diff --git a/paddle/fluid/API.spec b/paddle/fluid/API.spec
index f50a38842a21c795c979f859e88a9b16c3e54bd8..df961be911537582fb60dd258fcdd4a5dd41a38e 100644
--- a/paddle/fluid/API.spec
+++ b/paddle/fluid/API.spec
@@ -8,13 +8,13 @@ paddle.fluid.Program.parse_from_string ArgSpec(args=['binary_str'], varargs=None
 paddle.fluid.Program.to_string ArgSpec(args=['self', 'throw_on_error', 'with_details'], varargs=None, keywords=None, defaults=(False,))
 paddle.fluid.default_startup_program ArgSpec(args=[], varargs=None, keywords=None, defaults=None)
 paddle.fluid.default_main_program ArgSpec(args=[], varargs=None, keywords=None, defaults=None)
-paddle.fluid.program_guard ArgSpec(args=[], varargs='args', keywords='kwds', defaults=None)
-paddle.fluid.name_scope ArgSpec(args=[], varargs='args', keywords='kwds', defaults=None)
+paddle.fluid.program_guard ArgSpec(args=['main_program', 'startup_program'], varargs=None, keywords=None, defaults=(None,))
+paddle.fluid.name_scope ArgSpec(args=['prefix'], varargs=None, keywords=None, defaults=(None,))
 paddle.fluid.Executor.__init__ ArgSpec(args=['self', 'place'], varargs=None, keywords=None, defaults=None)
 paddle.fluid.Executor.close ArgSpec(args=['self'], varargs=None, keywords=None, defaults=None)
 paddle.fluid.Executor.run ArgSpec(args=['self', 'program', 'feed', 'fetch_list', 'feed_var_name', 'fetch_var_name', 'scope', 'return_numpy', 'use_program_cache'], varargs=None, keywords=None, defaults=(None, None, None, 'feed', 'fetch', None, True, False))
 paddle.fluid.global_scope ArgSpec(args=[], varargs=None, keywords=None, defaults=None)
-paddle.fluid.scope_guard ArgSpec(args=[], varargs='args', keywords='kwds', defaults=None)
+paddle.fluid.scope_guard ArgSpec(args=['scope'], varargs=None, keywords=None, defaults=None)
 paddle.fluid.DistributeTranspiler.__init__ ArgSpec(args=['self', 'config'], varargs=None, keywords=None, defaults=(None,))
 paddle.fluid.DistributeTranspiler.get_pserver_program ArgSpec(args=['self', 'endpoint'], varargs=None, keywords=None, defaults=None)
 paddle.fluid.DistributeTranspiler.get_pserver_programs ArgSpec(args=['self', 'endpoint'], varargs=None, keywords=None, defaults=None)
@@ -66,7 +66,7 @@ paddle.fluid.initializer.XavierInitializer.__init__ ArgSpec(args=['self', 'unifo
 paddle.fluid.initializer.BilinearInitializer.__init__ ArgSpec(args=['self'], varargs=None, keywords=None, defaults=None)
 paddle.fluid.initializer.MSRAInitializer.__init__ ArgSpec(args=['self', 'uniform', 'fan_in', 'seed'], varargs=None, keywords=None, defaults=(True, None, 0))
 paddle.fluid.initializer.force_init_on_cpu ArgSpec(args=[], varargs=None, keywords=None, defaults=None)
-paddle.fluid.initializer.init_on_cpu ArgSpec(args=[], varargs='args', keywords='kwds', defaults=None)
+paddle.fluid.initializer.init_on_cpu ArgSpec(args=[], varargs=None, keywords=None, defaults=None)
 paddle.fluid.initializer.NumpyArrayInitializer.__init__ ArgSpec(args=['self', 'value'], varargs=None, keywords=None, defaults=None)
 paddle.fluid.layers.fc ArgSpec(args=['input', 'size', 'num_flatten_dims', 'param_attr', 'bias_attr', 'act', 'is_test', 'name'], varargs=None, keywords=None, defaults=(1, None, None, None, False, None))
 paddle.fluid.layers.embedding ArgSpec(args=['input', 'size', 'is_sparse', 'is_distributed', 'padding_idx', 'param_attr', 'dtype'], varargs=None, keywords=None, defaults=(False, False, None, None, 'float32'))
@@ -229,7 +229,7 @@ paddle.fluid.layers.random_data_generator ArgSpec(args=['low', 'high', 'shapes',
 paddle.fluid.layers.py_reader ArgSpec(args=['capacity', 'shapes', 'dtypes', 'lod_levels', 'name', 'use_double_buffer'], varargs=None, keywords=None, defaults=(None, None, True))
 paddle.fluid.layers.create_py_reader_by_data ArgSpec(args=['capacity', 'feed_list', 'name', 'use_double_buffer'], varargs=None, keywords=None, defaults=(None, True))
 paddle.fluid.layers.Preprocessor.__init__ ArgSpec(args=['self', 'reader', 'name'], varargs=None, keywords=None, defaults=(None,))
