OP(pad, pad2d, pad_constant_like) error message enhancement (#23882) (#23994)

* enhance pad.* error message, test=develop

paddle/fluid/operators/pad2d_op.cc

@@ -466,34 +466,43 @@ class Pad2dOp : public framework::OperatorWithKernel {
   using framework::OperatorWithKernel::OperatorWithKernel;
 
   void InferShape(framework::InferShapeContext* ctx) const override {
-    PADDLE_ENFORCE(ctx->HasInput("X"),
-                   "Input(X) of Pad2dOp should not be null.");
-    PADDLE_ENFORCE(ctx->HasOutput("Out"),
-                   "Output(Out) of Pad2dOp should not be null.");
+    OP_INOUT_CHECK(ctx->HasInput("X"), "Input", "X", "Pad2d");
+    OP_INOUT_CHECK(ctx->HasOutput("Out"), "Output", "Out", "Pad2d");
 
     auto x_dim = ctx->GetInputDim("X");
     PADDLE_ENFORCE_EQ(x_dim.size(), 4,
-                      "The size of input(X)'s dimension should be equal to 4.");
+                      platform::errors::InvalidArgument(
+                          "The size of Input(X)'s dimension should be equal to "
+                          "4, but received %d. ",
+                          x_dim.size()));
 
     std::vector<int64_t> out_dims(x_dim.size());
     auto data_format = ctx->Attrs().Get<std::string>("data_format");
     out_dims[0] = x_dim[0];
     if (ctx->HasInput("Paddings")) {
       auto paddings_dim = ctx->GetInputDim("Paddings");
-      PADDLE_ENFORCE_EQ(
-          paddings_dim.size(), 1,
-          "Size of Input(Paddings)'s dimension should be equal to 1.");
+      PADDLE_ENFORCE_EQ(paddings_dim.size(), 1,
+                        platform::errors::InvalidArgument(
+                            "Size of Input(Paddings)'s dimension should be "
+                            "equal to 1, but received %d.",
+                            paddings_dim.size()));
       if (ctx->IsRuntime()) {
         PADDLE_ENFORCE_EQ(paddings_dim[0], 4,
-                          "Shape of Input(Paddings) should be equal to [4].");
+                          platform::errors::InvalidArgument(
+                              "Shape of Input(Paddings) should be equal to "
+                              "[4], but received [%d].",
+                              paddings_dim[0]));
       }
       out_dims[1] = x_dim[1];
       out_dims[2] = x_dim[2];
       out_dims[3] = x_dim[3];
     } else {
       auto paddings = ctx->Attrs().Get<std::vector<int>>("paddings");
-      PADDLE_ENFORCE_EQ(paddings.size(), 4,
-                        "Size of paddings should be equal to 4.");
+      PADDLE_ENFORCE_EQ(
+          paddings.size(), 4,
+          platform::errors::InvalidArgument(
+              "Size of paddings should be equal to 4, but received %d.",
+              static_cast<int>(paddings.size())));
       if (data_format == "NCHW") {
         out_dims[1] = x_dim[1];  // channel
         out_dims[2] = ((!ctx->IsRuntime()) && (x_dim[2] < 0))
@@ -608,9 +617,10 @@ class Pad2dOpGrad : public framework::OperatorWithKernel {
   using framework::OperatorWithKernel::OperatorWithKernel;
 
   void InferShape(framework::InferShapeContext* ctx) const override {
-    PADDLE_ENFORCE(ctx->HasInput("X"), "Input(X) should not be null");
-    PADDLE_ENFORCE(ctx->HasInput(framework::GradVarName("Out")),
-                   "Input(Out@GRAD) should not be null");
+    OP_INOUT_CHECK(ctx->HasInput("X"), "Input", "X", "Pad2d@Grad");
+    OP_INOUT_CHECK(ctx->HasInput(framework::GradVarName("Out")), "Input",
+                   framework::GradVarName("Out"), "Pad2d@Grad");
+
     auto x_dims = ctx->GetInputDim("X");
     auto x_grad_name = framework::GradVarName("X");
     if (ctx->HasOutput(x_grad_name)) {

paddle/fluid/operators/pad_constant_like_op.cc

@@ -25,18 +25,19 @@ class PadConstantLikeOp : public framework::OperatorWithKernel {
   using framework::OperatorWithKernel::OperatorWithKernel;
 
