Merge branch 'develop' of https://github.com/PaddlePaddle/Paddle into add_floordiv_and_mod

paddle/fluid/API.spec

@@ -205,7 +205,7 @@ paddle.fluid.layers.maxout (ArgSpec(args=['x', 'groups', 'name'], varargs=None,
 paddle.fluid.layers.space_to_depth (ArgSpec(args=['x', 'blocksize', 'name'], varargs=None, keywords=None, defaults=(None,)), ('document', '5f207ae10589ebe38a63575ef6ff8e1e'))
 paddle.fluid.layers.affine_grid (ArgSpec(args=['theta', 'out_shape', 'name'], varargs=None, keywords=None, defaults=(None,)), ('document', '51def402b8910e163cbace9d0c0526ed'))
 paddle.fluid.layers.sequence_reverse (ArgSpec(args=['x', 'name'], varargs=None, keywords=None, defaults=(None,)), ('document', '77a6d80aa5551ca70324fc975c44507f'))
-paddle.fluid.layers.affine_channel (ArgSpec(args=['x', 'scale', 'bias', 'data_layout', 'name'], varargs=None, keywords=None, defaults=(None, None, 'NCHW', None)), ('document', '2f46f1ff39a13ab00857e7b9f44b2fa7'))
+paddle.fluid.layers.affine_channel (ArgSpec(args=['x', 'scale', 'bias', 'data_layout', 'name', 'act'], varargs=None, keywords=None, defaults=(None, None, 'NCHW', None, None)), ('document', 'ab84fdc6dc60f3ad9aa397e6007e3bf9'))
 paddle.fluid.layers.similarity_focus (ArgSpec(args=['input', 'axis', 'indexes', 'name'], varargs=None, keywords=None, defaults=(None,)), ('document', '70e3b5182a18b40b47ecabd7c8490a35'))
 paddle.fluid.layers.hash (ArgSpec(args=['input', 'hash_size', 'num_hash', 'name'], varargs=None, keywords=None, defaults=(1, None)), ('document', '9bb77f8dc002dd2ce75d4769eaaf5007'))
 paddle.fluid.layers.grid_sampler (ArgSpec(args=['x', 'grid', 'name'], varargs=None, keywords=None, defaults=(None,)), ('document', 'd256cba1c41a5ed92ce3f31e24a2ca6d'))

paddle/fluid/inference/utils/CMakeLists.txt

 cc_library(benchmark SRCS benchmark.cc DEPS enforce)
 cc_test(test_benchmark SRCS benchmark_tester.cc DEPS benchmark)
-cc_binary(visualizer SRCS visualizer.cc DEPS analysis
-    paddle_pass_builder ir_pass_manager pass graph_viz_pass analysis_passes)

paddle/fluid/inference/utils/visualizer.cc

-// 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/inference/utils/visualizer.h"
-#include <gflags/gflags.h>
-#include <glog/logging.h>
-#include <fstream>
-#include <memory>
-#include "paddle/fluid/framework/ir/graph_viz_pass.h"
-#include "paddle/fluid/inference/analysis/analyzer.h"
-#include "paddle/fluid/inference/analysis/passes/ir_analysis_pass.h"
-#include "paddle/fluid/platform/init.h"
-
-DEFINE_string(model_dir, "", "model directory");
-DEFINE_string(model_program_path, "", "model program path");
-DEFINE_string(model_params_path, "", "model params path");
-
-using paddle::inference::analysis::Argument;
-
-namespace paddle {
-namespace inference {
-namespace utils {
-
-void Visualizer::SetArgument(Argument *argument) { argument_ = argument; }
-
-bool Visualizer::Run() {
-  paddle::framework::InitDevices(false);
-  paddle::inference::analysis::Analyzer().Run(argument_);
-  return true;
-}
-
-}  // namespace utils
-}  // namespace inference
-}  // namespace paddle
-
-// Generate a dot file describing the structure of graph.
-// To use this tool, run command: ./visualizer [options...]
-// Options:
-//     --model_dir: the directory of model
-//     --model_program_path: the path of program
-//     --model_params_path: the path of params
-int main(int argc, char *argv[]) {
-  gflags::ParseCommandLineFlags(&argc, &argv, true);
-  google::InitGoogleLogging(argv[0]);
-
-  paddle::inference::analysis::Argument argument;
-  argument.SetUseGPU(false);
-  argument.SetUseTensorRT(false);
-
-  if (FLAGS_model_dir.empty()) {
-    if (FLAGS_model_program_path.empty() || FLAGS_model_params_path.empty()) {
-      LOG(ERROR) << "Please set model_dir"
-                    " or model_program_path and model_params_path";
-      return -1;
-    } else {
-      argument.SetModelProgramPath(FLAGS_model_program_path);
-      argument.SetModelParamsPath(FLAGS_model_params_path);
-    }
-  } else {
-    argument.SetModelDir(FLAGS_model_dir);
-  }
-
-  // Only 1 pass, default filename is 0_ir_origin.dot
-  // For more details, looking for paddle::inference::analysis::IRPassManager
-  argument.SetIrAnalysisPasses({"infer_clean_graph_pass", "graph_viz_pass"});
-
-  std::unique_ptr<paddle::framework::Scope> scope{
-      new paddle::framework::Scope()};
-  argument.SetScopeNotOwned(
-      const_cast<paddle::framework::Scope *>(scope.get()));
-
-  paddle::inference::utils::Visualizer visualizer;
-  visualizer.SetArgument(&argument);
-  visualizer.Run();
-
-  return 0;
-}
-
-USE_PASS(infer_clean_graph_pass);
-USE_PASS(graph_viz_pass);
-USE_PASS(graph_to_program_pass);

