Merge remote-tracking branch 'origin/develop' into fix/sequence_pad

test=develop

Author: dzhwinter

paddle/fluid/API.spec

@@ -67,8 +67,8 @@ paddle.fluid.layers.conv3d ArgSpec(args=['input', 'num_filters', 'filter_size',
 paddle.fluid.layers.sequence_pool ArgSpec(args=['input', 'pool_type', 'is_test'], varargs=None, keywords=None, defaults=(False,))
 paddle.fluid.layers.sequence_softmax ArgSpec(args=['input', 'use_cudnn', 'name'], varargs=None, keywords=None, defaults=(False, None))
 paddle.fluid.layers.softmax ArgSpec(args=['input', 'use_cudnn', 'name'], varargs=None, keywords=None, defaults=(True, None))
-paddle.fluid.layers.pool2d ArgSpec(args=['input', 'pool_size', 'pool_type', 'pool_stride', 'pool_padding', 'global_pooling', 'use_cudnn', 'ceil_mode', 'name'], varargs=None, keywords=None, defaults=(-1, 'max', 1, 0, False, True, False, None))
-paddle.fluid.layers.pool3d ArgSpec(args=['input', 'pool_size', 'pool_type', 'pool_stride', 'pool_padding', 'global_pooling', 'use_cudnn', 'ceil_mode', 'name'], varargs=None, keywords=None, defaults=(-1, 'max', 1, 0, False, True, False, None))
+paddle.fluid.layers.pool2d ArgSpec(args=['input', 'pool_size', 'pool_type', 'pool_stride', 'pool_padding', 'global_pooling', 'use_cudnn', 'ceil_mode', 'name', 'exclusive'], varargs=None, keywords=None, defaults=(-1, 'max', 1, 0, False, True, False, None, True))
+paddle.fluid.layers.pool3d ArgSpec(args=['input', 'pool_size', 'pool_type', 'pool_stride', 'pool_padding', 'global_pooling', 'use_cudnn', 'ceil_mode', 'name', 'exclusive'], varargs=None, keywords=None, defaults=(-1, 'max', 1, 0, False, True, False, None, True))
 paddle.fluid.layers.batch_norm ArgSpec(args=['input', 'act', 'is_test', 'momentum', 'epsilon', 'param_attr', 'bias_attr', 'data_layout', 'in_place', 'name', 'moving_mean_name', 'moving_variance_name', 'do_model_average_for_mean_and_var', 'fuse_with_relu'], varargs=None, keywords=None, defaults=(None, False, 0.9, 1e-05, None, None, 'NCHW', False, None, None, None, False, False))
 paddle.fluid.layers.beam_search_decode ArgSpec(args=['ids', 'scores', 'beam_size', 'end_id', 'name'], varargs=None, keywords=None, defaults=(None,))
 paddle.fluid.layers.conv2d_transpose ArgSpec(args=['input', 'num_filters', 'output_size', 'filter_size', 'padding', 'stride', 'dilation', 'groups', 'param_attr', 'bias_attr', 'use_cudnn', 'act', 'name'], varargs=None, keywords=None, defaults=(None, None, 0, 1, 1, None, None, None, True, None, None))
@@ -103,7 +103,7 @@ paddle.fluid.layers.beam_search ArgSpec(args=['pre_ids', 'pre_scores', 'ids', 's
 paddle.fluid.layers.row_conv ArgSpec(args=['input', 'future_context_size', 'param_attr', 'act'], varargs=None, keywords=None, defaults=(None, None))
 paddle.fluid.layers.multiplex ArgSpec(args=['inputs', 'index'], varargs=None, keywords=None, defaults=None)
 paddle.fluid.layers.layer_norm ArgSpec(args=['input', 'scale', 'shift', 'begin_norm_axis', 'epsilon', 'param_attr', 'bias_attr', 'act', 'name'], varargs=None, keywords=None, defaults=(True, True, 1, 1e-05, None, None, None, None))
-paddle.fluid.layers.softmax_with_cross_entropy ArgSpec(args=['logits', 'label', 'soft_label', 'ignore_index'], varargs=None, keywords=None, defaults=(False, -100))
+paddle.fluid.layers.softmax_with_cross_entropy ArgSpec(args=['logits', 'label', 'soft_label', 'ignore_index', 'numeric_stable_mode'], varargs=None, keywords=None, defaults=(False, -100, False))
 paddle.fluid.layers.smooth_l1 ArgSpec(args=['x', 'y', 'inside_weight', 'outside_weight', 'sigma'], varargs=None, keywords=None, defaults=(None, None, None))
 paddle.fluid.layers.one_hot ArgSpec(args=['input', 'depth'], varargs=None, keywords=None, defaults=None)
 paddle.fluid.layers.autoincreased_step_counter ArgSpec(args=['counter_name', 'begin', 'step'], varargs=None, keywords=None, defaults=(None, 1, 1))
@@ -178,6 +178,7 @@ paddle.fluid.layers.affine_grid ArgSpec(args=['theta', 'out_shape', 'name'], var
 paddle.fluid.layers.sequence_reverse ArgSpec(args=['x', 'name'], varargs=None, keywords=None, defaults=(None,))
 paddle.fluid.layers.affine_channel ArgSpec(args=['x', 'scale', 'bias', 'data_layout', 'name'], varargs=None, keywords=None, defaults=(None, None, 'NCHW', None))
 paddle.fluid.layers.hash ArgSpec(args=['input', 'hash_size', 'num_hash', 'name'], varargs=None, keywords=None, defaults=(1, None))
+paddle.fluid.layers.grid_sampler ArgSpec(args=['x', 'grid', 'name'], varargs=None, keywords=None, defaults=(None,))
 paddle.fluid.layers.log_loss ArgSpec(args=['input', 'label', 'epsilon', 'name'], varargs=None, keywords=None, defaults=(0.0001, None))
 paddle.fluid.layers.add_position_encoding ArgSpec(args=['input', 'alpha', 'beta', 'name'], varargs=None, keywords=None, defaults=(None,))
 paddle.fluid.layers.data ArgSpec(args=['name', 'shape', 'append_batch_size', 'dtype', 'lod_level', 'type', 'stop_gradient'], varargs=None, keywords=None, defaults=(True, 'float32', 0, VarType.LOD_TENSOR, True))