   void InferShape(framework::InferShapeContext *ctx) const override {
-    PADDLE_ENFORCE(ctx->HasInput("X"),
-                   "Input(X) of PadConstantLikeOp should not be null.");
-    PADDLE_ENFORCE(ctx->HasInput("Y"),
-                   "Input(Y) of PadConstantLikeOp should not be null.");
-    PADDLE_ENFORCE(ctx->HasOutput("Out"),
-                   "Output(Out) of PadConstantLikeOp should not be null.");
+    OP_INOUT_CHECK(ctx->HasInput("X"), "Input", "X", "PadConstantLike");
+    OP_INOUT_CHECK(ctx->HasInput("Y"), "Input", "Y", "PadConstantLike");
+    OP_INOUT_CHECK(ctx->HasOutput("Out"), "Output", "Out", "PadConstantLike");
 
     auto x_dim = ctx->GetInputDim("X");
     auto y_dim = ctx->GetInputDim("Y");
 
     PADDLE_ENFORCE_EQ(x_dim.size(), y_dim.size(),
-                      "The dimension of X and Y should be the same.");
+                      platform::errors::InvalidArgument(
+                          "The size of Input(X)'s dimension and the size of "
+                          "Input(Y)'s dimension should be the same, but "
+                          "received %d for Input(X) vs %d for Input(Y).",
+                          x_dim.size(), y_dim.size()));
 
     for (int i = 0; i < x_dim.size(); ++i) {
       if ((!ctx->IsRuntime()) && ((x_dim[i] == -1) || (y_dim[i] == -1))) {
@@ -44,8 +45,11 @@ class PadConstantLikeOp : public framework::OperatorWithKernel {
       } else {
         PADDLE_ENFORCE_GE(
             x_dim[i], y_dim[i],
-            "expected X_dim[i] >= Y_dim[i], but received %d < %d for dim %d",
-            x_dim[i], y_dim[i], i);
+            platform::errors::InvalidArgument(
+                "The size of each dimension of Input(X) expected to be greater "
+                "than or equal to size of corresponding dimension of Input(Y) "
+                "(X_dim[i] >= Y_dim[i]), but received %d < %d for dimension %d",
+                x_dim[i], y_dim[i], i));
       }
     }
 
@@ -157,14 +161,20 @@ class PadConstantLikeOpGrad : public framework::OperatorWithKernel {
   using framework::OperatorWithKernel::OperatorWithKernel;
 
   void InferShape(framework::InferShapeContext *ctx) const override {
-    PADDLE_ENFORCE(ctx->HasInput("Y"), "Input(Y) should not be null");
-    PADDLE_ENFORCE(ctx->HasInput(framework::GradVarName("Out")),
-                   "Input(Out@GRAD) should not be null");
+    OP_INOUT_CHECK(ctx->HasInput("Y"), "Input", "Y", "PadConstantLike@Grad");
+    OP_INOUT_CHECK(ctx->HasInput(framework::GradVarName("Out")), "Input",
+                   framework::GradVarName("Out"), "PadConstantLike@Grad");
+
     auto y_dim = ctx->GetInputDim("Y");
     auto dout_dim = ctx->GetInputDim(framework::GradVarName("Out"));
 
-    PADDLE_ENFORCE_EQ(dout_dim.size(), y_dim.size(),
-                      "The dimension of X and Y should be the same.");
+    PADDLE_ENFORCE_EQ(
+        dout_dim.size(), y_dim.size(),
+        platform::errors::InvalidArgument(
+            "Op(PadConstantLike@Grad) the size of Input(Out@Grad)'s dimension "
+            "and the size of Input(Y)'s dimension should be the same, but "
+            "received %d for Input(Out@Grad) vs %d for Input(Y).",
+            dout_dim.size(), y_dim.size()));
 
     auto y_grad_name = framework::GradVarName("Y");
     if (ctx->HasOutput(y_grad_name)) {
@@ -175,10 +185,14 @@ class PadConstantLikeOpGrad : public framework::OperatorWithKernel {
         if ((!ctx->IsRuntime()) && ((dout_dim[i] == -1) || (y_dim[i] == -1))) {
           continue;
         } else {
-          PADDLE_ENFORCE_GE(dout_dim[i], y_dim[i],
-                            "expected Out_dim[i] >= Y_dim[i], but received %d "
-                            "< %d for dim %d",
-                            dout_dim[i], y_dim[i], i);
+          PADDLE_ENFORCE_GE(
+              dout_dim[i], y_dim[i],
+              platform::errors::InvalidArgument(
+                  "The size of each dimension of Input(Out@Grad) expected to "
+                  "be greater than or equal to size of corresponding dimension "
+                  "of Input(Y) (Out_dim[i] >= Y_dim[i]), but received %d < %d "
+                  "for dimension %d",
+                  dout_dim[i], y_dim[i], i));
         }
       }
     }