-paddle.fluid.layers.Preprocessor.block ArgSpec(args=[], varargs='args', keywords='kwds', defaults=None)
+paddle.fluid.layers.Preprocessor.block ArgSpec(args=['self'], varargs=None, keywords=None, defaults=None)
 paddle.fluid.layers.Preprocessor.inputs ArgSpec(args=['self'], varargs=None, keywords=None, defaults=None)
 paddle.fluid.layers.Preprocessor.outputs ArgSpec(args=['self'], varargs='outs', keywords=None, defaults=None)
 paddle.fluid.layers.load ArgSpec(args=['out', 'file_path', 'load_as_fp16'], varargs=None, keywords=None, defaults=(None,))
@@ -270,7 +270,7 @@ paddle.fluid.layers.IfElse.input ArgSpec(args=['self', 'x'], varargs=None, keywo
 paddle.fluid.layers.IfElse.output ArgSpec(args=['self'], varargs='outs', keywords=None, defaults=None)
 paddle.fluid.layers.IfElse.true_block ArgSpec(args=['self'], varargs=None, keywords=None, defaults=None)
 paddle.fluid.layers.DynamicRNN.__init__ ArgSpec(args=['self', 'name'], varargs=None, keywords=None, defaults=(None,))
-paddle.fluid.layers.DynamicRNN.block ArgSpec(args=[], varargs='args', keywords='kwds', defaults=None)
+paddle.fluid.layers.DynamicRNN.block ArgSpec(args=['self'], varargs=None, keywords=None, defaults=None)
 paddle.fluid.layers.DynamicRNN.memory ArgSpec(args=['self', 'init', 'shape', 'value', 'need_reorder', 'dtype'], varargs=None, keywords=None, defaults=(None, None, 0.0, False, 'float32'))
 paddle.fluid.layers.DynamicRNN.output ArgSpec(args=['self'], varargs='outputs', keywords=None, defaults=None)
 paddle.fluid.layers.DynamicRNN.static_input ArgSpec(args=['self', 'x'], varargs=None, keywords=None, defaults=None)
@@ -346,12 +346,12 @@ paddle.fluid.contrib.StateCell.set_state ArgSpec(args=['self', 'state_name', 'st
 paddle.fluid.contrib.StateCell.state_updater ArgSpec(args=['self', 'updater'], varargs=None, keywords=None, defaults=None)
 paddle.fluid.contrib.StateCell.update_states ArgSpec(args=['self'], varargs=None, keywords=None, defaults=None)
 paddle.fluid.contrib.TrainingDecoder.__init__ ArgSpec(args=['self', 'state_cell', 'name'], varargs=None, keywords=None, defaults=(None,))
-paddle.fluid.contrib.TrainingDecoder.block ArgSpec(args=[], varargs='args', keywords='kwds', defaults=None)
+paddle.fluid.contrib.TrainingDecoder.block ArgSpec(args=['self'], varargs=None, keywords=None, defaults=None)
 paddle.fluid.contrib.TrainingDecoder.output ArgSpec(args=['self'], varargs='outputs', keywords=None, defaults=None)
 paddle.fluid.contrib.TrainingDecoder.static_input ArgSpec(args=['self', 'x'], varargs=None, keywords=None, defaults=None)
 paddle.fluid.contrib.TrainingDecoder.step_input ArgSpec(args=['self', 'x'], varargs=None, keywords=None, defaults=None)
 paddle.fluid.contrib.BeamSearchDecoder.__init__ ArgSpec(args=['self', 'state_cell', 'init_ids', 'init_scores', 'target_dict_dim', 'word_dim', 'input_var_dict', 'topk_size', 'sparse_emb', 'max_len', 'beam_size', 'end_id', 'name'], varargs=None, keywords=None, defaults=({}, 50, True, 100, 1, 1, None))
-paddle.fluid.contrib.BeamSearchDecoder.block ArgSpec(args=[], varargs='args', keywords='kwds', defaults=None)
+paddle.fluid.contrib.BeamSearchDecoder.block ArgSpec(args=['self'], varargs=None, keywords=None, defaults=None)
 paddle.fluid.contrib.BeamSearchDecoder.decode ArgSpec(args=['self'], varargs=None, keywords=None, defaults=None)
 paddle.fluid.contrib.BeamSearchDecoder.early_stop ArgSpec(args=['self'], varargs=None, keywords=None, defaults=None)
 paddle.fluid.contrib.BeamSearchDecoder.read_array ArgSpec(args=['self', 'init', 'is_ids', 'is_scores'], varargs=None, keywords=None, defaults=(False, False))
@@ -456,7 +456,7 @@ paddle.fluid.optimizer.AdadeltaOptimizer.apply_gradients ArgSpec(args=['self', '
 paddle.fluid.optimizer.AdadeltaOptimizer.backward ArgSpec(args=['self', 'loss', 'startup_program', 'parameter_list', 'no_grad_set', 'callbacks'], varargs=None, keywords=None, defaults=(None, None, None, None))
