Add scale-matmul fuse pass (#23734)
joanna.wozna.intel
5 years ago
committed by
GitHub
parent
96add8a469
commit
12ba05ce0c
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/* Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved.
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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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http://www.apache.org/licenses/LICENSE-2.0
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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/mkldnn/scale_matmul_fuse_pass.h"
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#include <string>
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#include <vector>
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#include "paddle/fluid/framework/ir/graph_pattern_detector.h"
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#include "paddle/fluid/string/pretty_log.h"
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namespace paddle {
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namespace framework {
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namespace ir {
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using string::PrettyLogDetail;
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void ScaleMatmulFusePass::ApplyImpl(ir::Graph* graph) const {
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PADDLE_ENFORCE_NOT_NULL(graph,
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platform::errors::InvalidArgument(
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"Pointer to graph argument should not be NULL."));
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FusePassBase::Init("scale_matmul_fuse_pass", graph);
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GraphPatternDetector gpd;
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patterns::ScaleMatmul scale_matmul_pattern{gpd.mutable_pattern(),
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"scale_matmul"};
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scale_matmul_pattern();
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int found_scale_matmul_fuse_count = 0;
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auto handler = [&](const GraphPatternDetector::subgraph_t& subgraph,
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Graph* g) {
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GET_IR_NODE_FROM_SUBGRAPH(scale_in, scale_in, scale_matmul_pattern);
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GET_IR_NODE_FROM_SUBGRAPH(scale_op, scale_op, scale_matmul_pattern);
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GET_IR_NODE_FROM_SUBGRAPH(scale_out, scale_out, scale_matmul_pattern);
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GET_IR_NODE_FROM_SUBGRAPH(matmul_op, matmul_op, scale_matmul_pattern);
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if (scale_op->Op()->GetAttrIfExists<float>("bias") == 0.0) {
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auto matmul_alpha = matmul_op->Op()->GetAttrIfExists<float>("alpha");
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auto scale_scale = scale_op->Op()->GetAttrIfExists<float>("scale");
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PADDLE_ENFORCE_GT(matmul_alpha, 0.0f,
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platform::errors::InvalidArgument(
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"Alpha of matmul op should have positive value"));
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PADDLE_ENFORCE_GT(scale_scale, 0.0f,
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platform::errors::InvalidArgument(
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"Scale of scale op should have positive value"));
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std::string matmul_op_input_name;
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for (auto name : matmul_op->Op()->InputNames())
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for (auto input_name : matmul_op->Op()->Input(name))
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if (input_name == scale_out->Name()) matmul_op_input_name = name;
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PADDLE_ENFORCE_NE(
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matmul_op_input_name.empty(), true,
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platform::errors::NotFound("Operator after scale operator "
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"should have scale output as input"));
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matmul_op->Op()->SetAttr("alpha", matmul_alpha * scale_scale);
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matmul_op->Op()->SetInput(matmul_op_input_name,
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std::vector<std::string>({scale_in->Name()}));
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IR_NODE_LINK_TO(scale_in, matmul_op);
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GraphSafeRemoveNodes(graph, {scale_op, scale_out});
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found_scale_matmul_fuse_count++;
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}
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};
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gpd(graph, handler);
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AddStatis(found_scale_matmul_fuse_count);
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PrettyLogDetail("--- fused %d scale with matmul",
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found_scale_matmul_fuse_count);
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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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REGISTER_PASS(scale_matmul_fuse_pass,
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paddle::framework::ir::ScaleMatmulFusePass);
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@ -0,0 +1,33 @@
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/* Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved.
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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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http://www.apache.org/licenses/LICENSE-2.0
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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/fluid/framework/ir/fuse_pass_base.h"
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namespace paddle {
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namespace framework {
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namespace ir {
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class ScaleMatmulFusePass : public FusePassBase {
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public:
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virtual ~ScaleMatmulFusePass() {}
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protected:
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void ApplyImpl(ir::Graph* graph) const override;
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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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@ -0,0 +1,104 @@
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// Copyright (c) 2020 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/mkldnn/scale_matmul_fuse_pass.h"
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#include <gtest/gtest.h>
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namespace paddle {
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namespace framework {
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namespace ir {
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void SetOp(ProgramDesc* prog, const std::string& type,
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const std::vector<std::string>& inputs,
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const std::vector<std::string>& outputs, float scale = 1.0f,
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float bias = 0.0f) {
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auto* op = prog->MutableBlock(0)->AppendOp();
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op->SetType(type);
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if (type == "scale") {
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op->SetInput("X", {inputs[0]});
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op->SetAttr("scale", scale);
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op->SetAttr("bias", bias);
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} else if (type == "matmul") {
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op->SetInput("X", {inputs[0]});
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if (inputs.size() > 1) op->SetInput("Y", {inputs[1]});
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op->SetAttr("alpha", scale);
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} else {
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FAIL() << "Unexpected operator type.";
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}
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op->SetOutput("Out", {outputs[0]});
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}
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// a->scale->b
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// (b,c)->matmul->d
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ProgramDesc BuildProgramDesc(float scale, float bias, float alpha) {
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ProgramDesc prog;
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for (auto& v : std::vector<std::string>({"a", "b", "c", "d"})) {
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prog.MutableBlock(0)->Var(v);
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}
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SetOp(&prog, "scale", {"a"}, {"b"}, scale, bias);
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SetOp(&prog, "matmul", {"b", "c"}, {"d"}, alpha);
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return prog;
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}
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void MainTest(const ProgramDesc& prog, int removed_nodes_count,
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const std::vector<std::string> scale_in_out,
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const std::vector<std::string> matmul_in_out, float alpha) {
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std::unique_ptr<ir::Graph> graph(new ir::Graph(prog));
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int original_nodes_num = graph->Nodes().size();
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auto pass = PassRegistry::Instance().Get("scale_matmul_fuse_pass");
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graph.reset(pass->Apply(graph.release()));
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int current_nodes_num = graph->Nodes().size();
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for (auto* node : graph->Nodes()) {
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if (node->IsOp()) {
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auto* op = node->Op();
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if (op->Type() == "scale") {
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EXPECT_EQ(op->Input("X")[0], scale_in_out[0]);
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EXPECT_EQ(op->Output("Out")[0], scale_in_out[1]);
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} else if (op->Type() == "matmul") {
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EXPECT_EQ(op->Input("X")[0], matmul_in_out[0]);
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EXPECT_EQ(op->Input("Y")[0], matmul_in_out[1]);
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EXPECT_EQ(op->Output("Out")[0], matmul_in_out[2]);
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EXPECT_EQ(op->GetAttrIfExists<float>("alpha"), alpha);
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}
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}
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}
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EXPECT_EQ(original_nodes_num - removed_nodes_count, current_nodes_num);
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}
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TEST(ScaleMatmulFusePass, scale_matmul_with_no_bias) {
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auto bias = 0.0f;
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auto scale = 2.34f;
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auto alpha = 3.45f;
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int removed_nodes_count = 2;
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MainTest(BuildProgramDesc(scale, bias, alpha), removed_nodes_count, {},
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{"a", "c", "d"}, scale * alpha);
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}
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TEST(ScaleMatmulFusePass, scale_matmul_with_bias) {
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auto bias = 1.0f;
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auto scale = 2.34f;
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auto alpha = 3.45f;
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int removed_nodes_count = 0;
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MainTest(BuildProgramDesc(scale, bias, alpha), removed_nodes_count,
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{"a", "b"}, {"b", "c", "d"}, alpha);
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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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USE_PASS(scale_matmul_fuse_pass);
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