Merge branch 'develop' of https://github.com/PaddlePaddle/Paddle into optimize-thread-pool
test=developrevert-14324-fix_vlog
Qiao Longfei
7 years ago
commit
fe4cd50286
@ -0,0 +1,109 @@
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// Copyright (c) 2018 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/details/sequential_execution_pass.h"
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#include <string>
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#include <unordered_map>
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#include <unordered_set>
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#include <vector>
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#include "paddle/fluid/framework/op_proto_maker.h"
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namespace paddle {
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namespace framework {
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namespace details {
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static bool IsSameOpDesc(OpDesc *op1, OpDesc *op2) {
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return op1->Type() == op2->Type() && op1->Inputs() == op2->Inputs() &&
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op1->Outputs() == op2->Outputs();
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}
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std::unique_ptr<ir::Graph> SequentialExecutionPass::ApplyImpl(
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std::unique_ptr<ir::Graph> graph) const {
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// FIXME(zjl): Insert dependencies between some distributed ops may cause
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// the multi_devices_graph_pass fails. So we skip these ops here.
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// Indeed, maybe we should not insert dependencies between these ops
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// casually, which may cause deadlock easily.
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// We should add more skipped distributed ops when found errors in
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// multi_devices_graph_pass
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static std::unordered_set<std::string> skip_dist_ops{
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"send", "recv", "send_barrier", "fetch_barrier"};
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auto &ops = Get<const std::vector<OpDesc *>>(kAllOpDescs);
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std::vector<ir::Node *> op_node_list;
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op_node_list.reserve(ops.size());
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std::unordered_map<ir::Node *, size_t> op_deps;
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std::unordered_map<ir::Node *, std::unordered_set<ir::Node *>> pending_ops;
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std::unordered_set<ir::Node *> ready_ops;
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for (ir::Node *node : graph->Nodes()) {
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if (!node->IsOp()) continue;
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std::unordered_set<ir::Node *> preceding_ops;
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for (auto *in : node->inputs) {
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PADDLE_ENFORCE(in->IsVar(),
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"Preceding Node of Op Nodes must be Var Node");
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if (in->inputs.empty()) continue;
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PADDLE_ENFORCE(in->inputs.size() == 1 && in->inputs[0]->IsOp(),
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"Preceding Op Node of Var Node must be unique");
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preceding_ops.insert(in->inputs[0]);
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pending_ops[in->inputs[0]].insert(node);
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}
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op_deps[node] = preceding_ops.size();
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if (preceding_ops.empty()) {
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ready_ops.insert(node);
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}
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}
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for (auto *op_desc : ops) {
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ir::Node *found_node = nullptr;
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for (auto *node : ready_ops) {
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if (IsSameOpDesc(op_desc, node->Op())) {
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PADDLE_ENFORCE(found_node == nullptr,
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"Found multiple op_desc in graph: %s", op_desc->Type());
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found_node = node;
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}
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}
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PADDLE_ENFORCE_NOT_NULL(found_node, "Cannot find op_desc in graph: %s",
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op_desc->Type());
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for (auto *pending_op : pending_ops[found_node]) {
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if (--op_deps.at(pending_op) == 0) {
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ready_ops.insert(pending_op);
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}
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}
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ready_ops.erase(found_node);
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if (skip_dist_ops.count(op_desc->Type()) == 0) {
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op_node_list.push_back(found_node);
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}
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}
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for (size_t i = 1; i < op_node_list.size(); ++i) {
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auto *dep_var = graph->CreateControlDepVar();
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op_node_list[i]->inputs.push_back(dep_var);
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op_node_list[i - 1]->outputs.push_back(dep_var);
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dep_var->outputs.push_back(op_node_list[i]);
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dep_var->inputs.push_back(op_node_list[i - 1]);
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VLOG(10) << "Add dependencies between " << op_node_list[i - 1]->Name()
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<< " and " << op_node_list[i]->Name();
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}
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return graph;
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}
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} // namespace details
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} // namespace framework
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} // namespace paddle
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REGISTER_PASS(sequential_execution_pass,
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paddle::framework::details::SequentialExecutionPass)
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.RequirePassAttr(paddle::framework::details::kAllOpDescs);
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@ -0,0 +1,34 @@
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// Copyright (c) 2018 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/fluid/framework/ir/graph.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 details {
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constexpr char kAllOpDescs[] = "all_op_descs";
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class SequentialExecutionPass : public ir::Pass {
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protected:
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std::unique_ptr<ir::Graph> ApplyImpl(
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std::unique_ptr<ir::Graph> graph) const override;
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};
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} // namespace details
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} // namespace framework
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} // namespace paddle
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@ -0,0 +1,58 @@
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/* Copyright (c) 2018 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/depthwise_conv_mkldnn_pass.h"
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#include "paddle/fluid/framework/ir/graph_pattern_detector.h"
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namespace paddle {
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namespace framework {
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namespace ir {
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#define GET_NODE(id, pattern) \
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PADDLE_ENFORCE(subgraph.count(pattern.RetrieveNode(#id)), \
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"pattern has no Node called %s", #id); \
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auto* id = subgraph.at(pattern.RetrieveNode(#id)); \
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PADDLE_ENFORCE_NOT_NULL(id, "subgraph has no node %s", #id);
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std::unique_ptr<ir::Graph> DepthwiseConvMKLDNNPass::ApplyImpl(