paddle/fluid/framework/details/CMakeLists.txt

@@ -35,13 +35,15 @@ if(WITH_GPU)
           all_reduce_op_handle reduce_op_handle broadcast_op_handle data_balance_op_handle graph graph_helper pass)
 endif()
 
+cc_library(sequential_execution_pass SRCS sequential_execution_pass.cc DEPS graph graph_helper pass)
+
 cc_library(multi_devices_graph_pass SRCS multi_devices_graph_pass.cc DEPS multi_devices_helper computation_op_handle
         scale_loss_grad_op_handle rpc_op_handle all_reduce_op_handle reduce_op_handle broadcast_op_handle data_balance_op_handle fused_broadcast_op_handle)
 
 if(WITH_GPU)
-  cc_library(ssa_graph_executor SRCS ssa_graph_executor.cc DEPS graph framework_proto reference_count_pass)
+  cc_library(ssa_graph_executor SRCS ssa_graph_executor.cc DEPS graph framework_proto reference_count_pass sequential_execution_pass)
 else()
-  cc_library(ssa_graph_executor SRCS ssa_graph_executor.cc DEPS graph framework_proto)
+  cc_library(ssa_graph_executor SRCS ssa_graph_executor.cc DEPS graph framework_proto sequential_execution_pass)
 endif()
 
 cc_library(threaded_ssa_graph_executor SRCS threaded_ssa_graph_executor.cc DEPS fetch_op_handle ssa_graph_executor scope

paddle/fluid/framework/details/build_strategy.cc

@@ -16,6 +16,7 @@ limitations under the License. */
 
 #include "paddle/fluid/framework/details/multi_devices_graph_check_pass.h"
 #include "paddle/fluid/framework/details/multi_devices_graph_print_pass.h"
+#include "paddle/fluid/framework/details/sequential_execution_pass.h"
 #include "paddle/fluid/framework/ir/graph.h"
 #include "paddle/fluid/framework/ir/graph_viz_pass.h"
 
