lod_rank_table error message enhance (#23613) (#24047)

* lod_rank_table error message enhance. test=develop

python/paddle/fluid/layers/control_flow.py

@@ -1109,6 +1109,12 @@ def lod_rank_table(x, level=0):
                                   dtype='float32', lod_level=1)
             out = layers.lod_rank_table(x=x, level=0)
     """
+    check_type(x, 'x', (Variable, list), 'lod_rank_table')
+    if isinstance(x, (list)):
+        for i, input_x in enumerate(x):
+            check_type(input_x, 'input[' + str(i) + ']', Variable,
+                       'lod_rank_table')
+
     helper = LayerHelper("lod_rank_table", **locals())
     table = helper.create_variable(
         type=core.VarDesc.VarType.LOD_RANK_TABLE,

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

@@ -17,7 +17,7 @@ from __future__ import print_function
 from paddle.fluid.layers import data
 from paddle.fluid.layers.control_flow import lod_rank_table
 from paddle.fluid.executor import Executor
-import paddle.fluid.core as core
+from paddle.fluid import Program, program_guard, core
 import numpy
 import unittest
 
@@ -41,5 +41,25 @@ class TestLoDRankTable(unittest.TestCase):
         self.assertEqual([(0, 5), (1, 1), (2, 1)], list(table.items()))
 
 
+class TestLoDRankTableError(unittest.TestCase):
+    def test_errors(self):
+        with program_guard(Program(), Program()):
+            x = numpy.random.random((2, 4)).astype("float32")
+
+            def test_Variable():
+                rank_table = lod_rank_table(x=x, level=1)
+
+            self.assertRaises(TypeError, test_Variable)
+
+            def test_list_Variable():
+                rank_table = lod_rank_table(x=[x], level=1)
+
+            self.assertRaises(TypeError, test_list_Variable)
+
+            x = data(name='x', shape=[10], dtype='float32', lod_level=1)
+            out = lod_rank_table(x=x, level=0)
+            out = lod_rank_table(x=[x], level=0)
+
+
 if __name__ == '__main__':
     unittest.main()

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

@@ -219,5 +219,70 @@ class TestCPULoDTensorArrayOpGrad(unittest.TestCase):
         self.assertAlmostEqual(1.0, g_out_sum, delta=0.1)
 
 
+class TestLoDTensorArrayError(unittest.TestCase):
+    def test_errors(self):
+        with program_guard(Program(), Program()):
+            x = numpy.random.random((10)).astype("float32")
+            x2 = layers.data(name='x', shape=[10])
+            table = lod_rank_table(x2, level=0)
+
+            def test_x_Variable():
+                rank_table = lod_tensor_to_array(x=x, table=table)
+
+            self.assertRaises(TypeError, test_x_Variable)
+
+            table2 = numpy.random.random((2)).astype("int64")
+
+            def test_table_Variable():
+                rank_table = lod_tensor_to_array(x=x2, table=table2)
+
+            self.assertRaises(TypeError, test_table_Variable)
+
+            def test_x_list_Variable():
+                rank_table = lod_tensor_to_array(x=[x], table=table)
+
+            self.assertRaises(TypeError, test_x_list_Variable)
+
+            def test_table_list_Variable():
+                rank_table = lod_tensor_to_array(x=x2, table=[table2])
+
+            self.assertRaises(TypeError, test_table_list_Variable)
+
+            array = lod_tensor_to_array(x2, table)
+
+
+class TestArrayLoDTensorError(unittest.TestCase):
+    def test_errors(self):
+        with program_guard(Program(), Program()):
+            x = numpy.random.random((10)).astype("float32")
+            x2 = layers.data(name='x', shape=[10])
+            table = lod_rank_table(x2, level=0)
+            array = lod_tensor_to_array(x2, table)
+
+            def test_x_Variable():
+                rank_table = array_to_lod_tensor(x=x, table=table)
+
+            self.assertRaises(TypeError, test_x_Variable)
+
+            table2 = numpy.random.random((2)).astype("int64")
+
+            def test_table_Variable():
+                rank_table = array_to_lod_tensor(x=array, table=table2)
+
+            self.assertRaises(TypeError, test_table_Variable)
+
+            def test_x_list_Variable():
+                rank_table = array_to_lod_tensor(x=[x], table=table)
+
+            self.assertRaises(TypeError, test_x_list_Variable)
+
+            def test_table_list_Variable():
+                rank_table = array_to_lod_tensor(x=x2, table=[table2])
+
+            self.assertRaises(TypeError, test_table_list_Variable)
+
+            array = array_to_lod_tensor(x2, table)
+
+
 if __name__ == '__main__':
     unittest.main()