paddle/fluid/inference/utils/visualizer.h

-// 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 <string>
-#include "paddle/fluid/inference/analysis/argument.h"
-
-namespace paddle {
-namespace inference {
-namespace utils {
-
-using paddle::inference::analysis::Argument;
-
-class Visualizer final {
- public:
-  Visualizer() = default;
-  ~Visualizer() = default;
-  Visualizer(const Visualizer &) = delete;
-  Visualizer &operator=(const Visualizer &) = delete;
-
-  void SetArgument(Argument *);
-  bool Run();
-
- private:
-  Argument *argument_;
-};
-
-}  // namespace utils
-}  // namespace inference
-}  // namespace paddle

paddle/fluid/operators/affine_channel_op.cc

@@ -113,6 +113,27 @@ class AffineChannelOpGrad : public framework::OperatorWithKernel {
   }
 };
 
+class AffineChannelGradMaker : public framework::SingleGradOpDescMaker {
+ public:
+  using framework::SingleGradOpDescMaker::SingleGradOpDescMaker;
+
+  std::unique_ptr<framework::OpDesc> Apply() const override {
+    auto* op = new framework::OpDesc();
+    op->SetType("affine_channel_grad");
+    op->SetInput("X", Input("X"));
+    op->SetInput(framework::GradVarName("Out"), OutputGrad("Out"));
+    op->SetInput("Scale", Input("Scale"));
+
+    op->SetAttrMap(Attrs());
+
+    op->SetOutput(framework::GradVarName("X"), InputGrad("X"));
+    op->SetOutput(framework::GradVarName("Scale"), InputGrad("Scale"));
+    op->SetOutput(framework::GradVarName("Bias"), InputGrad("Bias"));
+
+    return std::unique_ptr<framework::OpDesc>(op);
+  }
+};
+
 template <typename T>
 using EigenArrayMap =
     Eigen::Map<Eigen::Array<T, Eigen::Dynamic, Eigen::Dynamic>>;
@@ -260,8 +281,7 @@ namespace ops = paddle::operators;
 using CPU = paddle::platform::CPUDeviceContext;
 
 REGISTER_OPERATOR(affine_channel, ops::AffineChannelOp,
-                  ops::AffineChannelOpMaker,
-                  paddle::framework::DefaultGradOpDescMaker<true>);
+                  ops::AffineChannelOpMaker, ops::AffineChannelGradMaker);
 REGISTER_OPERATOR(affine_channel_grad, ops::AffineChannelOpGrad);
 
 REGISTER_OP_CPU_KERNEL(affine_channel, ops::AffineChannelKernel<CPU, float>,

paddle/fluid/operators/batch_norm_op.cu

@@ -75,15 +75,11 @@ class BatchNormKernel<platform::CUDADeviceContext, T>
                  << "CUDNN_BN_MIN_EPSILON instead.";
     }
     epsilon = std::max(epsilon, CUDNN_BN_MIN_EPSILON);
-
-    // TODO(dengkaipeng): use PERSISTENT mode in training may incur errors
-    // in inference period, cuDNN fixed issues on PERSISTENT mode in version
-    // 7.0.2, 7.0.4 and 7.3.0, we disable this mode currently.
-    // #if CUDNN_VERSION_MIN(7, 0, 0)
-    //     mode_ = CUDNN_BATCHNORM_SPATIAL_PERSISTENT;
-    // #else
+#if CUDNN_VERSION_MIN(7, 0, 0)
+    mode_ = CUDNN_BATCHNORM_SPATIAL_PERSISTENT;
+#else
     mode_ = CUDNN_BATCHNORM_SPATIAL;
-    // #endif
+#endif
 
