[Cherry-Pick][Dy2Stat]Fix module loading OSError in multiprocess (#47302)

[Dy2Stat]Fix module loading OSError in multiprocess

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

@@ -53,7 +53,7 @@ ORIGI_INFO = "Original information of source code for ast node."
 
 class BaseNodeVisitor(gast.NodeVisitor):
     """
-    Implement customized NodeVisitor inherited from gast.NodeVisitor. 
+    Implement customized NodeVisitor inherited from gast.NodeVisitor.
     Ancestor nodes are traced to easily support more operations of currently
     visited node.
     """
@@ -100,10 +100,18 @@ RE_PYMODULE = r'[a-zA-Z0-9_]+\.'
 
 # FullArgSpec is valid from Python3. Defined a Namedtuple to
 # to make it available in Python2.
-FullArgSpec = collections.namedtuple('FullArgSpec', [
-    'args', 'varargs', 'varkw', 'defaults', 'kwonlyargs', 'kwonlydefaults',
-    'annotations'
-])
+FullArgSpec = collections.namedtuple(
+    'FullArgSpec',
+    [
+        'args',
+        'varargs',
+        'varkw',
+        'defaults',
+        'kwonlyargs',
+        'kwonlydefaults',
+        'annotations',
+    ],
+)
 
 
 def data_layer_not_check(name, shape, dtype='float32', lod_level=0):
@@ -113,7 +121,7 @@ def data_layer_not_check(name, shape, dtype='float32', lod_level=0):
     data can be various-length. This API is used in translating dygraph into
     static graph.
 
-     Note: 
+     Note:
         The default :code:`stop_gradient` attribute of the Tensor created by
         this API is true, which means the gradient won't be passed backward
         through the data Tensor. Set :code:`var.stop_gradient = False` If
@@ -124,7 +132,7 @@ def data_layer_not_check(name, shape, dtype='float32', lod_level=0):
            for more details.
        shape (list|tuple): List|Tuple of integers declaring the shape. You can
            set "None" at a dimension to indicate the dimension can be of any
-           size. For example, it is useful to set changeable batch size as "None" 
+           size. For example, it is useful to set changeable batch size as "None"
        dtype (np.dtype|VarType|str, optional): The type of the data. Supported
            dtype: bool, float16, float32, float64, int8, int16, int32, int64,
            uint8. Default: float32
@@ -141,20 +149,26 @@ def data_layer_not_check(name, shape, dtype='float32', lod_level=0):
         if shape[i] is None:
             shape[i] = -1
 
-    return helper.create_global_variable(name=name,
-                                         shape=shape,
-                                         dtype=dtype,
-                                         type=core.VarDesc.VarType.LOD_TENSOR,
-                                         stop_gradient=True,
-                                         lod_level=lod_level,
-                                         is_data=True,
-                                         need_check_feed=False)
+    return helper.create_global_variable(
+        name=name,
+        shape=shape,
+        dtype=dtype,
+        type=core.VarDesc.VarType.LOD_TENSOR,
+        stop_gradient=True,
+        lod_level=lod_level,
+        is_data=True,
+        need_check_feed=False,
+    )
 
 
 def create_undefined_variable():
-    from paddle.fluid.dygraph.dygraph_to_static.return_transformer import RETURN_NO_VALUE_MAGIC_NUM
-    var = data_layer_not_check(unique_name.generate("undefined_var"), [1],
-                               "float64")
+    from paddle.fluid.dygraph.dygraph_to_static.return_transformer import (
+        RETURN_NO_VALUE_MAGIC_NUM,
+    )
+
+    var = data_layer_not_check(
+        unique_name.generate("undefined_var"), [1], "float64"
+    )
     var.stop_gradient = False
     # the variable is created in block(0), we append assign in block(0) either.
     helper = LayerHelper('create_undefined_variable', **locals())
@@ -166,17 +180,16 @@ def create_undefined_variable():
 
 
 class UndefinedVar:
-
     def __init__(self, name):
         self.name = name
 
     def check(self):
         raise UnboundLocalError(
-            "local variable '{}' should be created before using it.")
+            "local variable '{}' should be created before using it."
+        )
 
 
 class Dygraph2StaticException(Exception):
-
     def __init__(self, message):
         super().__init__(message)
 
@@ -193,13 +206,15 @@ def getfullargspec(target):
         return inspect.getfullargspec(target)
     else:
         argspec = inspect.getargspec(target)
-        return FullArgSpec(args=argspec.args,
-                           varargs=argspec.varargs,
-                           varkw=argspec.keywords,
-                           defaults=argspec.defaults,
-                           kwonlyargs=[],
-                           kwonlydefaults=None,
-                           annotations={})
+        return FullArgSpec(
+            args=argspec.args,
+            varargs=argspec.varargs,
+            varkw=argspec.keywords,
+            defaults=argspec.defaults,
+            kwonlyargs=[],
+            kwonlydefaults=None,
+            annotations={},
+        )
 
 
 def parse_arg_and_kwargs(function):
@@ -216,7 +231,7 @@ def parse_arg_and_kwargs(function):
     default_values = fullargspec.defaults
     if default_values:
         assert len(default_values) <= len(arg_names)
-        default_kwarg_names = arg_names[-len(default_values):]
+        default_kwarg_names = arg_names[-len(default_values) :]
         default_kwargs = dict(zip(default_kwarg_names, default_values))
 
     return arg_names, default_kwargs
@@ -290,8 +305,9 @@ def is_api_in_module(node, module_prefix):
         from paddle.fluid.dygraph import to_variable
         from paddle import to_tensor
 
