wehub-resource-sync
116 lines
4.9 KiB
C++
116 lines
4.9 KiB
C++
// Copyright (c) 2023 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 "paddle/phi/backends/gpu/gpu_context.h"
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#include "paddle/phi/kernels/funcs/layer_norm_impl.cu.h"
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namespace phi {
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namespace fusion {
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// NOTE: T must be the same as OutType in ComputeBackward
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template <typename T, typename InType = T, typename OutType = T>
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class AttnLayerNorm {
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public:
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AttnLayerNorm(const GPUContext& dev_ctx,
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float epsilon,
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int64_t batch_size,
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int64_t feature_size)
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: dev_ctx_(dev_ctx),
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epsilon_(epsilon),
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batch_size_(batch_size),
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feature_size_(feature_size) {}
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~AttnLayerNorm() {}
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void ComputeForward(const InType* x_data,
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const funcs::LayerNormParamType<T>* scale_data,
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const funcs::LayerNormParamType<T>* bias_data,
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OutType* y_data,
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funcs::LayerNormParamType<T>* mean_data,
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funcs::LayerNormParamType<T>* var_data,
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const float* dequant_out_scale_data = nullptr,
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const int quant_out_scale_offset = 0,
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const float quant_in_scale = 1.0,
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const int quant_round_type = 1,
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const float quant_max_bound = 127.0,
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const float quant_min_bound = -127.0) {
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auto stream = dev_ctx_.stream();
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// TODO(large-tensor): generic kernel launch uses int32 grid dim
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PADDLE_ENFORCE_LE_INT_MAX(batch_size_, "batch_size");
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switch (funcs::GetDesiredBlockDim(feature_size_)) {
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FIXED_BLOCK_DIM_CASE(
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funcs::LayerNormForward<T,
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funcs::LayerNormParamType<T>,
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kBlockDim,
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false,
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InType,
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OutType>
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<<<batch_size_, kBlockDim, 0, stream>>>(x_data,
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scale_data,
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bias_data,
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y_data,
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mean_data,
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var_data,
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epsilon_,
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feature_size_,
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dequant_out_scale_data,
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quant_out_scale_offset,
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quant_in_scale,
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quant_round_type,
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quant_max_bound,
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quant_min_bound));
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default:
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PADDLE_THROW(common::errors::InvalidArgument(
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"Feature_size must be larger than 1"));
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break;
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}
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}
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void ComputeBackward(const T* x_data,
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const T* d_y_data,
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const funcs::LayerNormParamType<T>* scale_data,
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const funcs::LayerNormParamType<T>* mean_data,
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const funcs::LayerNormParamType<T>* var_data,
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T* d_x_data,
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funcs::LayerNormParamType<T>* d_scale_data,
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funcs::LayerNormParamType<T>* d_bias_data) {
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funcs::LayerNormBackward<T, funcs::LayerNormParamType<T>>(x_data,
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d_y_data,
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scale_data,
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mean_data,
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var_data,
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d_x_data,
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d_scale_data,
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d_bias_data,
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epsilon_,
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batch_size_,
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feature_size_,
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dev_ctx_);
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}
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private:
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const GPUContext& dev_ctx_;
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int64_t batch_size_;
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int64_t feature_size_;
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float epsilon_;
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};
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} // namespace fusion
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} // namespace phi
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