enhance error message (#26808)

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

@@ -393,19 +393,43 @@ class StaticLayer(object):
     def concrete_program(self):
         """
         Returns recent ConcreteProgram instance of decorated function.
+
+        Examples:
+            .. code-block:: python
+
+                import paddle
+                from paddle.jit import to_static
+                from paddle.static import InputSpec
+
+                paddle.disable_static()
+
+                def foo(x, y):
+                    z = x + y
+                    return z
+                
+                # usage 1:
+                decorated_foo = to_static(foo, input_spec=[InputSpec([10], name='x'), InputSpec([10], name='y')])
+                print(decorated_foo.concrete_program)
+
+                # usage 2:
+                decorated_foo = to_static(foo)
+                out_foo = decorated_foo(paddle.rand([10]), paddle.rand([10]))
+                print(decorated_foo.concrete_program)
         """
         # if specific the `input_spec`, the length of program_cache will always 1,
         # else, return the last one.
         cached_program_len = len(self._program_cache)
         # If specific `input_spec`, apply convertion from dygraph layers into static Program.
         if cached_program_len == 0:
-            if len(self._function_spec.flat_input_spec) > 0:
             input_spec = self._function_spec.input_spec
+            has_input_spec = (input_spec is not None and len(input_spec) > 0)
+            if has_input_spec:
                 concrete_program, _ = self.get_concrete_program(*input_spec)
                 return concrete_program
             else:
-                raise ValueError("No valid transformed program for {}".format(
-                    self._function_spec))
+                raise ValueError(
+                    "No valid transformed program for {}.\n\t    Please specific `input_spec` in `@paddle.jit.to_static` or feed input tensor to call the decorated function at once.\n".
+                    format(self._function_spec))
         # If more than one programs have been cached, return the recent converted program by default.
         elif cached_program_len > 1:
             logging.warning(

python/paddle/fluid/tests/unittests/dygraph_to_static/test_declarative.py

@@ -13,9 +13,11 @@
 # limitations under the License.
 
 import numpy as np
+import paddle
 from paddle.static import InputSpec
 import paddle.fluid as fluid
 from paddle.fluid.dygraph import to_variable, declarative, ProgramTranslator, Layer, jit
+from paddle.fluid.dygraph.dygraph_to_static.program_translator import ConcreteProgram
 
 import unittest
 
@@ -246,6 +248,29 @@ class TestDifferentInputSpecCacheProgram(unittest.TestCase):
         concrete_program_5 = foo.get_concrete_program(
             InputSpec([10]), InputSpec([10]), e=4)
 
+    def test_concrete_program(self):
+        with fluid.dygraph.guard(fluid.CPUPlace()):
+
+            # usage 1
+            foo_1 = paddle.jit.to_static(
+                foo_func,
+                input_spec=[
+                    InputSpec(
+                        [10], name='x'), InputSpec(
+                            [10], name='y')
+                ])
+            self.assertTrue(isinstance(foo_1.concrete_program, ConcreteProgram))
+
+            # usage 2
+            foo_2 = paddle.jit.to_static(foo_func)
+            out = foo_2(paddle.rand([10]), paddle.rand([10]))
+            self.assertTrue(isinstance(foo_2.concrete_program, ConcreteProgram))
+
+            # raise error
+            foo_3 = paddle.jit.to_static(foo_func)
+            with self.assertRaises(ValueError):
+                foo_3.concrete_program
+
 
 if __name__ == '__main__':
     unittest.main()