 paddle.fluid.optimizer.AdadeltaOptimizer.minimize ArgSpec(args=['self', 'loss', 'startup_program', 'parameter_list', 'no_grad_set'], varargs=None, keywords=None, defaults=(None, None, None))
 paddle.fluid.optimizer.ModelAverage.__init__ ArgSpec(args=['self', 'average_window_rate', 'min_average_window', 'max_average_window', 'regularization', 'name'], varargs=None, keywords=None, defaults=(10000, 10000, None, None))
-paddle.fluid.optimizer.ModelAverage.apply ArgSpec(args=[], varargs='args', keywords='kwds', defaults=None)
+paddle.fluid.optimizer.ModelAverage.apply ArgSpec(args=['self', 'executor', 'need_restore'], varargs=None, keywords=None, defaults=(True,))
 paddle.fluid.optimizer.ModelAverage.apply_gradients ArgSpec(args=['self', 'params_grads'], varargs=None, keywords=None, defaults=None)
 paddle.fluid.optimizer.ModelAverage.backward ArgSpec(args=['self', 'loss', 'startup_program', 'parameter_list', 'no_grad_set', 'callbacks'], varargs=None, keywords=None, defaults=(None, None, None, None))
 paddle.fluid.optimizer.ModelAverage.minimize ArgSpec(args=['self', 'loss', 'startup_program', 'parameter_list', 'no_grad_set'], varargs=None, keywords=None, defaults=(None, None, None))
@@ -491,14 +491,14 @@ paddle.fluid.clip.ErrorClipByValue.__init__ ArgSpec(args=['self', 'max', 'min'],
 paddle.fluid.clip.GradientClipByValue.__init__ ArgSpec(args=['self', 'max', 'min'], varargs=None, keywords=None, defaults=(None,))
 paddle.fluid.clip.GradientClipByNorm.__init__ ArgSpec(args=['self', 'clip_norm'], varargs=None, keywords=None, defaults=None)
 paddle.fluid.clip.GradientClipByGlobalNorm.__init__ ArgSpec(args=['self', 'clip_norm', 'group_name'], varargs=None, keywords=None, defaults=('default_group',))
-paddle.fluid.profiler.cuda_profiler ArgSpec(args=[], varargs='args', keywords='kwds', defaults=None)
+paddle.fluid.profiler.cuda_profiler ArgSpec(args=['output_file', 'output_mode', 'config'], varargs=None, keywords=None, defaults=(None, None))
 paddle.fluid.profiler.reset_profiler ArgSpec(args=[], varargs=None, keywords=None, defaults=None)
-paddle.fluid.profiler.profiler ArgSpec(args=[], varargs='args', keywords='kwds', defaults=None)
+paddle.fluid.profiler.profiler ArgSpec(args=['state', 'sorted_key', 'profile_path'], varargs=None, keywords=None, defaults=(None, '/tmp/profile'))
 paddle.fluid.profiler.start_profiler ArgSpec(args=['state'], varargs=None, keywords=None, defaults=None)
 paddle.fluid.profiler.stop_profiler ArgSpec(args=['sorted_key', 'profile_path'], varargs=None, keywords=None, defaults=(None, '/tmp/profile'))
 paddle.fluid.unique_name.generate ArgSpec(args=['key'], varargs=None, keywords=None, defaults=None)
 paddle.fluid.unique_name.switch ArgSpec(args=['new_generator'], varargs=None, keywords=None, defaults=(None,))
-paddle.fluid.unique_name.guard ArgSpec(args=[], varargs='args', keywords='kwds', defaults=None)
+paddle.fluid.unique_name.guard ArgSpec(args=['new_generator'], varargs=None, keywords=None, defaults=(None,))
 paddle.fluid.recordio_writer.convert_reader_to_recordio_file ArgSpec(args=['filename', 'reader_creator', 'feeder', 'compressor', 'max_num_records', 'feed_order'], varargs=None, keywords=None, defaults=(Compressor.Snappy, 1000, None))
 paddle.fluid.recordio_writer.convert_reader_to_recordio_files ArgSpec(args=['filename', 'batch_per_file', 'reader_creator', 'feeder', 'compressor', 'max_num_records', 'feed_order'], varargs=None, keywords=None, defaults=(Compressor.Snappy, 1000, None))
 paddle.fluid.Scope Scope() -> paddle.fluid.core._Scope
diff --git a/python/paddle/fluid/contrib/decoder/beam_search_decoder.py b/python/paddle/fluid/contrib/decoder/beam_search_decoder.py
index f2b7ac8375af25beed562b8279b6044f11c09d44..5854cadb58c76066ba4b48dc6b5dbca06fba8cba 100644
--- a/python/paddle/fluid/contrib/decoder/beam_search_decoder.py
+++ b/python/paddle/fluid/contrib/decoder/beam_search_decoder.py
@@ -22,7 +22,7 @@ This API is still under active development and may change drastically.
 