@@ -27,6 +28,10 @@ class ParallelExecutorPassBuilder : public ir::PassBuilder {
  public:
   explicit ParallelExecutorPassBuilder(const BuildStrategy &strategy)
       : ir::PassBuilder(), strategy_(strategy) {
+    if (strategy_.enable_sequential_execution_) {
+      AppendPass("sequential_execution_pass");
+    }
+
     // Add a graph viz pass to record a graph.
     if (!strategy_.debug_graphviz_path_.empty()) {
       auto viz_pass = AppendPass("graph_viz_pass");
@@ -110,6 +115,11 @@ std::unique_ptr<ir::Graph> BuildStrategy::Apply(
       pass->Erase("nccl_ctxs");
       pass->SetNotOwned<platform::NCCLContextMap>("nccl_ctxs", nctx);
 #endif
+    } else if (pass->Type() == "sequential_execution_pass") {
+      pass->Erase(kAllOpDescs);
+      pass->Set<const std::vector<OpDesc *>>(
+          kAllOpDescs,
+          new std::vector<OpDesc *>(main_program.Block(0).AllOps()));
     }
     graph = pass->Apply(std::move(graph));
   }
@@ -125,3 +135,4 @@ USE_PASS(multi_batch_merge_pass);
 USE_PASS(multi_devices_pass);
 USE_PASS(multi_devices_check_pass);
 USE_PASS(multi_devices_print_pass);
+USE_PASS(sequential_execution_pass);

paddle/fluid/framework/details/build_strategy.h

@@ -69,6 +69,8 @@ struct BuildStrategy {
 
   bool enable_data_balance_{false};
 
+  bool enable_sequential_execution_{false};
+
   bool fuse_broadcast_op_{false};
 
   // User normally doesn't need to call this API.

paddle/fluid/framework/details/sequential_execution_pass.cc

@@ -0,0 +1,109 @@
+// Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
+//
+// Licensed under the Apache License, Version 2.0 (the "License");
+// you may not use this file except in compliance with the License.
+// You may obtain a copy of the License at
+//
+//     http://www.apache.org/licenses/LICENSE-2.0
+//
+// Unless required by applicable law or agreed to in writing, software
+// distributed under the License is distributed on an "AS IS" BASIS,
+// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+// See the License for the specific language governing permissions and
+// limitations under the License.
+
+#include "paddle/fluid/framework/details/sequential_execution_pass.h"
+#include <string>
+#include <unordered_map>
+#include <unordered_set>
+#include <vector>
+#include "paddle/fluid/framework/op_proto_maker.h"
+
+namespace paddle {
+namespace framework {
+namespace details {
+
+static bool IsSameOpDesc(OpDesc *op1, OpDesc *op2) {
+  return op1->Type() == op2->Type() && op1->Inputs() == op2->Inputs() &&
+         op1->Outputs() == op2->Outputs();
+}
+
+std::unique_ptr<ir::Graph> SequentialExecutionPass::ApplyImpl(
+    std::unique_ptr<ir::Graph> graph) const {
+  // FIXME(zjl): Insert dependencies between some distributed ops may cause
+  // the multi_devices_graph_pass fails. So we skip these ops here.
+  // Indeed, maybe we should not insert dependencies between these ops
+  // casually, which may cause deadlock easily.
+  // We should add more skipped distributed ops when found errors in
+  // multi_devices_graph_pass
+  static std::unordered_set<std::string> skip_dist_ops{
+      "send", "recv", "send_barrier", "fetch_barrier"};
+
+  auto &ops = Get<const std::vector<OpDesc *>>(kAllOpDescs);
+  std::vector<ir::Node *> op_node_list;
+  op_node_list.reserve(ops.size());
+
+  std::unordered_map<ir::Node *, size_t> op_deps;
+  std::unordered_map<ir::Node *, std::unordered_set<ir::Node *>> pending_ops;
+  std::unordered_set<ir::Node *> ready_ops;
+
+  for (ir::Node *node : graph->Nodes()) {
+    if (!node->IsOp()) continue;
+    std::unordered_set<ir::Node *> preceding_ops;
+    for (auto *in : node->inputs) {
+      PADDLE_ENFORCE(in->IsVar(),
+                     "Preceding Node of Op Nodes must be Var Node");
+      if (in->inputs.empty()) continue;
+      PADDLE_ENFORCE(in->inputs.size() == 1 && in->inputs[0]->IsOp(),
+                     "Preceding Op Node of Var Node must be unique");
+      preceding_ops.insert(in->inputs[0]);
+      pending_ops[in->inputs[0]].insert(node);
+    }
+    op_deps[node] = preceding_ops.size();
+    if (preceding_ops.empty()) {
+      ready_ops.insert(node);
+    }
+  }
+
+  for (auto *op_desc : ops) {
+    ir::Node *found_node = nullptr;
+    for (auto *node : ready_ops) {
+      if (IsSameOpDesc(op_desc, node->Op())) {
+        PADDLE_ENFORCE(found_node == nullptr,
+                       "Found multiple op_desc in graph: %s", op_desc->Type());
+        found_node = node;
+      }
+    }
+
+    PADDLE_ENFORCE_NOT_NULL(found_node, "Cannot find op_desc in graph: %s",
+                            op_desc->Type());
+    for (auto *pending_op : pending_ops[found_node]) {
+      if (--op_deps.at(pending_op) == 0) {
+        ready_ops.insert(pending_op);
+      }
+    }
+    ready_ops.erase(found_node);
+    if (skip_dist_ops.count(op_desc->Type()) == 0) {
+      op_node_list.push_back(found_node);
+    }
+  }
+
+  for (size_t i = 1; i < op_node_list.size(); ++i) {
+    auto *dep_var = graph->CreateControlDepVar();
+    op_node_list[i]->inputs.push_back(dep_var);
+    op_node_list[i - 1]->outputs.push_back(dep_var);
+    dep_var->outputs.push_back(op_node_list[i]);
+    dep_var->inputs.push_back(op_node_list[i - 1]);
+    VLOG(10) << "Add dependencies between " << op_node_list[i - 1]->Name()
+             << " and " << op_node_list[i]->Name();
+  }
+  return graph;
+}
+
+}  // namespace details
+}  // namespace framework
+}  // namespace paddle
+
+REGISTER_PASS(sequential_execution_pass,
+              paddle::framework::details::SequentialExecutionPass)
+    .RequirePassAttr(paddle::framework::details::kAllOpDescs);

