_experts,
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int const split_k_limit,
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size_t const workspace_bytes,
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int const multi_processor_count,
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int const is_weight_only);
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} // namespace cutlass_kernels
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} // namespace kernels
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