A a pass to enable the use of cudnn (#19346)
* Add a interface to enable cudnn for inference. * Add cudnn_placement_pass. test=develop * Set the default value of cudnn_enabled_op_types to null. test=develop * Write the common basic class, placement_pass_base, to refine the codes. test=develop * Call EnableCUDNN in unittest. test=develop * Refine cudnn_placement_pass tester. * Enable the testing of cudnn_placement_pass in inference's unittest. test=develop * Add the check of op kernels. test=developfix_crf_doc
Yiqun Liu
6 years ago
committed by
GitHub
parent
cc443675e9
commit
c5548178b0
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/* Copyright (c) 2019 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/cudnn_placement_pass.h"
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REGISTER_PASS(cudnn_placement_pass, paddle::framework::ir::CUDNNPlacementPass)
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.RequirePassAttr("cudnn_enabled_op_types");
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/* Copyright (c) 2019 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 <string>
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#include <unordered_set>
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#include "paddle/fluid/framework/ir/placement_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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/*
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* Specifies which operators should use cuDNN.
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*/
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class CUDNNPlacementPass : public PlacementPassBase {
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private:
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const std::string GetPlacementName() const { return "cuDNN"; }
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const std::string GetAttrName() const { return "use_cudnn"; }
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const std::unordered_set<std::string> GetOpTypesList() const {
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return Get<std::unordered_set<std::string>>("cudnn_enabled_op_types");
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}
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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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// Copyright (c) 2019 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/cudnn_placement_pass.h"
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#include <gtest/gtest.h>
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#include "paddle/fluid/framework/ir/pass_tester_helper.h"
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#include "paddle/fluid/framework/operator.h"
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namespace paddle {
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namespace framework {
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namespace ir {
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void RegisterOpKernel() {
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static bool is_registered = false;
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if (!is_registered) {
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auto& all_kernels = OperatorWithKernel::AllOpKernels();
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platform::CUDAPlace place = platform::CUDAPlace(0);
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OpKernelType plain_kernel_type =
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OpKernelType(proto::VarType::FP32, place, DataLayout::kAnyLayout,
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LibraryType::kPlain);
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OpKernelType cudnn_kernel_type =
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OpKernelType(proto::VarType::FP32, place, DataLayout::kAnyLayout,
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LibraryType::kCUDNN);
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auto fake_kernel_func = [](const ExecutionContext&) -> void {
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static int num_calls = 0;
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num_calls++;
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};
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all_kernels["conv2d"][cudnn_kernel_type] = fake_kernel_func;
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all_kernels["pool2d"][cudnn_kernel_type] = fake_kernel_func;
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all_kernels["depthwise_conv2d"][plain_kernel_type] = fake_kernel_func;
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all_kernels["relu"][plain_kernel_type] = fake_kernel_func;
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is_registered = true;
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}
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}
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void MainTest(std::initializer_list<std::string> cudnn_enabled_op_types,
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unsigned expected_use_cudnn_true_count) {
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// operator use_cudnn
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// --------------------------------------------------
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// (a,b)->concat->c -
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// (c,weights,bias)->conv2d->f false
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// f->relu->g -
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// g->pool2d->h false
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// (h,weights2,bias2)->depthwise_conv2d->k false
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// k->relu->l -
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Layers layers;
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VarDesc* a = layers.data("a");
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VarDesc* b = layers.data("b");
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VarDesc* c = layers.concat(std::vector<VarDesc*>({a, b}));
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VarDesc* weights_0 = layers.data("weights_0");
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VarDesc* bias_0 = layers.data("bias_0");
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VarDesc* f = layers.conv2d(c, weights_0, bias_0, false);
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VarDesc* g = layers.relu(f);
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VarDesc* h = layers.pool2d(g, false);
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VarDesc* weights_1 = layers.data("weights_1");
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VarDesc* bias_1 = layers.data("bias_1");
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VarDesc* k = layers.depthwise_conv2d(h, weights_1, bias_1, false);
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layers.relu(k);
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RegisterOpKernel();
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std::unique_ptr<ir::Graph> graph(new ir::Graph(layers.main_program()));
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auto pass = PassRegistry::Instance().Get("cudnn_placement_pass");
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pass->Set("cudnn_enabled_op_types",
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new std::unordered_set<std::string>(cudnn_enabled_op_types));