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std::unique_ptr<ir::Graph> graph) const {
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PADDLE_ENFORCE(graph.get());
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FusePassBase::Init("depthwise_conv_mkldnn_pass", graph.get());
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GraphPatternDetector gpd;
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auto* pattern = gpd.mutable_pattern();
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pattern->NewNode("depthwise_conv")
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->assert_is_op("depthwise_conv2d")
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->assert_op_attr("use_mkldnn", true);
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int found_depthwise_conv_mkldnn_count = 0;
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auto handler = [&](const GraphPatternDetector::subgraph_t& subgraph,
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Graph* g) {
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VLOG(3) << "handle DepthwiseConvMKLDNN fuse";
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GET_NODE(depthwise_conv, (*pattern));
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depthwise_conv->Op()->SetType("conv2d");
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found_depthwise_conv_mkldnn_count++;
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};
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gpd(graph.get(), handler);
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AddStatis(found_depthwise_conv_mkldnn_count);
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return graph;
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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(depthwise_conv_mkldnn_pass,
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paddle::framework::ir::DepthwiseConvMKLDNNPass);
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@ -0,0 +1,34 @@
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/* Copyright (c) 2018 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 DepthwiseConvMKLDNNPass : public FusePassBase {
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public:
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virtual ~DepthwiseConvMKLDNNPass() {}
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protected:
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std::unique_ptr<ir::Graph> ApplyImpl(
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std::unique_ptr<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 +1,123 @@
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// Copyright (c) 2018 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/depthwise_conv_mkldnn_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, const std::string& name,
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const std::vector<std::string>& inputs,
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const std::vector<std::string>& outputs, bool use_mkldnn = false) {
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auto* op = prog->MutableBlock(0)->AppendOp();
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op->SetType(type);
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op->SetAttr("use_mkldnn", use_mkldnn);
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op->SetAttr("name", name);
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op->SetInput("Input", {inputs[0]});
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op->SetInput("Filter", {inputs[1]});
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op->SetInput("Bias", {inputs[2]});
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op->SetOutput("Out", outputs);
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}
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// (a, weights, bias)->depthwise conv mkldnn->b
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// (b, weights2, bias2)->depthwise conv no mkldnn->c
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// (c, weights3, bias3)->conv mkldnn->d
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// (d, weights3, bias3)->conv no mkldnn->e
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ProgramDesc BuildProgramDesc() {
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ProgramDesc prog;
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for (auto& v : std::vector<std::string>(
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{"a", "b", "c", "d", "e", "weights", "bias", "weights2", "bias2",
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"weights3", "bias3", "weights4", "bias4"})) {
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auto* var = prog.MutableBlock(0)->Var(v);
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var->SetType(proto::VarType::SELECTED_ROWS);
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if (v == "weights" || v == "bias" || v == "weights2" || v == "bias2" ||
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v == "weights3" || v == "bias3" || v == "weights4" || v == "bias4") {
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var->SetPersistable(true);
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}
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}
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// depthwise conv with MKL-DNN
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SetOp(&prog, "depthwise_conv2d", "conv1",
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std::vector<std::string>({"a", "weights", "bias"}),
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std::vector<std::string>({"b"}), true);
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// depthwise conv without MKL-DNN
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SetOp(&prog, "depthwise_conv2d", "conv2",
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std::vector<std::string>({"b", "weights2", "bias2"}),
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std::vector<std::string>({"c"}), false);
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// conv with MKL-DNN
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SetOp(&prog, "conv2d", "conv3",
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std::vector<std::string>({"c", "weights3", "bias3"}),
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std::vector<std::string>({"d"}), true);
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// conv without MKL-dNN
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SetOp(&prog, "conv2d", "conv4",
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std::vector<std::string>({"d", "weights4", "bias4"}),
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std::vector<std::string>({"e"}), false);
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return prog;
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}
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TEST(DepthwiseConvMKLDNNPass, basic) {
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auto prog = BuildProgramDesc();
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std::unique_ptr<ir::Graph> graph(new ir::Graph(prog));
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auto pass = PassRegistry::Instance().Get("depthwise_conv_mkldnn_pass");
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struct counters {
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int mkldnn_depthwise_conv_nodes;
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int other_depthwise_conv_nodes;
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int mkldnn_conv_nodes;
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int other_conv_nodes;
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};
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counters before{1, 1, 1, 1};
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graph = pass->Apply(std::move(graph));
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// initialize counters before loop
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counters after{0, 0, 0, 0};
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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() == "conv2d") {
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if (boost::get<bool>(op->GetAttr("use_mkldnn")))
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after.mkldnn_conv_nodes++;
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else
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after.other_conv_nodes++;
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} else if (op->Type() == "depthwise_conv2d") {
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if (boost::get<bool>(op->GetAttr("use_mkldnn")))
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after.mkldnn_depthwise_conv_nodes++;
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else
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after.other_depthwise_conv_nodes++;
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}
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}
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}
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EXPECT_EQ(after.other_depthwise_conv_nodes,
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before.other_depthwise_conv_nodes);
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EXPECT_EQ(after.other_conv_nodes, before.other_conv_nodes);
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EXPECT_EQ(after.mkldnn_depthwise_conv_nodes,
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before.mkldnn_depthwise_conv_nodes - 1);
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EXPECT_EQ(after.mkldnn_conv_nodes, before.mkldnn_conv_nodes + 1);
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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(depthwise_conv_mkldnn_pass);
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