code clean

paddle/fluid/framework/tensor_impl.h

@@ -59,6 +59,14 @@ inline T* Tensor::mutable_data(platform::Place place) {
 }
 
 inline Tensor ReshapeToMatrix(const Tensor& src, int num_col_dims) {
+  int rank = src.dims().size();
+  PADDLE_ENFORCE_GE(
+      rank, 2,
+      "'ReshapeToMatrix()' is only used for flatten high rank "
+      "tensors to matrixs. Can not be used in reshaping vectors.");
+  if (rank == 2) {
+    return src;
+  }
   Tensor res;
   res.ShareDataWith(src);
   res.Resize(flatten_to_2d(src.dims(), num_col_dims));

paddle/fluid/operators/cross_entropy_op.cc

@@ -45,11 +45,9 @@ class CrossEntropyOp : public framework::OperatorWithKernel {
                         "Input(Label) should be 1.");
     }
 
-    auto out_dim_vec =
-        framework::vectorize(framework::slice_ddim(x_dims, 0, rank - 1));
-    out_dim_vec.push_back(1);
-
-    ctx->SetOutputDim("Y", framework::make_ddim(out_dim_vec));
+    auto y_dims = x_dims;
+    y_dims[rank - 1] = 1;
+    ctx->SetOutputDim("Y", y_dims);
     ctx->ShareLoD("X", /*->*/ "Y");
   }
 

paddle/fluid/operators/cross_entropy_op.h

@@ -34,10 +34,9 @@ class CrossEntropyOpKernel : public framework::OpKernel<T> {
     y->mutable_data<T>(ctx.GetPlace());
 
     int rank = x->dims().size();
-    Tensor x_2d = rank > 2 ? framework::ReshapeToMatrix(*x, rank - 1) : *x;
-    Tensor labels_2d =
-        rank > 2 ? framework::ReshapeToMatrix(*labels, rank - 1) : *labels;
-    Tensor y_2d = rank > 2 ? framework::ReshapeToMatrix(*y, rank - 1) : *y;
+    Tensor x_2d = framework::ReshapeToMatrix(*x, rank - 1);
+    Tensor labels_2d = framework::ReshapeToMatrix(*labels, rank - 1);
+    Tensor y_2d = framework::ReshapeToMatrix(*y, rank - 1);
 
     math::CrossEntropyFunctor<DeviceContext, T>()(
         ctx.template device_context<DeviceContext>(), &y_2d, &x_2d, &labels_2d,

paddle/fluid/operators/softmax_op.h

@@ -32,9 +32,8 @@ class SoftmaxKernel : public framework::OpKernel<T> {
     Out->mutable_data<T>(context.GetPlace());
 
     int rank = X->dims().size();
-    Tensor X_2d = rank > 2 ? framework::ReshapeToMatrix(*X, rank - 1) : *X;
-    Tensor Out_2d =
-        rank > 2 ? framework::ReshapeToMatrix(*Out, rank - 1) : *Out;
+    Tensor X_2d = framework::ReshapeToMatrix(*X, rank - 1);
+    Tensor Out_2d = framework::ReshapeToMatrix(*Out, rank - 1);
 
     math::SoftmaxFunctor<DeviceContext, T>()(
         context.template device_context<DeviceContext>(), &X_2d, &Out_2d);
@@ -53,11 +52,9 @@ class SoftmaxGradKernel : public framework::OpKernel<T> {
     dX->mutable_data<T>(context.GetPlace());
 
     int rank = Out->dims().size();
-    Tensor Out_2d =
-        rank > 2 ? framework::ReshapeToMatrix(*Out, rank - 1) : *Out;
-    Tensor dOut_2d =
-        rank > 2 ? framework::ReshapeToMatrix(*dOut, rank - 1) : *dOut;
-    Tensor dX_2d = rank > 2 ? framework::ReshapeToMatrix(*dX, rank - 1) : *dX;
+    Tensor Out_2d = framework::ReshapeToMatrix(*Out, rank - 1);
+    Tensor dOut_2d = framework::ReshapeToMatrix(*dOut, rank - 1);
+    Tensor dX_2d = framework::ReshapeToMatrix(*dX, rank - 1);
 
     math::SoftmaxGradFunctor<DeviceContext, T>()(
         context.template device_context<DeviceContext>(), &Out_2d, &dOut_2d,