refine error message of input TypeError in framework.py (#19970)

* refine error message of input TypeError in framework.py

test=develop

* refine error message

test=develop

* update test_compare_op.py unit-test to improve coverage

test=develop

python/paddle/fluid/framework.py

@@ -1756,9 +1756,12 @@ class Operator(object):
                             elif isinstance(arg, Variable):
                                 in_arg_names.append(cpt.to_text(arg.name))
                             else:
-                                raise ValueError(
-                                    "not suprt args type , should be[ string_type, binary_type, Varibale]"
-                                )
+                                raise TypeError(
+                                    "The type of '%s' in operator %s should be "
+                                    "one of [basestring(), str, Varibale] in python2, "
+                                    "or one of [str, bytes, Variable] in python3."
+                                    "but received : " % (in_proto.name, type),
+                                    arg)
                         self.desc.set_input(in_proto.name, in_arg_names)
                     else:
                         self.desc.set_input(in_proto.name, [])

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

@@ -17,6 +17,8 @@ from __future__ import print_function
 import op_test
 import unittest
 import numpy
+import paddle.fluid as fluid
+from paddle.fluid import Program, program_guard
 
 
 def create_test_class(op_type, typename, callback):
@@ -45,5 +47,16 @@ for _type_name in {'float32', 'float64', 'int32', 'int64'}:
     create_test_class('equal', _type_name, lambda _a, _b: _a == _b)
     create_test_class('not_equal', _type_name, lambda _a, _b: _a != _b)
 
+
+class TestCompareOpError(op_test.OpTest):
+    def test_errors(self):
+        with program_guard(Program(), Program()):
+            # The input x and y of compare_op must be Variable.
+            x = fluid.layers.data(name='x', shape=[1], dtype="float32")
+            y = fluid.create_lod_tensor(
+                numpy.array([[-1]]), [[1]], fluid.CPUPlace())
+            self.assertRaises(TypeError, fluid.layers.greater_equal, x, y)
+
+
 if __name__ == '__main__':
     unittest.main()