refine reshape operator

paddle/operators/reshape_op.cc

@@ -29,14 +29,17 @@ class ReshapeOp : public framework::OperatorWithKernel {
   void InferShape(const framework::InferShapeContext &ctx) const override {
     auto *in = ctx.Input<framework::Tensor>("X");
     auto shape = ctx.Attr<std::vector<int>>("shape");
-    PADDLE_ENFORCE_EQ((unsigned)shape.size(), in->dims().size(),
-                      "The dimension of Input(X) mismatches with Attr(shape).");
-    size_t shape_size = 1;
+    int64_t capacity = -1;
     for (auto dim : shape) {
-      shape_size *= dim;
+      PADDLE_ENFORCE(dim > 0, "Each dimension of shape must be positive.");
+      if (capacity < 0) {
+        capacity = dim;
+      } else {
+        capacity *= dim;
+      }
     }
-    size_t in_size = framework::product(in->dims());
-    PADDLE_ENFORCE_EQ(shape_size, in_size,
+    int64_t in_size = framework::product(in->dims());
+    PADDLE_ENFORCE_EQ(capacity, in_size,
                       "The size of Input(X) mismatches with Attr(shape).");
     ctx.Output<framework::Tensor>("Out")->Resize(in->dims());
   }

paddle/operators/reshape_op.h

@@ -21,14 +21,12 @@
 namespace paddle {
 namespace operators {
 
-using Tensor = framework::Tensor;
-
 template <typename Place, typename T>
 class ReshapeKernel : public framework::OpKernel {
  public:
   void Compute(const framework::ExecutionContext& ctx) const {
-    auto* out = ctx.Output<Tensor>("Out");
-    auto* in = ctx.Input<Tensor>("X");
+    auto* out = ctx.Output<framework::Tensor>("Out");
+    auto* in = ctx.Input<framework::Tensor>("X");
     out->mutable_data<T>(ctx.GetPlace());
 
     auto shape = ctx.Attr<std::vector<int>>("shape");
@@ -46,8 +44,8 @@ template <typename Place, typename T>
 class ReshapeGradKernel : public framework::OpKernel {
  public:
   void Compute(const framework::ExecutionContext& ctx) const {
-    auto* d_out = ctx.Input<Tensor>(framework::GradVarName("Out"));
-    auto* d_x = ctx.Output<Tensor>(framework::GradVarName("X"));
+    auto* d_out = ctx.Input<framework::Tensor>(framework::GradVarName("Out"));
+    auto* d_x = ctx.Output<framework::Tensor>(framework::GradVarName("X"));
     d_x->mutable_data<T>(ctx.GetPlace());
 
     auto in_dims = d_x->dims();

python/paddle/v2/framework/tests/test_reshape_op.py

@@ -10,15 +10,27 @@ class TestReshapeOp(unittest.TestCase):
     def setUp(self):
         self.type = "reshape"
         self.inputs = {'X': np.random.random((37, 51)).astype("float32"), }
-        self.attrs = {'shape': [51, 37]}
+        self.attrs = {'shape': [51 * 37]}
         self.outputs = {'Out': self.inputs['X'].reshape(self.attrs['shape'])}
 
 
-class ReshapeGradOpTest(GradientChecker):
+class TestReshapeGradOp(GradientChecker):
+    """
     def test_normal(self):
         op = Operator("reshape", X='X', Out='Out', shape=[5, 40])
         inputs = {"X": np.random.random((10, 20)).astype("float32")}
         self.check_grad(op, inputs, set("X"), "Out")
+    """
+
+    def setUp(self):
+        self.op = Operator("reshape", X='X', Out='Out', shape=[5, 40])
+        self.inputs = {"X": np.random.random((10, 20)).astype("float32")}
+
+    def test_normal(self):
+        self.check_grad(self.op, self.inputs, ["X"], "Out")
+
+    def test_dev_compare(self):
+        self.compare_grad(self.op, self.inputs)
 
 
 if __name__ == '__main__':