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graph.reset(pass->Apply(graph.release()));
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unsigned use_cudnn_true_count = 0;
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for (auto* node : graph->Nodes()) {
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if (node->IsOp() && node->Op()) {
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auto* op = node->Op();
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if (op->HasAttr("use_cudnn") &&
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boost::get<bool>(op->GetAttr("use_cudnn"))) {
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++use_cudnn_true_count;
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}
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}
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}
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EXPECT_EQ(use_cudnn_true_count, expected_use_cudnn_true_count);
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}
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TEST(CUDNNPlacementPass, enable_conv2d) {
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// 1 conv2d
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MainTest({"conv2d"}, 1);
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}
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TEST(CUDNNPlacementPass, enable_relu_pool) {
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// 1 conv2d + 1 pool2d
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MainTest({"conv2d", "pool2d"}, 2);
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}
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TEST(CUDNNPlacementPass, enable_all) {
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// 1 conv2d + 1 pool2d
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// depthwise_conv2d doesnot have CUDNN kernel.
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MainTest({}, 2);
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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(cudnn_placement_pass);
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@ -0,0 +1,69 @@
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/* Copyright (c) 2019 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/placement_pass_base.h"
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#include <memory>
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#include <string>
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#include "paddle/fluid/framework/operator.h"
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namespace paddle {
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namespace framework {
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namespace ir {
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void PlacementPassBase::ApplyImpl(ir::Graph* graph) const {
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VLOG(3) << "Applies " << GetPlacementName() << " placement strategy.";
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std::string attr_name = GetAttrName();
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const auto& op_types_list = GetOpTypesList();
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if (!graph->Has(attr_name)) {
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graph->Set<bool>(attr_name, new bool(true));
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}
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for (const Node* n : graph->Nodes()) {
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if (n->IsOp()) {
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auto* op = n->Op();
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if ((op->HasAttr(attr_name) || op->HasProtoAttr(attr_name)) &&
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IsSupport(op->Type())) {
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if (op_types_list.empty()) {
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op->SetAttr(attr_name, true);
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} else if (std::find(op_types_list.begin(), op_types_list.end(),
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n->Name()) != op_types_list.end()) {
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op->SetAttr(attr_name, true);
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}
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}
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}
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}
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}
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bool PlacementPassBase::IsSupport(const std::string& op_type) const {
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if (GetAttrName() == "use_cudnn") {
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auto& all_kernels = OperatorWithKernel::AllOpKernels();
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auto it = all_kernels.find(op_type);
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if (it == all_kernels.end()) {
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// All control operators don't have kernel.
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return false;
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}
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for (auto& kernel_pair : it->second) {
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if (platform::is_gpu_place(kernel_pair.first.place_) &&
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(kernel_pair.first.library_type_ == LibraryType::kCUDNN)) {
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return true;
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}
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}
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} else if (GetAttrName() == "use_mkldnn") {
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return true;
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}
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return false;
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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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/* Copyright (c) 2019 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 <string>
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#include <unordered_set>
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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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* Specifies which operators should use cuDNN.
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*/
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class PlacementPassBase : public Pass {
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protected:
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void ApplyImpl(ir::Graph* graph) const override;
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virtual const std::string GetPlacementName() const = 0;
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virtual const std::string GetAttrName() const = 0;
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virtual const std::unordered_set<std::string> GetOpTypesList() const = 0;
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private:
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bool IsSupport(const std::string& op_type) 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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