-        return eval("_is_api_in_module_helper({}, '{}')".format(
-            func_str, module_prefix))
+        return eval(
+            "_is_api_in_module_helper({}, '{}')".format(func_str, module_prefix)
+        )
     except Exception:
         return False
 
@@ -322,8 +338,10 @@ def is_numpy_api(node):
     func_str = astor.to_source(gast.gast_to_ast(node.func))
     try:
         import numpy as np
-        module_result = eval("_is_api_in_module_helper({}, '{}')".format(
-            func_str, "numpy"))
+
+        module_result = eval(
+            "_is_api_in_module_helper({}, '{}')".format(func_str, "numpy")
+        )
         # BUG: np.random.uniform doesn't have module and cannot be analyzed
         # TODO: find a better way
         if not module_result:
@@ -332,18 +350,19 @@ def is_numpy_api(node):
         return False
 
 
-def is_control_flow_to_transform(node,
-                                 static_analysis_visitor=None,
-                                 var_name_to_type=None):
+def is_control_flow_to_transform(
+    node, static_analysis_visitor=None, var_name_to_type=None
+):
     """
     Determines whether the node is a PaddlePaddle control flow statement which needs to
     be transformed into a static graph control flow statement.
     """
-    assert isinstance(node, gast.AST), \
-        "The type of input node must be gast.AST, but received %s." % type(node)
-    visitor = IsControlFlowVisitor(node,
-                                   static_analysis_visitor,
-                                   node_var_type_map=var_name_to_type)
+    assert isinstance(
+        node, gast.AST
+    ), "The type of input node must be gast.AST, but received %s." % type(node)
+    visitor = IsControlFlowVisitor(
+        node, static_analysis_visitor, node_var_type_map=var_name_to_type
+    )
     need_to_transform = visitor.transform()
     return need_to_transform
 
@@ -352,6 +371,7 @@ def _delete_keywords_from(node):
     assert isinstance(node, gast.Call)
     func_src = astor.to_source(gast.gast_to_ast(node.func))
     import paddle.fluid as fluid
+
     full_args = eval("inspect.getargspec({})".format(func_src))
     full_args_name = full_args[0]
 
@@ -365,7 +385,8 @@ def to_static_api(dygraph_class):
     else:
         raise NotImplementedError(
             "Paddle dygraph API {} cannot be converted "
-            "to static graph at present.".format(dygraph_class))
+            "to static graph at present.".format(dygraph_class)
+        )
 
 
 def _add_keywords_to(node, dygraph_api_name):
@@ -376,8 +397,10 @@ def _add_keywords_to(node, dygraph_api_name):
                 ast_keyword.arg = "size"
 
         node.keywords.append(
-            gast.keyword(arg="num_flatten_dims",
-                         value=gast.Constant(value=-1, kind=None)))
+            gast.keyword(
+                arg="num_flatten_dims", value=gast.Constant(value=-1, kind=None)
+            )
+        )
 
     if dygraph_api_name == "BilinearTensorProduct":
         for ast_keyword in node.keywords:
@@ -396,15 +419,17 @@ def to_static_ast(node, class_node):
     assert isinstance(class_node, gast.Call)
     static_api = to_static_api(class_node.func.attr)
 
-    node.func = gast.Attribute(attr=static_api,
-                               ctx=gast.Load(),
-                               value=gast.Attribute(attr='layers',
-                                                    ctx=gast.Load(),
-                                                    value=gast.Name(
-                                                        ctx=gast.Load(),
-                                                        id='fluid',
-                                                        annotation=None,
-                                                        type_comment=None)))
+    node.func = gast.Attribute(
+        attr=static_api,
+        ctx=gast.Load(),
+        value=gast.Attribute(
+            attr='layers',
+            ctx=gast.Load(),
+            value=gast.Name(
+                ctx=gast.Load(), id='fluid', annotation=None, type_comment=None
+            ),
+        ),
+    )
 
     update_args_of_func(node, class_node, 'forward')
 
