255 lines
8.2 KiB
C++
255 lines
8.2 KiB
C++
// Copyright (c) 2021 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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#include "paddle/fluid/framework/ir/matmul_scale_fuse_pass.h"
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#include <cmath>
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#include <string>
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#include "paddle/fluid/framework/ir/graph_pattern_detector.h"
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#include "paddle/fluid/framework/op_proto_maker.h"
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#include "paddle/fluid/framework/op_version_registry.h"
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#include "paddle/fluid/platform/enforce.h"
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namespace paddle::framework::ir {
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class Node;
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MatmulScaleFusePass::MatmulScaleFusePass() {
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AddOpCompat(OpCompat("matmul"))
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.AddInput("X")
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.IsTensor()
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.End()
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.AddInput("Y")
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.IsTensor()
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.End()
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.AddOutput("Out")
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.IsTensor()
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.End()
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.AddAttr("transpose_X")
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.IsType<bool>()
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.End()
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.AddAttr("transpose_Y")
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.IsType<bool>()
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.End()
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.AddAttr("alpha")
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.IsType<float>()
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.End();
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AddOpCompat(OpCompat("scale"))
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.AddInput("X")
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.IsTensor()
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.End()
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.AddInput("ScaleTensor")
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.IsTensor()
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.IsOptional()
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.End()
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.AddOutput("Out")
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.IsTensor()
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.End()
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.AddAttr("bias_after_scale")
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.IsType<bool>()
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.End()
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.AddAttr("scale")
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.End()
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.AddAttr("bias")
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.IsNumEQ(0.0f)
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.End();
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}
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MatmulV2ScaleFusePass::MatmulV2ScaleFusePass() {
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AddOpCompat(OpCompat("matmul_v2"))
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.AddInput("X")
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.IsTensor()
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.End()
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.AddInput("Y")
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.IsTensor()
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.End()
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.AddOutput("Out")
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.IsTensor()
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.End()
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.AddAttr("trans_x")
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.IsType<bool>()
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.End()
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.AddAttr("trans_y")
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.IsType<bool>()
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.End();
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AddOpCompat(OpCompat("scale"))
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.AddInput("X")
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.IsTensor()
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.End()
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.AddInput("ScaleTensor")
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.IsTensor()
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.IsOptional()
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.End()
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.AddOutput("Out")
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.IsTensor()
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.End()
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.AddAttr("bias_after_scale")
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.IsType<bool>()
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.End()
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.AddAttr("scale")
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.End()
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.AddAttr("bias")
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.IsNumEQ(0.0f)
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.End();
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}
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void MatmulScaleFusePass::ApplyImpl(ir::Graph* graph) const {
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PADDLE_ENFORCE_NOT_NULL(
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graph, common::errors::InvalidArgument("Graph cannot be nullptr."));
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std::string name_scope = "matmul_scale_fuse";
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FusePassBase::Init(name_scope, graph);
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GraphPatternDetector gpd;
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patterns::MatmulScale matmul_scale_pattern(gpd.mutable_pattern(), name_scope);
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matmul_scale_pattern();
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int found_count = 0;
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auto handler = [&](const GraphPatternDetector::subgraph_t& subgraph,
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Graph* g) {
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VLOG(4) << "matmul_scale_fuse pass";
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GET_IR_NODE_FROM_SUBGRAPH(matmul_in_x, matmul_in_x, matmul_scale_pattern);
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GET_IR_NODE_FROM_SUBGRAPH(matmul_in_y, matmul_in_y, matmul_scale_pattern);
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GET_IR_NODE_FROM_SUBGRAPH(matmul_op, matmul_op, matmul_scale_pattern);
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GET_IR_NODE_FROM_SUBGRAPH(scale_in_x, scale_in_x, matmul_scale_pattern);
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GET_IR_NODE_FROM_SUBGRAPH(scale_op, scale_op, matmul_scale_pattern);
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GET_IR_NODE_FROM_SUBGRAPH(scale_out, scale_out, matmul_scale_pattern);
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auto* scope = param_scope();
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float bias = PADDLE_GET_CONST(float, scale_op->Op()->GetAttr("bias"));
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if (std::abs(bias) > 1e-5) return;
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if (!IsCompat(subgraph, g)) {
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LOG(WARNING) << "matmul_scale_fuse_pass in op compat failed.";
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return;
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}
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float scale = PADDLE_GET_CONST(float, scale_op->Op()->GetAttr("scale"));
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float matmul_alpha =
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PADDLE_GET_CONST(float, matmul_op->Op()->GetAttr("alpha"));
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auto const& names = scale_op->Op()->InputNames();
