API/OP(sequence_expand_as) error message enhancement (#23712)

* API/OP(sequence_expand_as) error message enhancement.
test=develop
Co-authored-by: NFrostML <380185688@qq.com>

paddle/fluid/operators/sequence_ops/sequence_expand_as_op.cc

@@ -27,18 +27,18 @@ class SequenceExpandAsOp : public framework::OperatorWithKernel {
 
  protected:
   void InferShape(framework::InferShapeContext* ctx) const override {
-    PADDLE_ENFORCE(ctx->HasInput("X"),
-                   "Input(X) of SequenceExpandAsOp should not be null.");
-    PADDLE_ENFORCE(ctx->HasInput("Y"),
-                   "Input(Y) of SequenceExpandAsOp should not be null.");
-    PADDLE_ENFORCE(ctx->HasOutput("Out"),
-                   "Output(Out) of SequenceExpandAsOp should not be null.");
+    OP_INOUT_CHECK(ctx->HasInputs("X"), "Input", "X", "SequenceExpandAs");
+    OP_INOUT_CHECK(ctx->HasInputs("Y"), "Input", "Y", "SequenceExpandAs");
+    OP_INOUT_CHECK(ctx->HasOutput("Out"), "Output", "Out", "SequenceExpandAs");
 
     auto x_dims = ctx->GetInputDim("X");
     auto out_dims = x_dims;
 
     PADDLE_ENFORCE_GE(x_dims.size(), 2,
-                      "Dimension number of Input(X) should be at least 2.");
+                      platform::errors::InvalidArgument(
+                          "Dimension number of Input(X) should be at least 2. "
+                          "But received X's dimensions = %d, X's shape = [%s].",
+                          x_dims.size(), x_dims));
 
     if (ctx->IsRuntime()) {
       framework::Variable* x_var =
@@ -50,11 +50,17 @@ class SequenceExpandAsOp : public framework::OperatorWithKernel {
       auto& y_lod = y_var->Get<LoDTensor>().lod();
 
       PADDLE_ENFORCE_EQ(y_lod.size(), 1,
-                        "Level number of Input(Y)'s lod should be 1.");
+                        platform::errors::InvalidArgument(
+                            "Level number of Input(Y)'s lod should be 1. But "
+                            "received Y's lod level = %d.",
+                            y_lod.size()));
 
       PADDLE_ENFORCE_EQ(static_cast<size_t>(x_dim[0]), y_lod[0].size() - 1,
-                        "The first dimension of Input(X) should be equal "
-                        "to the size of Input(Y)'s 0 level lod.");
+                        platform::errors::InvalidArgument(
+                            "The first dimension of Input(X) should be one "
+                            "less than the size of Input(Y)'s 0 level lod. But "
+                            "received X's shape[0] = %d, Y's lod[0].size = %d.",
+                            x_dim[0], y_lod[0].size()));
 
       int64_t out_first_dim = 0;
       if (y_lod[0].size() <= 1) {
@@ -138,9 +144,9 @@ class SequenceExpandAsOpGrad : public framework::OperatorWithKernel {
 
  protected:
   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->HasInputs("X"), "Input", "X", "SequenceExpandAsGrad");
+    OP_INOUT_CHECK(ctx->HasInputs(framework::GradVarName("Out")), "Input",
+                   "Out@GRAD", "SequenceExpandAsGrad");
 
     auto x_dims = ctx->GetInputDim("X");
     auto x_grad_name = framework::GradVarName("X");

paddle/fluid/operators/sequence_ops/sequence_expand_as_op.h

@@ -74,13 +74,25 @@ class SequenceExpandAsKernel : public framework::OpKernel<T> {
     auto *y = context.Input<framework::LoDTensor>("Y");
     auto *out = context.Output<framework::LoDTensor>("Out");
 