 from __future__ import print_function
 
-import contextlib
+from ...wrapped_decorator import signature_safe_contextmanager
 import numpy as np
 import six
 
@@ -419,7 +419,7 @@ class TrainingDecoder(object):
         self._state_cell = state_cell
         self._state_cell._enter_decoder(self)
 
-    @contextlib.contextmanager
+    @signature_safe_contextmanager
     def block(self):
         """
         Define the behavior of the decoder for each RNN time step.
@@ -613,7 +613,7 @@ class BeamSearchDecoder(object):
         self._word_dim = word_dim
         self._input_var_dict = input_var_dict
 
-    @contextlib.contextmanager
+    @signature_safe_contextmanager
     def block(self):
         """
         Define the behavior of the decoder for each RNN time step.
diff --git a/python/paddle/fluid/contrib/inferencer.py b/python/paddle/fluid/contrib/inferencer.py
index b8d5f4ffeadca0a7b103682f175d50dc46fa258a..4f37129234482189436ad71391f55394e2b8a277 100644
--- a/python/paddle/fluid/contrib/inferencer.py
+++ b/python/paddle/fluid/contrib/inferencer.py
@@ -14,7 +14,7 @@
 
 from __future__ import print_function
 
-import contextlib
+from ..wrapped_decorator import signature_safe_contextmanager
 
 from .. import core
 
@@ -105,7 +105,7 @@ class Inferencer(object):
 
         return results
 
-    @contextlib.contextmanager
+    @signature_safe_contextmanager
     def _prog_and_scope_guard(self):
         with framework.program_guard(main_program=self.inference_program):
             with executor.scope_guard(self.scope):
diff --git a/python/paddle/fluid/contrib/trainer.py b/python/paddle/fluid/contrib/trainer.py
index 8569e486f91786b5562e84dcdccf6d91da0612cc..d27b808438d53a004db4e85345a68c35d00fff98 100644
--- a/python/paddle/fluid/contrib/trainer.py
+++ b/python/paddle/fluid/contrib/trainer.py
@@ -14,7 +14,7 @@
 
 from __future__ import print_function
 
-import contextlib
+from ..wrapped_decorator import signature_safe_contextmanager
 import os
 import errno
 import shutil
@@ -453,7 +453,7 @@ class Trainer(object):
             io.save_inference_model(param_path, feeded_var_names, target_vars,
                                     exe)
 