     VLOG(3) << "Setting descriptors.";
     std::vector<int> dims;
@@ -305,15 +301,11 @@ class BatchNormGradKernel<platform::CUDADeviceContext, T>
                    << "CUDNN_BN_MIN_EPSILON instead.";
       }
       epsilon = std::max(epsilon, CUDNN_BN_MIN_EPSILON);
-
-      // TODO(dengkaipeng): use PERSISTENT mode in training may incur errors
-      // in inference period, cuDNN fixed issues on PERSISTENT mode in version
-      // 7.0.2, 7.0.4 and 7.3.0, we disable this mode currently.
-      // #if CUDNN_VERSION_MIN(7, 0, 0)
-      //       mode_ = CUDNN_BATCHNORM_SPATIAL_PERSISTENT;
-      // #else
+#if CUDNN_VERSION_MIN(7, 0, 0)
+      mode_ = CUDNN_BATCHNORM_SPATIAL_PERSISTENT;
+#else
       mode_ = CUDNN_BATCHNORM_SPATIAL;
-      // #endif
+#endif
 
       CUDNN_ENFORCE(platform::dynload::cudnnSetTensorNdDescriptor(
           data_desc_, CudnnDataType<T>::type,

paddle/fluid/operators/lod_reset_op.cc

@@ -32,7 +32,10 @@ class LoDResetOp : public framework::OperatorWithKernel {
       PADDLE_ENFORCE_GT(level0.size(), 1,
                         "If Input(Y) not provided, the target lod should be "
                         "specified by attribute `target_lod`.");
+    } else {
+      ctx->ShareLoD("Y", "Out");
     }
+
     ctx->SetOutputDim("Out", ctx->GetInputDim("X"));
   }
 

paddle/fluid/operators/math/sequence_padding.cu

@@ -78,12 +78,6 @@ class PaddingLoDTensorFunctor<platform::CUDADeviceContext, T> {
                    "The numel of 'pad_value' can only be 1 or be equal to the "
                    "'step_width'.");
 
-    if (!norm_by_times && seq_num == 1UL && pad_seq_len == max_seq_len) {
-      TensorCopy(seq_tensor, context.GetPlace(), context, pad_tensor);
-      pad_tensor->Resize(pad_tensor_dims);
-      return;
-    }
-
     const int kBlockSize = 512;
 
     /* At least use 32 threads to copy sequence_width elements,
@@ -129,12 +123,13 @@ class UnpaddingLoDTensorFunctor<platform::CUDADeviceContext, T> {
 
     CheckDims(seq_tensor_dims, pad_tensor_dims, seq_offsets, pad_seq_len,
               step_width, layout);
-
+    /*
     if (!norm_by_times && seq_num == 1UL && pad_seq_len == max_seq_len) {
       TensorCopy(pad_tensor, context.GetPlace(), context, seq_tensor);
       seq_tensor->Resize(seq_tensor_dims);
       return;
     }
+    */
 
     const int kBlockSize = 512;
 

paddle/fluid/operators/matmul_op.cc

@@ -290,8 +290,10 @@ class MatMulOp : public framework::OperatorWithKernel {
                                      context->Attrs().Get<bool>("transpose_Y"));
 
     PADDLE_ENFORCE_EQ(mat_dim_x.width_, mat_dim_y.height_);
+    if (context->IsRuntime()) {
       PADDLE_ENFORCE(mat_dim_x.batch_size_ == mat_dim_y.batch_size_ ||
                      mat_dim_x.batch_size_ == 0 || mat_dim_y.batch_size_ == 0);
+    }
     std::vector<int64_t> dim_out;
     if (mat_dim_x.batch_size_ != 0) {
       dim_out = framework::vectorize(dim_x);

