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https://github.com/PaddlePaddle/FastDeploy.git
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lizexu123
6619298b50
* update w4afp8 * build.sh ok * support cuda_graph * fix * add test * fix max_tokens_per_expert * >=70 * fix * compute_max_tokens_from_prefix_sum in w4afp8 * compute_max_tokens use cub
50 lines
2.1 KiB
C++
50 lines
2.1 KiB
C++
// Copyright (c) 2022 PaddlePaddle Authors. 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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#pragma once
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#include <string>
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#include <vector>
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#include "helper.h"
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std::vector<paddle::Tensor> W4AFp8Gemm(
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const paddle::Tensor& input,
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const paddle::Tensor& weight,
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const paddle::Tensor&
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tokens, // If tokenpadding=0, this tensor represents the prefix sum of
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// tensors, otherwise it represents the number of tokens in
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// each group
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const paddle::Tensor& weight_scale,
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const paddle::optional<paddle::Tensor>& input_dequant_scale,
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const paddle::optional<paddle::Tensor>& max_tokens_per_expert,
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const int64_t token_padding_size,
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const int64_t max_tokens,
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const bool is_bfloat16);
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template <typename InputType, typename OutputType>
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void DisPatchW4AFp8GemmWrapper(const InputType* input,
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const InputType* weight,
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const int64_t* tokens,
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const float* input_dequant_scale,
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const float* weight_scale,
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OutputType* out,
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const int64_t token_padding_size,
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const int64_t max_tokens,
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const int num_experts,
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const int64_t M,
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const int64_t K,
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const int WeightScaleGroup,
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cudaStream_t stream,
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const int64_t* max_tokens_per_expert);
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