wehub-resource-sync
93 lines
3.2 KiB
C++
93 lines
3.2 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 <mutex>
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#include <string>
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#include <unordered_set>
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#include "paddle/fluid/framework/ir/fuse_pass_base.h"
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#include "paddle/fluid/framework/ir/graph.h"
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#include "paddle/fluid/framework/ir/graph_pattern_detector.h"
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#include "paddle/fluid/framework/ir/pass.h"
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namespace paddle {
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namespace framework {
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namespace ir {
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/*
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* Fuse the FeedForward in attention
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* Forward:
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* 1. layer_norm -> linear1 -> activation -> dropout1 -> linear2 -> dropout2
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* -> residual_add (pre_layer_norm)
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* 2. linear1 -> activation -> dropout1 -> linear2 -> dropout2 -> residual_add
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* -> layer_norm (pose_layer_norm)
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* other cases: may delete mp, residual_add, dropout1, dropout2 operators
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* Backward:
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* 1. residual_add_grad -> dropout2_grad -> linear2_grad -> dropout1_grad ->
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* activation_grad -> linear1_grad -> layer_norm_grad (pre_layer_norm)
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* 2. layer_norm_grad -> residual_add_grad -> dropout2_grad -> linear2_grad ->
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* dropout1_grad -> activation_grad -> linear1_grad (pose_layer_norm)
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* other cases: may delete mp, residual_add_grad, dropout1_grad, dropout2_grad
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* operators
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*/
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class Graph;
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class Node;
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class FusedFeedForwardPass : public FusePassBase {
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public:
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virtual ~FusedFeedForwardPass() {}
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protected:
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// Used for pattern created variable node transfer
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// between corresponding forward operator and backward operator.
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struct DropoutNode {
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Node *dropout_out_node_1;
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Node *dropout_mask_node_1;
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Node *dropout_out_node_2;
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Node *dropout_mask_node_2;
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DropoutNode()
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: dropout_out_node_1(nullptr),
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dropout_mask_node_1(nullptr),
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dropout_out_node_2(nullptr),
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dropout_mask_node_2(nullptr) {}
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};
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typedef std::unordered_map<Node *, DropoutNode> Cache;
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const std::string scope_name{"fused_feedforward"};
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void ApplyImpl(ir::Graph *graph) const override;
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ir::Graph *FusedFeedForwardFwd(ir::Graph *graph,
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bool use_mp,
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bool pre_layer_norm,
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bool add_residual,
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bool use_dropout_1,
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bool use_dropout_2,
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Cache *dropout_nodes_map) const;
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ir::Graph *FusedFeedForwardBwd(ir::Graph *graph,
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bool use_mp,
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bool pre_layer_norm,
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bool add_residual,
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bool use_dropout_1,
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bool use_dropout_2,
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Cache *dropout_nodes_map) const;
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};
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} // namespace ir
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} // namespace framework
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} // namespace paddle
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