[cherry-pick 1.6] fix error message for elementwise_add and elementwise_mul (#20353)

* fix error message for elementwise_add/mul;test=develop

* edit error message;test=develop

paddle/fluid/operators/elementwise/elementwise_op.h

@@ -52,14 +52,25 @@ class ElementwiseOp : public framework::OperatorWithKernel {
         framework::proto::VarType::LOD_TENSOR) {
       auto x_dim = ctx->GetInputDim("X");
       auto y_dim = ctx->GetInputDim("Y");
-      PADDLE_ENFORCE_GE(x_dim.size(), y_dim.size(),
-                        "Rank of first input must >= rank of second input.");
+      PADDLE_ENFORCE_GE(
+          x_dim.size(), y_dim.size(),
+          "ShapeError: the dimension of input X must greater than or equal to "
+          "the one of input Y. But received: the shape of input X = [%s], the "
+          "dimension of input X = %d, the shape of input Y = [%s], the "
+          "dimension of input Y = %d",
+          x_dim, x_dim.size(), y_dim, y_dim.size());
     } else if (ctx->GetInputsVarType("X").front() ==
                framework::proto::VarType::SELECTED_ROWS) {
-      PADDLE_ENFORCE((ctx->GetInputDim("Y").size() == 1u) &&
-                         (ctx->GetInputDim("Y")[0] == 1),
-                     "For elementwise_op, if X is Sparse, "
-                     "Y must be scalar.");
+      PADDLE_ENFORCE_EQ(
+          ctx->GetInputDim("Y").size(), 1u,
+          "ShapeError: For elementwise_op, if X is Sparse(VarType.SELECTED_ROWS"
+          "), Y must be scalar. But reveived the dimension of Y = %s",
+          ctx->GetInputDim("Y").size());
+      PADDLE_ENFORCE_EQ(
+          ctx->GetInputDim("Y")[0], 1,
+          "ShapeError: For elementwise_op, if X is Sparse(VarType.SELECTED_ROWS"
+          "), Y must be scalar. But reveived the first dimension of Y = %s",
+          ctx->GetInputDim("Y")[0]);
     } else {
       PADDLE_THROW("X's type[%s] is not supported by elementwise_op.",
                    ctx->GetInputsVarType("X").front());
@@ -203,8 +214,13 @@ class ElementwiseOpGrad : public framework::OperatorWithKernel {
     auto x_dims = ctx->GetInputDim(out_grad_name);
     auto y_dims = ctx->GetInputDim("Y");
 
-    PADDLE_ENFORCE_GE(x_dims.size(), y_dims.size(),
-                      "Rank of first input must >= rank of second input.");
+    PADDLE_ENFORCE_GE(
+        x_dims.size(), y_dims.size(),
+        "ShapeError: the dimension of Out@GRAD must greater than or equal to "
+        "the one of input Y. But received: the shape of Out@GRAD = [%s], the "
+        "dimension of Out@GRAD = %d, the shape of input Y = [%s], the "
+        "dimension of of input Y = %d",
+        x_dims, x_dims.size(), y_dims, y_dims.size());
 
     auto x_grad_name = framework::GradVarName("X");
     auto y_grad_name = framework::GradVarName("Y");

paddle/fluid/operators/elementwise/elementwise_op_function.h

@@ -71,7 +71,12 @@ inline void get_mid_dims(const framework::DDim &x_dims,
         // only support single y_dims[i] = 1 now.
         PADDLE_ENFORCE_EQ(*mid_flag, 0,
                           "Broadcast support y_dims with single 1.");
-        PADDLE_ENFORCE_EQ(y_dims[i], 1, "Broadcast dimension mismatch.");
+        PADDLE_ENFORCE_EQ(y_dims[i], 1,
+                          "ShapeError: broadcast dimension mismatch. Operands "
+                          "could not be broadcast together with the shape of "
+                          "X = [%s] and the shape of Y = [%s]. Received [%d] "
+                          "in X is not equal to [%d] in Y",
+                          x_dims, y_dims, x_dims[i + axis], y_dims[i]);
         // m*n*k m*1*k
         for (int j = 0; j < i; ++j) {
           (*pre) *= y_dims[j];
@@ -823,8 +828,13 @@ void ElementwiseComputeEx(const framework::ExecutionContext &ctx,
       x, y, z, ctx.template device_context<DeviceContext>(), func);
   auto x_dims = x->dims();
   auto y_dims_untrimed = y->dims();
-  PADDLE_ENFORCE_GE(x_dims.size(), y_dims_untrimed.size(),
-                    "Rank of first input must >= rank of second input.");
+  PADDLE_ENFORCE_GE(
+      x_dims.size(), y_dims_untrimed.size(),
+      "ShapeError: the dimension of input X must greater than or equal to "
+      "the one of input Y. But received: the shape of input X = [%s], the "
+      "dimension of input X = %d, the shape of input Y = [%s], the dimension "
+      "of of input Y = %d",
+      x_dims, x_dims.size(), y_dims_untrimed, y_dims_untrimed.size());
   if (x_dims == y_dims_untrimed) {
     functor.Run();
     return;