-    @contextlib.contextmanager
+    @signature_safe_contextmanager
     def _prog_and_scope_guard(self):
         with framework.program_guard(
                 main_program=self.train_program,
diff --git a/python/paddle/fluid/executor.py b/python/paddle/fluid/executor.py
index d3ff14a17955990bff851e95bd61fbc370ea7aa5..8815911eaeb36067987c0490d7a4f3e909789499 100644
--- a/python/paddle/fluid/executor.py
+++ b/python/paddle/fluid/executor.py
@@ -17,7 +17,7 @@ from __future__ import print_function
 import os
 import multiprocessing
 import numpy as np
-import contextlib
+from .wrapped_decorator import signature_safe_contextmanager
 import six
 from .framework import Program, default_main_program, Variable
 from . import core
@@ -49,7 +49,7 @@ def _switch_scope(scope):
     return ex
 
 
-@contextlib.contextmanager
+@signature_safe_contextmanager
 def scope_guard(scope):
     """
     Change the global/default scope instance by Python `with` statement. All
diff --git a/python/paddle/fluid/framework.py b/python/paddle/fluid/framework.py
index c0b0ad8a202b82183de9ec1edd43cb10db10fb5c..832c97c7deb49b4e118e15989ab7a34da6ce57a0 100644
--- a/python/paddle/fluid/framework.py
+++ b/python/paddle/fluid/framework.py
@@ -16,7 +16,7 @@ from __future__ import print_function
 
 import collections
 from collections import defaultdict
-import contextlib
+from .wrapped_decorator import signature_safe_contextmanager
 import os
 import re
 import traceback
@@ -111,7 +111,7 @@ class NameScope(object):
 _name_scope = NameScope()
 
 
-@contextlib.contextmanager
+@signature_safe_contextmanager
 def name_scope(prefix=None):
     """
     Generate hierarchical name prefix for the operators.
@@ -1775,7 +1775,7 @@ class Program(object):
     def set_op_role_var(self, var_name):
         self._op_role_var = [var_name]
 
-    @contextlib.contextmanager
+    @signature_safe_contextmanager
     def _optimized_guard(self, param_and_grads):
         """
         A with guard to set :code:`Optimization` :code:`OpRole` and
@@ -1805,7 +1805,7 @@ class Program(object):
         self._op_role_var = tmp_var
         self._current_role = tmp_role
 
-    @contextlib.contextmanager
+    @signature_safe_contextmanager
     def _lr_schedule_guard(self, is_with_opt=False):
         """
         A with guard to set :code:`LRSched` :code:`OpRole` and
@@ -2459,7 +2459,7 @@ def switch_startup_program(program):
     return prev_program
 
 
-@contextlib.contextmanager
+@signature_safe_contextmanager
 def program_guard(main_program, startup_program=None):
     """
     Change the global main program and startup program with `with` statement.
@@ -2524,7 +2524,7 @@ def _get_var(name, program=None):
     return program.global_block().var(name)
 
 
-@contextlib.contextmanager
+@signature_safe_contextmanager
 def _imperative_guard(tracer):
     global _imperative_tracer_
     tmp_trace = _imperative_tracer_
@@ -2535,7 +2535,7 @@ def _imperative_guard(tracer):
     _imperative_tracer_ = tmp_trace
 
 
-@contextlib.contextmanager
+@signature_safe_contextmanager
 def _imperative_place_guard(place):
     global _imperative_current_expected_place_
     tmp_place = _imperative_current_expected_place_
diff --git a/python/paddle/fluid/imperative/base.py b/python/paddle/fluid/imperative/base.py
index ff3984b11f42cf9e6ff49c8654c600c065effe1d..d4525233cc681720404770ef1d0c5d3006607a2e 100644
--- a/python/paddle/fluid/imperative/base.py
+++ b/python/paddle/fluid/imperative/base.py
@@ -11,7 +11,7 @@
 # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 # See the License for the specific language governing permissions and
 # limitations under the License.
-import contextlib
+from ..wrapped_decorator import signature_safe_contextmanager
 import numpy as np
 
 from paddle.fluid import core
@@ -24,7 +24,7 @@ def enabled():
     return framework._in_imperative_mode()
 
