From f31217fc2e535d0d1079a02895214c2c2f434809 Mon Sep 17 00:00:00 2001
From: wanghaoshuang <wanghaoshuang@baidu.com>
Date: Mon, 11 Sep 2017 14:50:54 +0800
Subject: [PATCH] Fix issues

---
 paddle/operators/pad_op.cc |  5 +++--
 paddle/operators/pad_op.h  | 21 +++++++++++----------
 2 files changed, 14 insertions(+), 12 deletions(-)

diff --git a/paddle/operators/pad_op.cc b/paddle/operators/pad_op.cc
index 894fe2cecf..ef678cf3d3 100644
--- a/paddle/operators/pad_op.cc
+++ b/paddle/operators/pad_op.cc
@@ -27,10 +27,10 @@ class PadOp : public framework::OperatorWithKernel {
   void InferShape(const framework::InferShapeContext &ctx) const override {
     auto x_dim = ctx.Input<Tensor>("X")->dims();
     auto paddings = Attr<std::vector<int>>("paddings");
-    PADDLE_ENFORCE_EQ(x_dim.size() * 2, int(paddings.size()),
+    PADDLE_ENFORCE_EQ(x_dim.size() * 2, int64_t(paddings.size()),
                       "Size of paddings should be equal to 2 * dimension size "
                       "of input tensor.");
-    std::vector<int> out_dims(x_dim.size());
+    std::vector<int64_t> out_dims(x_dim.size());
     for (int i = 0; i < x_dim.size(); ++i) {
       out_dims[i] = x_dim[i] + paddings[i * 2] + paddings[i * 2 + 1];
     }
@@ -95,6 +95,7 @@ class PadOpGrad : public framework::OperatorWithKernel {
                             "Input(Out@GRAD) should not be null");
     auto x_dims = ctx.Input<Tensor>("X")->dims();
     auto *x_grad = ctx.Output<Tensor>(framework::GradVarName("X"));
+    PADDLE_ENFORCE_NOT_NULL(x_grad, "Output(X@GRAD) should not be null");
 
     x_grad->Resize(x_dims);
   }
diff --git a/paddle/operators/pad_op.h b/paddle/operators/pad_op.h
index dcf957b47e..53451f925a 100644
--- a/paddle/operators/pad_op.h
+++ b/paddle/operators/pad_op.h
@@ -28,18 +28,17 @@ using EigenTensor = framework::EigenTensor<T, D, MajorType, IndexType>;
 
 template <typename Place, typename T, size_t D>
 void PadFunction(const framework::ExecutionContext& context) {
-  auto pads = context.GetAttr<std::vector<int>>("paddings");
+  auto pads = context.Attr<std::vector<int>>("paddings");
   Eigen::array<std::pair<int, int>, D> paddings;
   for (int i = 0; i < paddings.size(); ++i) {
     paddings[i].first = pads[i * 2];
     paddings[i].second = pads[i * 2 + 1];
   }
-  T pad_value = context.GetAttr<T>("pad_value");
+  T pad_value = context.Attr<T>("pad_value");
 
   auto* x = context.Input<Tensor>("X");
   auto* out = context.Output<Tensor>("Out");
   out->mutable_data<T>(context.GetPlace());
-  auto dims = x->dims();
 
   auto x_tensor = EigenTensor<T, D>::From(*x);
   auto out_tensor = EigenTensor<T, D>::From(*out);
@@ -51,8 +50,8 @@ template <typename Place, typename T>
 class PadKernel : public framework::OpKernel {
  public:
   void Compute(const framework::ExecutionContext& context) const override {
-    int dim = context.Input<Tensor>("X")->dims().size();
-    switch (dim) {
+    int rank = context.Input<Tensor>("X")->dims().size();
+    switch (rank) {
       case 1:
         PadFunction<Place, T, 1>(context);
         break;
@@ -72,14 +71,15 @@ class PadKernel : public framework::OpKernel {
         PadFunction<Place, T, 6>(context);
         break;
       default:
-        PADDLE_THROW("Only ranks up to 6 supported.");
+        PADDLE_THROW(
+            "PadOp only support tensors with no more than 6 dimensions.");
     }
   }
 };
 
 template <typename Place, typename T, size_t D>
 void PadGradFunction(const framework::ExecutionContext& context) {
-  auto pads = context.GetAttr<std::vector<int>>("paddings");
+  auto pads = context.Attr<std::vector<int>>("paddings");
   Eigen::array<std::pair<int, int>, D> paddings;
   for (int i = 0; i < paddings.size(); ++i) {
     paddings[i].first = -pads[i * 2];
@@ -99,9 +99,9 @@ template <typename Place, typename T>
 class PadGradKernel : public framework::OpKernel {
  public:
   void Compute(const framework::ExecutionContext& context) const override {
-    size_t dim =
+    size_t rank =
         context.Input<Tensor>(framework::GradVarName("Out"))->dims().size();
-    switch (dim) {
+    switch (rank) {
       case 1:
         PadGradFunction<Place, T, 1>(context);
         break;
@@ -121,7 +121,8 @@ class PadGradKernel : public framework::OpKernel {
         PadGradFunction<Place, T, 6>(context);
         break;
       default:
-        PADDLE_THROW("Only ranks up to 6 supported.");
+        PADDLE_THROW(
+            "PadOp only support tensors with no more than 6 dimensions.");
     }
   }
 };
-- 
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