paddle/fluid/framework/details/sequential_execution_pass.h

@@ -0,0 +1,34 @@
+// Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
+//
+// Licensed under the Apache License, Version 2.0 (the "License");
+// you may not use this file except in compliance with the License.
+// You may obtain a copy of the License at
+//
+//     http://www.apache.org/licenses/LICENSE-2.0
+//
+// Unless required by applicable law or agreed to in writing, software
+// distributed under the License is distributed on an "AS IS" BASIS,
+// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+// See the License for the specific language governing permissions and
+// limitations under the License.
+
+#pragma once
+
+#include "paddle/fluid/framework/ir/graph.h"
+#include "paddle/fluid/framework/ir/pass.h"
+
+namespace paddle {
+namespace framework {
+namespace details {
+
+constexpr char kAllOpDescs[] = "all_op_descs";
+
+class SequentialExecutionPass : public ir::Pass {
+ protected:
+  std::unique_ptr<ir::Graph> ApplyImpl(
+      std::unique_ptr<ir::Graph> graph) const override;
+};
+
+}  // namespace details
+}  // namespace framework
+}  // namespace paddle

paddle/fluid/framework/ir/CMakeLists.txt

@@ -41,6 +41,7 @@ pass_library(conv_bn_fuse_pass inference)
 pass_library(seqconv_eltadd_relu_fuse_pass inference)
 if(WITH_MKLDNN)
     pass_library(mkldnn_placement_pass base)
+    pass_library(depthwise_conv_mkldnn_pass base)
     pass_library(conv_bias_mkldnn_fuse_pass inference)
     pass_library(conv_relu_mkldnn_fuse_pass inference)
     pass_library(conv_elementwise_add_mkldnn_fuse_pass inference)
@@ -59,6 +60,7 @@ cc_test(graph_to_program_pass_test SRCS graph_to_program_pass_test.cc DEPS graph
 cc_test(test_graph_pattern_detector SRCS graph_pattern_detector_tester.cc DEPS graph_pattern_detector)
 cc_test(test_fc_fuse_pass SRCS fc_fuse_pass_tester.cc DEPS fc_fuse_pass framework_proto)
 if (WITH_MKLDNN)
+    cc_test(test_depthwise_conv_mkldnn_pass SRCS depthwise_conv_mkldnn_pass_tester.cc DEPS depthwise_conv_mkldnn_pass)
     cc_test(test_conv_relu_mkldnn_fuse_pass SRCS conv_relu_mkldnn_fuse_pass_tester.cc DEPS conv_relu_mkldnn_fuse_pass)
     cc_test(test_conv_elementwise_add_mkldnn_fuse_pass SRCS conv_elementwise_add_mkldnn_fuse_pass_tester.cc DEPS conv_elementwise_add_mkldnn_fuse_pass)
 endif ()

