Add global function `FalttenToMatrix` and add `axis` for MulOp

paddle/operators/mul_op.cc

@@ -27,24 +27,25 @@ class MulOp : public framework::OperatorWithKernel {
   void InferShape(const framework::InferShapeContext &ctx) const override {
     auto x_dim = ctx.Input<Tensor>("X")->dims();
     auto y_dim = ctx.Input<Tensor>("Y")->dims();
-    int x_num_row_dims = GetAttr<int>("X_num_raw_dims");
-    int y_num_row_dims = GetAttr<int>("Y_num_raw_dims");
+    int x_num_row_dims = GetAttr<int>("x_num_row_dims");
+    int y_num_row_dims = GetAttr<int>("y_num_row_dims");
 
     PADDLE_ENFORCE(x_dim.size() > x_num_row_dims,
                    "The rank of input tensor X(%s) should be larger than "
-                   "`mul_op`'s `X_num_raw_dims`.",
+                   "`mul_op`'s `x_num_row_dims`.",
                    ctx.op().Input("X"));
     PADDLE_ENFORCE(y_dim.size() > y_num_row_dims,
                    "The rank of input tensor Y(%s) should be larger than "
-                   "`mul_op`'s `Y_num_raw_dims`.",
+                   "`mul_op`'s `y_num_row_dims`.",
                    ctx.op().Input("Y"));
     PADDLE_ENFORCE_EQ(
         product(x_dim, x_dim.size() - x_num_row_dims, x_dim.size()),
         product(y_dim, 0, y_dim.size() - y_num_row_dims),
         "First matrix's width must be equal with second matrix's height.");
     ctx.Output<Tensor>("Out")->Resize(
-        {product(x_dim, 0, x_dim.size() - x_num_row_dims),
-         product(y_dim, y_dim.size() - y_num_row_dims, y_dim.size())});
+        {static_cast<int>(product(x_dim, 0, x_dim.size() - x_num_row_dims)),
+         static_cast<int>(
+             product(y_dim, y_dim.size() - y_num_row_dims, y_dim.size()))});
   }
 };
 
@@ -96,10 +97,12 @@ class MulOpGrad : public framework::OperatorWithKernel {
     auto *x_grad = ctx.Output<Tensor>(framework::GradVarName("X"));
     auto *y_grad = ctx.Output<Tensor>(framework::GradVarName("Y"));
     PADDLE_ENFORCE(
-        product(x_dim, 0, x_dims.size() - x_num_row_dims) == out_dims[0],
+        product(x_dims, 0, x_dims.size() - GetAttr<int>("x_num_row_dims")) ==
+            out_dims[0],
         "The first dimension of Out@GRAD must equal to the first dimension of "
         "the first operand.");
-    PADDLE_ENFORCE(product(y_dim, y_dims.size() - y_num_row_dims,
+    PADDLE_ENFORCE(
+        product(y_dims, y_dims.size() - GetAttr<int>("y_num_row_dims"),
                 y_dims.size()) == out_dims[1],
         "The second dimension of Out@GRAD must equal to the second "
         "dimension of the second operand.");

paddle/operators/mul_op.h

@@ -31,13 +31,25 @@ template <typename Place, typename T>
 class MulKernel : public framework::OpKernel {
  public:
   void Compute(const framework::ExecutionContext& context) const override {
-    auto* X = context.Input<Tensor>("X");
-    auto* Y = context.Input<Tensor>("Y");
-    auto* Z = context.Output<Tensor>("Out");
+    const Tensor* X = context.Input<Tensor>("X");
+    const Tensor* Y = context.Input<Tensor>("Y");
+    Tensor* Z = context.Output<Tensor>("Out");
+    const Tensor X_matrix =
+        X->dims().size() > 2
+            ? framework::FlattenToMatrix<T>(
+                  *X, context.template GetAttr<int>("x_num_row_dims"))
+            : *X;
+    const Tensor Y_matrix =
+        Y->dims().size() > 2
+            ? framework::FlattenToMatrix<T>(
+                  *Y, context.template GetAttr<int>("y_num_row_dims"))
+            : *Y;
+
     Z->mutable_data<T>(context.GetPlace());
     auto* device_context =
         const_cast<platform::DeviceContext*>(context.device_context_);
-    math::matmul<Place, T>(*X, false, *Y, false, 1, Z, 0, device_context);
+    math::matmul<Place, T>(X_matrix, false, Y_matrix, false, 1, Z, 0,
+                           device_context);
   }
 };
 
@@ -45,20 +57,36 @@ template <typename Place, typename T>
 class MulGradKernel : public framework::OpKernel {
  public:
   void Compute(const framework::ExecutionContext& ctx) const override {
-    auto* X = ctx.Input<Tensor>("X");
-    auto* Y = ctx.Input<Tensor>("Y");
-    auto* dOut = ctx.Input<Tensor>(framework::GradVarName("Out"));
+    int x_num_row_dims = ctx.template GetAttr<int>("x_num_row_dims");
+    int y_num_row_dims = ctx.template GetAttr<int>("y_num_row_dims");
+    const Tensor* X = ctx.Input<Tensor>("X");
+    const Tensor* Y = ctx.Input<Tensor>("Y");
+    const Tensor X_matrix =
+        X->dims().size() > 2 ? framework::FlattenToMatrix<T>(*X, x_num_row_dims)
+                             : *X;
+    const Tensor Y_matrix =
+        Y->dims().size() > 2 ? framework::FlattenToMatrix<T>(*Y, y_num_row_dims)
+                             : *Y;
+    const Tensor* dOut = ctx.Input<Tensor>(framework::GradVarName("Out"));
 
-    auto* dX = ctx.Output<Tensor>(framework::GradVarName("X"));
-    auto* dY = ctx.Output<Tensor>(framework::GradVarName("Y"));
+    Tensor* dX = ctx.Output<Tensor>(framework::GradVarName("X"));
+    Tensor* dY = ctx.Output<Tensor>(framework::GradVarName("Y"));
     dX->mutable_data<T>(ctx.GetPlace());
     dY->mutable_data<T>(ctx.GetPlace());
+    Tensor dX_matrix = dX->dims().size() > 2
+                           ? framework::FlattenToMatrix<T>(*dX, x_num_row_dims)
+                           : *dX;
+    Tensor dY_matrix = dY->dims().size() > 2
+                           ? framework::FlattenToMatrix<T>(*dY, y_num_row_dims)
+                           : *dY;
     auto* device_context =
         const_cast<platform::DeviceContext*>(ctx.device_context_);
     // dX = dOut * Y'. dX: M x K, dOut : M x N, Y : K x N
-    math::matmul<Place, T>(*dOut, false, *Y, true, 1, dX, 0, device_context);
+    math::matmul<Place, T>(*dOut, false, Y_matrix, true, 1, &dX_matrix, 0,
+                           device_context);
     // dY = X' * dOut. dY: K x N, dOut : M x N, X : M x K
-    math::matmul<Place, T>(*X, true, *dOut, false, 1, dY, 0, device_context);
+    math::matmul<Place, T>(X_matrix, true, *dOut, false, 1, &dY_matrix, 0,
+                           device_context);
   }
 };