paddle/fluid/operators/pad_op.cc

@@ -25,17 +25,24 @@ class PadOp : public framework::OperatorWithKernel {
   using framework::OperatorWithKernel::OperatorWithKernel;
 
   void InferShape(framework::InferShapeContext* ctx) const override {
-    PADDLE_ENFORCE(ctx->HasInput("X"), "Input(X) of PadOp should not be null.");
-    PADDLE_ENFORCE(ctx->HasOutput("Out"),
-                   "Output(Out) of PadOp should not be null.");
+    OP_INOUT_CHECK(ctx->HasInput("X"), "Input", "X", "Pad");
+    OP_INOUT_CHECK(ctx->HasOutput("Out"), "Output", "Out", "Pad");
 
     auto x_dim = ctx->GetInputDim("X");
     auto& paddings = ctx->Attrs().Get<std::vector<int>>("paddings");
-    PADDLE_ENFORCE_EQ(x_dim.size() * 2, int64_t(paddings.size()),
-                      "Size of paddings should be equal to 2 * dimension size "
-                      "of input tensor.");
+    PADDLE_ENFORCE_EQ(
+        static_cast<int>(paddings.size()), x_dim.size() * 2,
+        platform::errors::InvalidArgument(
+            "Size of 'paddings' dimension should be equal to 2 * size of "
+            "Input(X)'s dimension, but received (size of 'paddings' dimension "
+            "is) %d vs (2 * size of Input(X)'s dimension is) %d.",
+            static_cast<int>(paddings.size()), x_dim.size() * 2));
     for (size_t i = 0; i < paddings.size(); ++i) {
-      PADDLE_ENFORCE_GE(paddings[i], 0, "paddings should >= 0.");
+      PADDLE_ENFORCE_GE(paddings[i], 0,
+                        platform::errors::InvalidArgument(
+                            "The element of 'paddings' should >= 0, but "
+                            "received %d for index %d.",
+                            paddings[i], static_cast<int>(i)));
     }
     std::vector<int64_t> out_dims(x_dim.size());
     for (int i = 0; i < x_dim.size(); ++i) {

python/paddle/fluid/layers/nn.py

@@ -6432,6 +6432,9 @@ def pad(x, paddings, pad_value=0., name=None):
             x = fluid.data(name='data', shape=[300, 300], dtype='float32')
             out = fluid.layers.pad(x=x, paddings=[0, 1, 1, 2], pad_value=0.)
     """
+    check_variable_and_dtype(
+        x, 'x', ['float16', 'float32', 'float64', 'int32', 'int64'], "pad")
+
     helper = LayerHelper('pad', input=x, **locals())
     dtype = helper.input_dtype()
     out = helper.create_variable_for_type_inference(dtype)
@@ -6523,6 +6526,10 @@ def pad_constant_like(x, y, pad_value=0., name=None):
             out = fluid.layers.pad_constant_like(x=x, y=y, pad_value=0.)
             # out is a rank 4 tensor variable, and out.shape = [2, 3 ,2 , 3]
     """
+    check_type(x, 'x', (Variable), 'pad_constant_like')
+    check_variable_and_dtype(y, 'y', ['float32', 'float64', 'int32', 'int64'],
+                             "pad_constant_like")
+
     helper = LayerHelper('pad_constant_like', input=x, **locals())
     dtype = helper.input_dtype()
     out = helper.create_variable_for_type_inference(dtype)
@@ -8802,6 +8809,9 @@ def pad2d(input,
             data = fluid.data(name='data', shape=[None, 3, 32, 32], dtype='float32')
             result = fluid.layers.pad2d(input=data, paddings=[0, 1, 2, 3], mode='reflect')
     """
+    check_variable_and_dtype(
+        input, 'input', ['float16', 'float32', 'float64', 'int32', 'int64'],
+        "pad2d")
 
     if in_dygraph_mode():
         _paddings = paddings.numpy().tolist() if isinstance(

python/paddle/fluid/tests/unittests/test_pad2d_op.py

@@ -15,6 +15,8 @@
 import unittest
 import numpy as np
 from op_test import OpTest
+import paddle.fluid as fluid
+from paddle.fluid import Program, program_guard
 
 
 class TestPad2dOp(OpTest):
@@ -124,5 +126,20 @@ class TestCase7(TestPad2dOp):
         self.variable_paddings = True
 