python/paddle/fluid/layers/nn.py

@@ -13456,6 +13456,35 @@ def _elementwise_op(helper):
 
     assert x is not None, 'x cannot be None in {}'.format(op_type)
     assert y is not None, 'y cannot be None in {}'.format(op_type)
+    if not isinstance(x, Variable):
+        raise TypeError(
+            "The type of 'x' in %s must be Variable, but received %s" %
+            (op_type, type(x)))
+    if not isinstance(y, Variable):
+        raise TypeError(
+            "The type of 'y' in %s must be Variable, but received %s" %
+            (op_type, type(y)))
+    if convert_dtype(x.dtype) in ['float16']:
+        warnings.warn(
+            "The data type of 'x' in %s only support float16 on GPU now." %
+            (op_type))
+    if convert_dtype(y.dtype) in ['float16']:
+        warnings.warn(
+            "The data type of 'y' in %s only support float16 on GPU now." %
+            (op_type))
+    if convert_dtype(x.dtype) not in [
+            'float16', 'float32', 'float64', 'int32', 'int64'
+    ]:
+        raise TypeError(
+            "The data type of 'x' in %s must be float16 or float32 or float64 or int32 or int64, "
+            "but received %s." % (op_type, convert_dtype(x.dtype)))
+    if convert_dtype(y.dtype) not in [
+            'float16', 'float32', 'float64', 'int32', 'int64'
+    ]:
+        raise TypeError(
+            "The data type of 'y' in %s must be float16 or float32 or float64 or int32 or int64, "
+            "but received %s." % (op_type, convert_dtype(y.dtype)))
+
     axis = helper.kwargs.get('axis', -1)
     use_mkldnn = helper.kwargs.get('use_mkldnn', False)
     name = helper.kwargs.get('name', None)

python/paddle/fluid/tests/unittests/test_elementwise_add_op.py

@@ -17,6 +17,8 @@ import unittest
 import numpy as np
 import paddle.fluid.core as core
 from op_test import OpTest
+import paddle.fluid as fluid
+from paddle.fluid import compiler, Program, program_guard
 
 
 class TestElementwiseAddOp(OpTest):
@@ -306,5 +308,22 @@ class TestFP16ElementwiseAddOp_channelwise_add(TestFP16ElementwiseAddOp):
         self.axis = -1
 
 
+class TestElementwiseAddOpError(OpTest):
+    def test_errors(self):
+        with program_guard(Program(), Program()):
+            # the input of elementwise_add must be Variable.
+            x1 = fluid.create_lod_tensor(
+                np.array([-1, 3, 5, 5]), [[1, 1, 1, 1]], fluid.CPUPlace())
+            y1 = fluid.create_lod_tensor(
+                np.array([-1, 3, 5, 5]), [[1, 1, 1, 1]], fluid.CPUPlace())
+            self.assertRaises(TypeError, fluid.layers.elementwise_add, x1, y1)
+
+            # the input dtype of elementwise_add must be float16 or float32 or float64 or int32 or int64
+            # float16 only can be set on GPU place
+            x2 = fluid.layers.data(name='x2', shape=[3, 4, 5, 6], dtype="uint8")
+            y2 = fluid.layers.data(name='y2', shape=[3, 4, 5, 6], dtype="uint8")
+            self.assertRaises(TypeError, fluid.layers.elementwise_add, x2, y2)
+
+
 if __name__ == '__main__':
     unittest.main()

python/paddle/fluid/tests/unittests/test_elementwise_mul_op.py

@@ -18,6 +18,8 @@ import numpy as np
 from op_test import OpTest
 import paddle.fluid.core as core
 from paddle.fluid.op import Operator
+import paddle.fluid as fluid
+from paddle.fluid import compiler, Program, program_guard
 
 
 class ElementwiseMulOp(OpTest):
@@ -160,5 +162,22 @@ class TestElementwiseMulOpFp16(ElementwiseMulOp):
         self.dtype = np.float16
 
 
+class TestElementwiseMulOpError(OpTest):
+    def test_errors(self):
+        with program_guard(Program(), Program()):
+            # the input of elementwise_mul must be Variable.
+            x1 = fluid.create_lod_tensor(
+                np.array([-1, 3, 5, 5]), [[1, 1, 1, 1]], fluid.CPUPlace())
+            y1 = fluid.create_lod_tensor(
+                np.array([-1, 3, 5, 5]), [[1, 1, 1, 1]], fluid.CPUPlace())
+            self.assertRaises(TypeError, fluid.layers.elementwise_mul, x1, y1)
+
+            # the input dtype of elementwise_mul must be float16 or float32 or float64 or int32 or int64
+            # float16 only can be set on GPU place
+            x2 = fluid.layers.data(name='x2', shape=[3, 4, 5, 6], dtype="uint8")
+            y2 = fluid.layers.data(name='y2', shape=[3, 4, 5, 6], dtype="uint8")
+            self.assertRaises(TypeError, fluid.layers.elementwise_mul, x2, y2)
+
+
 if __name__ == '__main__':
     unittest.main()