Raise RuntimeError if run the callable object decorated by...

Raise RuntimeError if run the callable object decorated by '@paddle.jit.to_static' not in dynamic mode.  (#26750)

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

@@ -24,6 +24,7 @@ import warnings
 
 import gast
 from paddle.fluid import framework
+from paddle.fluid import in_dygraph_mode
 from paddle.fluid.dygraph import layers
 from paddle.fluid.data_feeder import check_type
 from paddle.fluid.layers.utils import flatten
@@ -32,6 +33,7 @@ from paddle.fluid.dygraph.base import switch_to_static_graph
 from paddle.fluid.dygraph.dygraph_to_static import DygraphToStaticAst
 from paddle.fluid.dygraph.dygraph_to_static.error import ERROR_DATA
 from paddle.fluid.dygraph.dygraph_to_static.error import attach_error_data
+from paddle.fluid.dygraph.dygraph_to_static import logging_utils
 from paddle.fluid.dygraph.dygraph_to_static.origin_info import attach_origin_info
 from paddle.fluid.dygraph.dygraph_to_static.origin_info import create_and_update_origin_info_map
 from paddle.fluid.dygraph.dygraph_to_static.origin_info import update_op_callstack_with_origin_info
@@ -283,13 +285,21 @@ class StaticLayer(object):
         Return:
             Outputs of decorated function.
         """
+
         # 1. call dygraph function directly if not enable `declarative`
         if not self._program_trans.enable_declarative:
-            warnings.warn(
-                "The decorator '@paddle.jit.to_static' doesn't work when setting ProgramTranslator.enable=False. "
+            logging_utils.warn(
+                "The decorator '@paddle.jit.to_static' does NOT work when setting ProgramTranslator.enable=False. "
                 "We will just return dygraph output.")
             return self._call_dygraph_function(*args, **kwargs)
 
+        if not in_dygraph_mode() and self._program_trans.enable_declarative:
+            raise RuntimeError(
+                "Failed to run the callable object {} decorated by '@paddle.jit.to_static', "
+                "because it does NOT in dynamic mode. Please disable the static mode to enter dynamic mode with the "
+                "following API: paddle.disable_static().".format(
+                    self.dygraph_function))
+
         # 2. trace ops from dygraph layers and cache the generated program.
         args, kwargs = self._function_spec.unified_args_and_kwargs(args, kwargs)
         try:

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

@@ -13,13 +13,15 @@
 # limitations under the License.
 
 import numpy as np
+import unittest
+
 import paddle
-from paddle.static import InputSpec
 import paddle.fluid as fluid
+from paddle.static import InputSpec
 from paddle.fluid.dygraph import to_variable, declarative, ProgramTranslator, Layer, jit
 from paddle.fluid.dygraph.dygraph_to_static.program_translator import ConcreteProgram
 
-import unittest
+from test_basic_api_transformation import dyfunc_to_variable
 
 program_trans = ProgramTranslator()
 
@@ -181,6 +183,9 @@ def foo_func(a, b, c=1, d=2):
 
 
 class TestDifferentInputSpecCacheProgram(unittest.TestCase):
+    def setUp(self):
+        program_trans.enable(True)
+
     def test_with_different_input(self):
         with fluid.dygraph.guard(fluid.CPUPlace()):
             x_data = np.ones([16, 10]).astype('float32')
@@ -272,5 +277,23 @@ class TestDifferentInputSpecCacheProgram(unittest.TestCase):
                 foo_3.concrete_program
 
 
+class TestDeclarativeAPI(unittest.TestCase):
+    def test_error(self):
+        func = declarative(dyfunc_to_variable)
+
+        paddle.enable_static()
+
+        # Failed to run the callable object decorated by '@paddle.jit.to_static'
+        # if it does NOT in dynamic mode.
+        with self.assertRaises(RuntimeError):
+            func(np.ones(5).astype("int32"))
+
+        program_trans.enable(False)
+        with self.assertRaises(AssertionError):
+            # AssertionError: We Only support to_variable in imperative mode,
+            #  please use fluid.dygraph.guard() as context to run it in imperative Mode
+            func(np.ones(5).astype("int32"))
+
+
 if __name__ == '__main__':
     unittest.main()