 
-@contextlib.contextmanager
+@signature_safe_contextmanager
 def guard(place=None):
     train = framework.Program()
     startup = framework.Program()
diff --git a/python/paddle/fluid/initializer.py b/python/paddle/fluid/initializer.py
index 5be21ff7f7270f6ce950c069f61418c922bcedc5..e8341be28683a25971a53a37c70533a16add1593 100644
--- a/python/paddle/fluid/initializer.py
+++ b/python/paddle/fluid/initializer.py
@@ -16,7 +16,7 @@ from __future__ import print_function
 
 from . import framework
 import numpy as np
-import contextlib
+from .wrapped_decorator import signature_safe_contextmanager
 from .core import VarDesc
 from . import unique_name
 
@@ -49,7 +49,7 @@ def force_init_on_cpu():
     return _force_init_on_cpu_
 
 
-@contextlib.contextmanager
+@signature_safe_contextmanager
 def init_on_cpu():
     """
     Force the variable to be inited on CPU.
diff --git a/python/paddle/fluid/layers/control_flow.py b/python/paddle/fluid/layers/control_flow.py
index a7494aaceab42332cb4362ab1df43d9e0b139f4f..3a6753b01f152f61b78a9f04f4fe32136c051a19 100644
--- a/python/paddle/fluid/layers/control_flow.py
+++ b/python/paddle/fluid/layers/control_flow.py
@@ -13,7 +13,7 @@
 # limitations under the License.
 
 from __future__ import print_function
-import contextlib
+from ..wrapped_decorator import signature_safe_contextmanager
 
 from .layer_function_generator import autodoc, templatedoc
 from .tensor import assign, fill_constant
@@ -1532,7 +1532,7 @@ class DynamicRNN(object):
             outputs={'Out': [x_reordered]})
         return shrink_memory(x_reordered, self.step_idx, self.lod_rank_table)
 
-    @contextlib.contextmanager
+    @signature_safe_contextmanager
     def block(self):
         """
         The block for user to define operators in RNN. See the class docstring
diff --git a/python/paddle/fluid/layers/io.py b/python/paddle/fluid/layers/io.py
index 1762bd3e343e8af6768dd23f8fbc58cd0182d3c9..b88be66906e806aeee55c1af6235a6fef9da7030 100644
--- a/python/paddle/fluid/layers/io.py
+++ b/python/paddle/fluid/layers/io.py
@@ -13,7 +13,7 @@
 # limitations under the License.
 
 from __future__ import print_function
-import contextlib
+from ..wrapped_decorator import signature_safe_contextmanager
 import multiprocessing
 import os
 import six
@@ -1116,7 +1116,7 @@ class Preprocessor(object):
     def _is_completed(self):
         return self.sub_block and self.source_var_names and self.sink_var_names
 
-    @contextlib.contextmanager
+    @signature_safe_contextmanager
     def block(self):
         self.status = Preprocessor.IN_SUB_BLOCK
         self.sub_block = self.main_prog._create_block()
diff --git a/python/paddle/fluid/optimizer.py b/python/paddle/fluid/optimizer.py
index e0e781a322b3eb68e3f54a66252a8d8b11a9a56f..fbd04f1eb461268ae98ca74c0bc46cc2717733cb 100644
--- a/python/paddle/fluid/optimizer.py
+++ b/python/paddle/fluid/optimizer.py
@@ -15,7 +15,7 @@
 from __future__ import print_function
 
 from collections import defaultdict
-from contextlib import contextmanager
+from .wrapped_decorator import signature_safe_contextmanager
 
 from paddle.fluid.framework import Program, Variable, name_scope, default_main_program
 from paddle.fluid.distribute_lookup_table import find_distributed_lookup_table
@@ -1610,7 +1610,7 @@ class ModelAverage(Optimizer):
             },
             stop_gradient=True)
 