 
+class TestPad2dOpError(unittest.TestCase):
+    def test_errors(self):
+        with program_guard(Program(), Program()):
+            input_data = np.random.random((2, 2, 2, 2)).astype("float32")
+
+            def test_Variable():
+                fluid.layers.pad2d(input=input_data, paddings=[1, 1, 1, 1])
+
+            self.assertRaises(TypeError, test_Variable)
+
+            data = fluid.data(
+                name='data', shape=[None, 3, 20, 20], dtype='float16')
+            fluid.layers.pad2d(input=data, paddings=[1, 1, 1, 1])
+
+
 if __name__ == '__main__':
     unittest.main()

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

@@ -17,9 +17,11 @@ from __future__ import print_function
 import unittest
 import numpy as np
 from op_test import OpTest
+import paddle.fluid as fluid
+from paddle.fluid import Program, program_guard
 
 
-class TestPadOp(OpTest):
+class TestPadConstantLikeOp(OpTest):
     def setUp(self):
         self.initTestCase()
         self.op_type = "pad_constant_like"
@@ -49,7 +51,7 @@ class TestPadOp(OpTest):
         self.paddings = [(0, 13), (0, 0)]
 
 
-class TestCase1(TestPadOp):
+class TestCase1(TestPadConstantLikeOp):
     def initTestCase(self):
         self.x_shape = (4, 3, 4, 5)
         self.y_shape = (2, 3, 4, 5)
@@ -57,7 +59,7 @@ class TestCase1(TestPadOp):
         self.pad_value = 0.5
 
 
-class TestCase2(TestPadOp):
+class TestCase2(TestPadConstantLikeOp):
     def initTestCase(self):
         self.x_shape = (4, 3, 4, 10)
         self.y_shape = (2, 3, 2, 10)
@@ -65,5 +67,26 @@ class TestCase2(TestPadOp):
         self.pad_value = 0.5
 
 
+class TestPadConstantLikeOpError(unittest.TestCase):
+    def test_errors(self):
+        with program_guard(Program(), Program()):
+            x_data = np.random.random((2, 2, 2, 2)).astype("float32")
+            y_data = np.random.random((2, 2, 2, 2)).astype("float32")
+
+            def test_Variable_x():
+                var_y = fluid.data(
+                    name="data_y", shape=[2, 2, 2, 2], dtype="float32")
+                fluid.layers.pad_constant_like(x=x_data, y=var_y)
+
+            self.assertRaises(TypeError, test_Variable_x)
+
+            def test_Variable_y():
+                var_x = fluid.data(
+                    name="data_x", shape=[2, 2, 2, 2], dtype="float32")
+                fluid.layers.pad_constant_like(x=var_x, y=y_data)
+
+            self.assertRaises(TypeError, test_Variable_y)
+
+
 if __name__ == '__main__':
     unittest.main()

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

@@ -18,6 +18,8 @@ import unittest
 import numpy as np
 from op_test import OpTest
 import paddle.fluid.core as core
+import paddle.fluid as fluid
+from paddle.fluid import Program, program_guard
 
 
 class TestPadOp(OpTest):
@@ -95,5 +97,20 @@ create_test_fp16(TestCase1)
 create_test_fp16(TestCase2)
 create_test_fp16(TestCase3)
 
+
+class TestPadOpError(unittest.TestCase):
+    def test_errors(self):
+        with program_guard(Program(), Program()):
+            input_data = np.random.random((2, 2)).astype("float32")
+
+            def test_Variable():
+                fluid.layers.pad(x=input_data, paddings=[1, 1, 1, 1])
+
+            self.assertRaises(TypeError, test_Variable)
+
+            data = fluid.data(name='data', shape=[4], dtype='float16')
+            fluid.layers.pad(x=data, paddings=[0, 1])
+
+
 if __name__ == '__main__':
     unittest.main()