paddle/scripts/paddle_build.sh

@@ -453,6 +453,7 @@ function assert_api_spec_approvals() {
       echo "checking ${API_FILE} change, PR: ${GIT_PR_ID}, changes: ${API_CHANGE}"
       if [ ${API_CHANGE} ] && [ "${GIT_PR_ID}" != "" ]; then
           # NOTE: per_page=10000 should be ok for all cases, a PR review > 10000 is not human readable.
+          # approval_user_list: velconia 1979255,panyx0718 2887803,XiaoguangHu01 46782768,chengduoZH 30176695,Xreki 12538138,luotao1 6836917,sneaxiy 32832641,tensor-tang 21351065,jacquesqiao 3048612,typhoonzero 13348433,shanyi15 35982308. 
           if [ "$API_FILE" == "paddle/fluid/API.spec" ];then
             APPROVALS=`curl -H "Authorization: token ${GITHUB_API_TOKEN}" https://api.github.com/repos/PaddlePaddle/Paddle/pulls/${GIT_PR_ID}/reviews?per_page=10000 | \
             python ${PADDLE_ROOT}/tools/check_pr_approval.py 2 2887803 35982308 46782768 30176695`
@@ -462,14 +463,14 @@ function assert_api_spec_approvals() {
             fi
           else
             APPROVALS=`curl -H "Authorization: token ${GITHUB_API_TOKEN}" https://api.github.com/repos/PaddlePaddle/Paddle/pulls/${GIT_PR_ID}/reviews?per_page=10000 | \
-            python ${PADDLE_ROOT}/tools/check_pr_approval.py 1 2887803`
+            python ${PADDLE_ROOT}/tools/check_pr_approval.py 1 2887803 1979255 21351065 3048612 13348433 46782768 30176695 12538138 6836917 32832641`
           fi
           echo "current pr ${GIT_PR_ID} got approvals: ${APPROVALS}"
           if [ "${APPROVALS}" == "FALSE" ]; then
             if [ "$API_FILE" == "paddle/fluid/API.spec" ];then
               echo "You must have one RD (panyx0718 or chengduoZH or XiaoguangHu01) and one PM (shanyi15) approval for the api change! ${API_FILE}"
             else
-              echo "You must have panyx0718 approval for the api change! ${API_FILE}"
+              echo "You must have one RD (velconia,panyx0718,XiaoguangHu01,chengduoZH,Xreki,luotao1,sneaxiy,tensor-tang,jacquesqiao,typhoonzero) approval for the api change! ${API_FILE}"
             fi
             exit 1
           fi
@@ -479,10 +480,10 @@ function assert_api_spec_approvals() {
     HAS_CONST_CAST=`git diff -U0 upstream/$BRANCH |grep -o -m 1 "const_cast" || true`
     if [ ${HAS_CONST_CAST} ] && [ "${GIT_PR_ID}" != "" ]; then
         APPROVALS=`curl -H "Authorization: token ${GITHUB_API_TOKEN}" https://api.github.com/repos/PaddlePaddle/Paddle/pulls/${GIT_PR_ID}/reviews?per_page=10000 | \
-        python ${PADDLE_ROOT}/tools/check_pr_approval.py 1 2887803`
+        python ${PADDLE_ROOT}/tools/check_pr_approval.py 1 2887803 1979255 21351065 3048612 13348433 46782768 30176695 12538138 6836917 32832641`
         echo "current pr ${GIT_PR_ID} got approvals: ${APPROVALS}"
         if [ "${APPROVALS}" == "FALSE" ]; then
-            echo "You must have panyx0718 approval for the const_cast"
+            echo "You must have one RD (velconia,panyx0718,XiaoguangHu01,chengduoZH,Xreki,luotao1,sneaxiy,tensor-tang,jacquesqiao,typhoonzero) approval for the api change! ${API_FILE}"
             exit 1
         fi
     fi

python/paddle/fluid/layers/nn.py

@@ -4901,6 +4901,9 @@ def matmul(x, y, transpose_x=False, transpose_y=False, alpha=1.0, name=None):
 
         if len(y_shape) > 2 and len(x_shape) > 2:
             for i, dim_x in enumerate(x_shape[:-2]):
+                # don't check neg shape
+                if dim_x < 0 or y_shape[i] < 0:
+                    continue
                 if dim_x != y_shape[i]:
                     raise ValueError("Invalid inputs for matmul. x(%s), y(%s)" %
                                      (x.shape, y.shape))
@@ -9721,7 +9724,12 @@ def sequence_reverse(x, name=None):
     return out
 
 
-def affine_channel(x, scale=None, bias=None, data_layout='NCHW', name=None):
+def affine_channel(x,
+                   scale=None,
+                   bias=None,
+                   data_layout='NCHW',
+                   name=None,
+                   act=None):
     """
     Applies a separate affine transformation to each channel of the input.
     Useful for replacing spatial batch norm with its equivalent fixed
@@ -9740,6 +9748,7 @@ def affine_channel(x, scale=None, bias=None, data_layout='NCHW', name=None):
         data_layout (string, default NCHW): NCHW or NHWC. If input is 2D
             tensor, you can ignore data_layout.
         name (str, default None): The name of this layer.
+        act (str, default None): Activation to be applied to the output of this layer.
 
     Returns:
         out (Variable): A tensor of the same shape and data layout with x.
@@ -9759,7 +9768,7 @@ def affine_channel(x, scale=None, bias=None, data_layout='NCHW', name=None):
                 'Bias': bias},
         attrs={"data_layout": data_layout},
         outputs={"Out": out})
-    return out
+    return helper.append_activation(pre_activation)
 
 
 def similarity_focus(input, axis, indexes, name=None):