-    @contextmanager
+    @signature_safe_contextmanager
     def apply(self, executor, need_restore=True):
         """Apply average values to parameters of current model.
         """
diff --git a/python/paddle/fluid/profiler.py b/python/paddle/fluid/profiler.py
index e05885f5f5bfc169828c1c6e723dffff098c3c2e..d5670dbc823c5d317f27f768c596ed2e009e71b6 100644
--- a/python/paddle/fluid/profiler.py
+++ b/python/paddle/fluid/profiler.py
@@ -15,7 +15,7 @@
 from __future__ import print_function
 
 from . import core
-from contextlib import contextmanager
+from .wrapped_decorator import signature_safe_contextmanager
 import os
 import six
 
@@ -35,7 +35,7 @@ NVPROF_CONFIG = [
 ]
 
 
-@contextmanager
+@signature_safe_contextmanager
 def cuda_profiler(output_file, output_mode=None, config=None):
     """The CUDA profiler.
     This fuctions is used to profile CUDA program by CUDA runtime application
@@ -217,7 +217,7 @@ def stop_profiler(sorted_key=None, profile_path='/tmp/profile'):
     core.disable_profiler(key_map[sorted_key], profile_path)
 
 
-@contextmanager
+@signature_safe_contextmanager
 def profiler(state, sorted_key=None, profile_path='/tmp/profile'):
     """The profiler interface.
     Different from cuda_profiler, this profiler can be used to profile both CPU
diff --git a/python/paddle/fluid/recordio_writer.py b/python/paddle/fluid/recordio_writer.py
index 076a942cdde5623faa570bf98f889e8145b60f8b..aa581f23a191639fdc026e7781897d5d996823a9 100644
--- a/python/paddle/fluid/recordio_writer.py
+++ b/python/paddle/fluid/recordio_writer.py
@@ -15,14 +15,14 @@
 from __future__ import print_function
 
 import os
-import contextlib
+from .wrapped_decorator import signature_safe_contextmanager
 from . import core
 __all__ = [
     'convert_reader_to_recordio_file', 'convert_reader_to_recordio_files'
 ]
 
 
-@contextlib.contextmanager
+@signature_safe_contextmanager
 def create_recordio_writer(filename,
                            compressor=core.RecordIOWriter.Compressor.Snappy,
                            max_num_records=1000):
diff --git a/python/paddle/fluid/unique_name.py b/python/paddle/fluid/unique_name.py
index b9957a699e597898bee75ce0e7283f7224293f0c..324257c13ff9828b341ca9affe8186387688c0bf 100644
--- a/python/paddle/fluid/unique_name.py
+++ b/python/paddle/fluid/unique_name.py
@@ -15,7 +15,7 @@
 from __future__ import print_function
 
 import collections
-import contextlib
+from .wrapped_decorator import signature_safe_contextmanager
 import six
 import sys
 
@@ -68,7 +68,7 @@ def switch(new_generator=None):
     return old
 
 
-@contextlib.contextmanager
+@signature_safe_contextmanager
 def guard(new_generator=None):
     if isinstance(new_generator, six.string_types):
         new_generator = UniqueNameGenerator(new_generator)
diff --git a/python/paddle/fluid/wrapped_decorator.py b/python/paddle/fluid/wrapped_decorator.py
new file mode 100644
index 0000000000000000000000000000000000000000..7e7dbff65611e947d1a11a0c33c6ecc27e6df636
--- /dev/null
+++ b/python/paddle/fluid/wrapped_decorator.py
@@ -0,0 +1,30 @@
+# Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+import decorator
+import contextlib
+
+__all__ = ['wrap_decorator', 'signature_safe_contextmanager']
+
+
+def wrap_decorator(decorator_func):
+    @decorator.decorator
+    def __impl__(func, *args, **kwargs):
+        wrapped_func = decorator_func(func)
+        return wrapped_func(*args, **kwargs)
+
+    return __impl__
+
+
+signature_safe_contextmanager = wrap_decorator(contextlib.contextmanager)
diff --git a/python/requirements.txt b/python/requirements.txt
index 03d5e33e88cd5f1138ca8f6a6e885d6acfbc260e..5a70f1aa3ffc0ab6d4d148eb5bc26981784f2d32 100644
--- a/python/requirements.txt
+++ b/python/requirements.txt
@@ -11,3 +11,4 @@ graphviz
 six
 funcsigs
 pyyaml
+decorator