Refine check_type Error Message for @declarative (#25098)

* Refine check_type for @declarative test=develop

python/paddle/fluid/data_feeder.py

@@ -60,7 +60,7 @@ def convert_dtype(dtype):
                 u'float64', u'int8', u'int16', u'int32', u'int64', u'uint8'
         ]:
             # this code is a little bit dangerous, since error could happen
-            # when casting no-asci code to str in python2.
+            # when casting no-ascii code to str in python2.
             # but since the set itself is limited, so currently, it is good.
             # however, jointly supporting python2 and python3, (as well as python4 maybe)
             # may still be a long-lasting problem.
@@ -76,8 +76,7 @@ def check_variable_and_dtype(input,
                              expected_dtype,
                              op_name,
                              extra_message=''):
-    check_type(input, input_name, (Variable, core.VarBase), op_name,
+    check_type(input, input_name, Variable, op_name, extra_message)
-               extra_message)
     check_dtype(input.dtype, input_name, expected_dtype, op_name, extra_message)
 
 
@@ -91,6 +90,22 @@ def check_type(input, input_name, expected_type, op_name, extra_message=''):
     # each step in dynamic graph mode, it will bring a heavy performance burden.
     if in_dygraph_mode():
         return
+
+    from .dygraph.dygraph_to_static.program_translator import in_declarative_mode
+    # NOTE: `in_declarative_mode` is used to determined whether this op is called under
+    # @declarative in transformation from dygrah to static layer. We add VarBase in
+    # expected_type to skip checking because varBase may be created and used in unusual way.
+    # Need a better design to be fix this.
+    if in_declarative_mode():
+        if not isinstance(expected_type, tuple):
+            expected_type = (expected_type, )
+        expected_type += (core.VarBase, )
+    elif isinstance(input, core.VarBase):
+        raise TypeError(
+            "Please use `with fluid.dygraph.guard()` as context or `fluid.enable_dygraph()` to switch to imperative mode firstly. "
+            "Because received '{}' in {} is a imperative Variable.".format(
+                input_name, op_name))
+
     if not isinstance(input, expected_type):
         raise TypeError(
             "The type of '%s' in %s must be %s, but received %s. %s" %

python/paddle/fluid/dygraph/dygraph_to_static/program_translator.py

@@ -31,6 +31,7 @@ from paddle.fluid.dygraph.base import switch_to_static_graph
 from paddle.fluid.dygraph.dygraph_to_static.ast_transformer import convert_to_static
 from paddle.fluid.dygraph.dygraph_to_static.ast_transformer import DygraphToStaticAst
 from paddle.fluid.dygraph.dygraph_to_static.utils import ast_to_source_code
+from paddle.fluid.wrapped_decorator import signature_safe_contextmanager
 from paddle.fluid.dygraph.base import param_guard
 from paddle.fluid.data_feeder import check_type
 from paddle.fluid.dygraph.dygraph_to_static.partial_program import partial_program_from
@@ -155,6 +156,28 @@ class FunctionSpec(object):
         return self.__key() == self.__key()
 
 
+# Flag that indicates whether running code under `@declarative`
+_in_declarative_mode_ = False
+
+
+def in_declarative_mode():
+    """
+    Return a bool value that indicates whether running code under `@declarative`
+
+    """
+    return _in_declarative_mode_
+
+
+@signature_safe_contextmanager
+def _switch_declarative_mode_guard_(is_declarative=True):
+
+    global _in_declarative_mode_
+    original_val = _in_declarative_mode_
+    _in_declarative_mode_ = is_declarative
+    yield
+    _in_declarative_mode_ = original_val
+
+
 class ConcreteProgram(object):
     def __init__(self,
                  inputs,
@@ -190,17 +213,18 @@ class ConcreteProgram(object):
         ).random_seed
 
         with framework.program_guard(main_program, startup_program):
-            # 1. Adds `fluid.data` layers for input if needed
+            with _switch_declarative_mode_guard_(is_declarative=True):
-            inputs = func_spec.to_static_inputs(main_program)
+                # 1. Adds `fluid.data` layers for input if needed
-
+                inputs = func_spec.to_static_inputs(main_program)
-            # 2. Gets all ParamBases in the function
+
-            all_parameters = list(func_spec.parameters().values())
+                # 2. Gets all ParamBases in the function
-
+                all_parameters = list(func_spec.parameters().values())
-            # 3. Builds program only once and returns the output Variables.
+
-            with param_guard(func_spec.parameters(False)):
+                # 3. Builds program only once and returns the output Variables.
-                outputs = static_func(*inputs)
+                with param_guard(func_spec.parameters(False)):
-            if not isinstance(outputs, (tuple, list)):
+                    outputs = static_func(*inputs)
-                outputs = [outputs] if outputs else []
+                if not isinstance(outputs, (tuple, list)):
+                    outputs = [outputs] if outputs else []
 
         return ConcreteProgram(
             inputs=inputs,

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

@@ -645,5 +645,14 @@ class TestDygraphUtils(unittest.TestCase):
             self.assertTrue(np.array_equal(res1.numpy(), res2.numpy()))
 
 
+class TestDygraphGuardWithError(unittest.TestCase):
+    def test_without_guard(self):
+        with fluid.dygraph.guard():
+            x = fluid.dygraph.to_variable(np.zeros([10, 10]))
+        with self.assertRaisesRegexp(TypeError,
+                                     "Please use `with fluid.dygraph.guard()"):
+            y = fluid.layers.matmul(x, x)
+
+
 if __name__ == '__main__':
     unittest.main()