-    PADDLE_ENFORCE_EQ(y->lod().empty(), false,
-                      "Input(Y) Tensor of SequenceExpandAsOp does not contain "
-                      "LoD information.");
+    PADDLE_ENFORCE_EQ(
+        y->lod().empty(), false,
+        platform::errors::InvalidArgument(
+            "Input(Y) of SequenceExpandAsOp has wrong LoD information. "
+            "Expected Y's lod is not empty, but received empty lod."));
 
     auto &y_lod = y->lod();
-    PADDLE_ENFORCE_EQ(y_lod.size(), 1, "LoD of Y should be 1.");
-    PADDLE_ENFORCE_GT(y_lod[0].size(), 1, ".");
+    PADDLE_ENFORCE_EQ(y_lod.size(), 1,
+                      platform::errors::InvalidArgument(
+                          "Input(Y) of SequenceExpandAsOp has wrong LoD "
+                          "information. Expected Y's lod level = 1, but "
+                          "received  lod level = %d.",
+                          y_lod.size()));
+    PADDLE_ENFORCE_GT(y_lod[0].size(), 1,
+                      platform::errors::InvalidArgument(
+                          "Input(Y) of SequenceExpandAsOp has wrong LoD "
+                          "information. Expected the size of Y's lod[0] > 1, "
+                          "but received lod[0].size = %d.",
+                          y_lod[0].size()));
 
     out->mutable_data<T>(context.GetPlace());
 

python/paddle/fluid/layers/sequence_lod.py

@@ -815,7 +815,7 @@ def sequence_expand_as(x, y, name=None):
 
     Args:
         x (Variable): The input variable which is a Tensor or LoDTensor, with the \
-            dims ``[M, K]``. The data type should be float32, float64, int8, int32 \
+            dims ``[M, K]``. The data type should be float32, float64, int32 \
             or int64.
         y (Variable): The input variable which is a LoDTensor with 1-level lod.
         name (str, optional): For detailed information, please refer \
@@ -872,6 +872,9 @@ def sequence_expand_as(x, y, name=None):
     """
     assert not in_dygraph_mode(), (
         "sequence layer is not supported in dygraph mode yet.")
+    check_variable_and_dtype(x, 'x', ['float32', 'float64', 'int32', 'int64'],
+                             'sequence_expand_as')
+    check_type(y, 'y', Variable, 'sequence_expand_as')
     helper = LayerHelper('sequence_expand_as', input=x, **locals())
     dtype = helper.input_dtype()
     tmp = helper.create_variable_for_type_inference(dtype)

python/paddle/fluid/tests/unittests/sequence/test_sequence_expand_as.py

@@ -18,7 +18,9 @@ import unittest
 import numpy as np
 import sys
 sys.path.append("../")
+import paddle.fluid as fluid
 from op_test import OpTest
+from paddle.fluid import Program, program_guard
 
 
 class TestSequenceExpandAs(OpTest):
@@ -84,5 +86,22 @@ class TestSequenceExpandAsCase3(TestSequenceExpandAs):
         self.inputs = {'X': (x_data, x_lod), 'Y': (y_data, y_lod)}
 
 
+class TestSequenceExpandAsOpError(unittest.TestCase):
+    def test_errors(self):
+        with program_guard(Program(), Program()):
+            # the input x must be Variable
+            x1 = np.random.random((2, 4)).astype("float32")
+            self.assertRaises(TypeError, fluid.layers.sequence_expand_as, x1)
+
+            # the dtype of input x must be float32, float64, int32 or int64
+            x2 = fluid.data(name='x2', shape=[None, 4], dtype="bool")
+            self.assertRaises(TypeError, fluid.layers.sequence_expand_as, x2)
+
+            # the input y must be Variable
+            x3 = fluid.data(name='x3', shape=[None, 4], dtype="float32")
+            y = np.random.random((2, 4)).astype("float32")
+            self.assertRaises(TypeError, fluid.layers.sequence_expand_as, x3, y)
+
+
 if __name__ == '__main__':
     unittest.main()