paddle/fluid/framework/ir/conv_relu_mkldnn_fuse_pass.h

@@ -31,7 +31,8 @@ class ConvReLUFusePass : public FusePassBase {
   virtual ~ConvReLUFusePass() {}
 
  protected:
-  std::unique_ptr<ir::Graph> ApplyImpl(std::unique_ptr<ir::Graph> graph) const;
+  std::unique_ptr<ir::Graph> ApplyImpl(
+      std::unique_ptr<ir::Graph> graph) const override;
 };
 
 }  // namespace ir

paddle/fluid/framework/ir/conv_relu_mkldnn_fuse_pass_tester.cc

@@ -15,6 +15,7 @@
 #include "paddle/fluid/framework/ir/conv_relu_mkldnn_fuse_pass.h"
 
 #include <gtest/gtest.h>
+#include "paddle/fluid/framework/op_proto_maker.h"
 
 namespace paddle {
 namespace framework {
@@ -36,6 +37,8 @@ void SetOp(ProgramDesc* prog, const std::string& type, const std::string& name,
     op->SetInput("X", inputs);
   }
   op->SetOutput("Out", outputs);
+  op->SetAttr(OpProtoAndCheckerMaker::OpRoleAttrName(),
+              static_cast<int>(OpRole::kForward));
 }
 
 // a->OP0->b

paddle/fluid/framework/ir/depthwise_conv_mkldnn_pass.cc

@@ -0,0 +1,58 @@
+/* Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License. */
+
+#include "paddle/fluid/framework/ir/depthwise_conv_mkldnn_pass.h"
+#include "paddle/fluid/framework/ir/graph_pattern_detector.h"
+
+namespace paddle {
+namespace framework {
+namespace ir {
+
+#define GET_NODE(id, pattern)                               \
+  PADDLE_ENFORCE(subgraph.count(pattern.RetrieveNode(#id)), \
+                 "pattern has no Node called %s", #id);     \
+  auto* id = subgraph.at(pattern.RetrieveNode(#id));        \
+  PADDLE_ENFORCE_NOT_NULL(id, "subgraph has no node %s", #id);
+
+std::unique_ptr<ir::Graph> DepthwiseConvMKLDNNPass::ApplyImpl(
+    std::unique_ptr<ir::Graph> graph) const {
+  PADDLE_ENFORCE(graph.get());
+  FusePassBase::Init("depthwise_conv_mkldnn_pass", graph.get());
+  GraphPatternDetector gpd;
+
+  auto* pattern = gpd.mutable_pattern();
+  pattern->NewNode("depthwise_conv")
+      ->assert_is_op("depthwise_conv2d")
+      ->assert_op_attr("use_mkldnn", true);
+
+  int found_depthwise_conv_mkldnn_count = 0;
+  auto handler = [&](const GraphPatternDetector::subgraph_t& subgraph,
+                     Graph* g) {
+    VLOG(3) << "handle DepthwiseConvMKLDNN fuse";
+    GET_NODE(depthwise_conv, (*pattern));
+    depthwise_conv->Op()->SetType("conv2d");
+    found_depthwise_conv_mkldnn_count++;
+  };
+
+  gpd(graph.get(), handler);
+  AddStatis(found_depthwise_conv_mkldnn_count);
+  return graph;
+}
+
+}  // namespace ir
+}  // namespace framework
+}  // namespace paddle
+
+REGISTER_PASS(depthwise_conv_mkldnn_pass,
+              paddle::framework::ir::DepthwiseConvMKLDNNPass);