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bool has_scale_tensor =
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std::find(names.begin(), names.end(), "ScaleTensor") != names.end();
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if (has_scale_tensor && !scale_op->Op()->Input("ScaleTensor").empty()) {
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std::string scale_var_name = scale_op->Op()->Input("ScaleTensor").front();
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auto* scale_var = scope->FindVar(scale_var_name);
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// ScaleTensor must be weight
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if (scale_var == nullptr) return;
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auto* scale_tensor = scale_var->GetMutable<DenseTensor>();
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scale = *(scale_tensor->data<float>());
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}
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OpDesc* matmul_desc = matmul_op->Op();
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matmul_desc->SetAttr("alpha", scale * matmul_alpha);
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matmul_desc->SetOutput("Out", {scale_out->Name()});
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if (!IsCompat(*matmul_desc)) {
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LOG(WARNING) << "matmul_scale_fuse_pass in out mul op compat failed.";
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return;
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}
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IR_NODE_LINK_TO(matmul_op, scale_out);
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GraphSafeRemoveNodes(graph, {scale_in_x, scale_op});
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++found_count;
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};
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gpd(graph, handler);
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AddStatis(found_count);
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}
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void MatmulV2ScaleFusePass::ApplyImpl(ir::Graph* graph) const {
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PADDLE_ENFORCE_NOT_NULL(
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graph, common::errors::InvalidArgument("Graph cannot be nullptr."));
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std::string name_scope = "matmul_v2_scale_fuse";
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FusePassBase::Init(name_scope, graph);
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GraphPatternDetector gpd;
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patterns::MatmulV2Scale matmul_v2_scale_pattern(gpd.mutable_pattern(),
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name_scope);
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matmul_v2_scale_pattern();
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int found_count = 0;
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auto handler = [&](const GraphPatternDetector::subgraph_t& subgraph,
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Graph* g) {
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VLOG(4) << "matmul_v2_scale_fuse pass";
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GET_IR_NODE_FROM_SUBGRAPH(
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matmul_v2_in_x, matmul_v2_in_x, matmul_v2_scale_pattern);
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GET_IR_NODE_FROM_SUBGRAPH(
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matmul_v2_in_y, matmul_v2_in_y, matmul_v2_scale_pattern);
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GET_IR_NODE_FROM_SUBGRAPH(
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matmul_v2_op, matmul_v2_op, matmul_v2_scale_pattern);
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GET_IR_NODE_FROM_SUBGRAPH(scale_in_x, scale_in_x, matmul_v2_scale_pattern);
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GET_IR_NODE_FROM_SUBGRAPH(scale_op, scale_op, matmul_v2_scale_pattern);
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GET_IR_NODE_FROM_SUBGRAPH(scale_out, scale_out, matmul_v2_scale_pattern);
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auto* scope = param_scope();
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float bias = PADDLE_GET_CONST(float, scale_op->Op()->GetAttr("bias"));
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if (std::abs(bias) > 1e-5) return;
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if (!IsCompat(subgraph, g)) {
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LOG(WARNING) << "matmul_v2_scale_fuse_pass in op compat failed.";
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return;
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}
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float scale = PADDLE_GET_CONST(float, scale_op->Op()->GetAttr("scale"));
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auto const& names = scale_op->Op()->InputNames();
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bool has_scale_tensor =
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std::find(names.begin(), names.end(), "ScaleTensor") != names.end();
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if (has_scale_tensor && !scale_op->Op()->Input("ScaleTensor").empty()) {
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std::string scale_var_name = scale_op->Op()->Input("ScaleTensor").front();
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auto* scale_var = scope->FindVar(scale_var_name);
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// ScaleTensor must be weight
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if (scale_var == nullptr) return;
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auto* scale_tensor = scale_var->GetMutable<DenseTensor>();
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scale = *(scale_tensor->data<float>());
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}
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auto* matmul_y =
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scope->FindVar(matmul_v2_in_y->Name())->GetMutable<DenseTensor>();
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auto y_data = matmul_y->mutable_data<float>(CPUPlace());
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for (int i = 0; i < matmul_y->numel(); ++i) {
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y_data[i] *= scale;
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}
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OpDesc* matmul_v2_desc = matmul_v2_op->Op();
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matmul_v2_desc->SetOutput("Out", {scale_out->Name()});
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if (!IsCompat(*matmul_v2_desc)) {
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LOG(WARNING) << "matmul_v2_scale_fuse_pass in out mul op compat failed.";
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return;
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}
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IR_NODE_LINK_TO(matmul_v2_op, scale_out);
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GraphSafeRemoveNodes(graph, {scale_in_x, scale_op});
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++found_count;
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};
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gpd(graph, handler);
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AddStatis(found_count);
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}
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} // namespace paddle::framework::ir
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REGISTER_PASS(matmul_scale_fuse_pass,
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paddle::framework::ir::MatmulScaleFusePass);
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REGISTER_PASS_CAPABILITY(matmul_scale_fuse_pass)
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.AddCombination(
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paddle::framework::compatible::OpVersionComparatorCombination()
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.LE("matmul", 1)
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.EQ("scale", 0));
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REGISTER_PASS(matmul_v2_scale_fuse_pass,
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paddle::framework::ir::MatmulV2ScaleFusePass);
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REGISTER_PASS_CAPABILITY(matmul_v2_scale_fuse_pass)
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.AddCombination(
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paddle::framework::compatible::OpVersionComparatorCombination()
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.EQ("matmul_v2", 0)
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.EQ("scale", 0));
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