@@ -427,10 +452,13 @@ def update_args_of_func(node, dygraph_node, method_name):
 
     class_src = astor.to_source(gast.gast_to_ast(dygraph_node.func))
     import paddle.fluid as fluid
+
     if method_name == "__init__" or eval(
-            "issubclass({}, fluid.dygraph.Layer)".format(class_src)):
-        full_args = eval("inspect.getargspec({}.{})".format(
-            class_src, method_name))
+        "issubclass({}, fluid.dygraph.Layer)".format(class_src)
+    ):
+        full_args = eval(
+            "inspect.getargspec({}.{})".format(class_src, method_name)
+        )
         full_args_name = [
             arg_name for arg_name in full_args[0] if arg_name != "self"
         ]
@@ -445,21 +473,24 @@ def update_args_of_func(node, dygraph_node, method_name):
 
 
 def create_api_shape_node(tensor_shape_node):
-    assert isinstance(tensor_shape_node,
-                      (gast.Name, gast.Attribute, gast.Subscript))
+    assert isinstance(
+        tensor_shape_node, (gast.Name, gast.Attribute, gast.Subscript)
+    )
 
     if isinstance(tensor_shape_node, gast.Name):
         api_shape_node = gast.Call(
             func=gast.parse('paddle.shape').body[0].value,
             args=[tensor_shape_node],
-            keywords=[])
+            keywords=[],
+        )
         return api_shape_node
 
     if isinstance(tensor_shape_node, gast.Attribute):
         api_shape_node = gast.Call(
             func=gast.parse('paddle.shape').body[0].value,
             args=[tensor_shape_node.value],
-            keywords=[])
+            keywords=[],
+        )
         return api_shape_node
 
     if isinstance(tensor_shape_node, gast.Subscript):
@@ -469,14 +500,15 @@ def create_api_shape_node(tensor_shape_node):
 
 
 def get_constant_variable_node(name, value, shape=[1], dtype='int64'):
-    return gast.parse('%s = paddle.full(%s, "%s", %s)' %
-                      (name, str(shape), str(value), dtype))
+    return gast.parse(
+        '%s = paddle.full(%s, "%s", %s)' % (name, str(shape), str(value), dtype)
+    )
 
 
 def get_attribute_full_name(node):
     assert isinstance(
-        node,
-        gast.Attribute), "Input non-Attribute node to get attribute full name"
+        node, gast.Attribute
+    ), "Input non-Attribute node to get attribute full name"
     return astor.to_source(gast.gast_to_ast(node)).strip()
 
 
@@ -494,15 +526,15 @@ def generate_name_node(name_ids, ctx=gast.Load(), gen_tuple_if_single=False):
         name_ids = [name_ids]
     if not isinstance(name_ids, (list, tuple, set)):
         raise TypeError(
-            'name_ids must be list or tuple or set, but received %s' %
-            type(type(name_ids)))
+            'name_ids must be list or tuple or set, but received %s'
+            % type(type(name_ids))
+        )
 
     def create_node_for_name(name):
         if '.' not in name:
-            return gast.Name(id=name,
-                             ctx=ctx,
-                             annotation=None,
-                             type_comment=None)
+            return gast.Name(
+                id=name, ctx=ctx, annotation=None, type_comment=None
+            )
         return gast.parse(name).body[0].value
 
     gast_names = [create_node_for_name(name_id) for name_id in name_ids]
@@ -524,12 +556,14 @@ def create_funcDef_node(nodes, name, input_args, return_name_ids):
         nodes.append(gast.Return(value=generate_name_node(return_name_ids)))
     else:
         nodes.append(gast.Return(value=None))
-    func_def_node = gast.FunctionDef(name=name,
-                                     args=input_args,
-                                     body=nodes,
-                                     decorator_list=[],
-                                     returns=None,
-                                     type_comment=None)
+    func_def_node = gast.FunctionDef(
+        name=name,
+        args=input_args,
+        body=nodes,
+        decorator_list=[],
+        returns=None,
+        type_comment=None,
+    )
     return func_def_node
 
 
@@ -554,8 +588,9 @@ def get_temp_dir():
     """
     Return @to_static temp directory.
     """
-    dir_name = "paddle/to_static_tmp"
+    dir_name = "paddle/to_static_tmp/{pid}".format(pid=os.getpid())
     temp_dir = os.path.join(os.path.expanduser('~/.cache'), dir_name)
+
     is_windows = sys.platform.startswith('win')
     if is_windows:
         temp_dir = os.path.normpath(temp_dir)
@@ -589,12 +624,14 @@ def ast_to_func(ast_root, dyfunc, delete_on_exit=True):
     source = ast_to_source_code(ast_root)
     source = _inject_import_statements() + source
     temp_dir = get_temp_dir()
-    f = tempfile.NamedTemporaryFile(mode='w',
-                                    prefix=func_prefix(dyfunc),
-                                    suffix='.py',
-                                    delete=False,
-                                    dir=temp_dir,
-                                    encoding='utf-8')
+    f = tempfile.NamedTemporaryFile(
+        mode='w',
+        prefix=func_prefix(dyfunc),
+        suffix='.py',
+        delete=False,
+        dir=temp_dir,
+        encoding='utf-8',
+    )
     with f:
         module_name = os.path.basename(f.name[:-3])
         f.write(source)
@@ -616,8 +653,9 @@ def ast_to_func(ast_root, dyfunc, delete_on_exit=True):
         callable_func = getattr(module, func_name)
     else:
         raise ValueError(
-            'Function: %s doesn\'t exist in the Module transformed from AST.' %
-            func_name)
+            'Function: %s doesn\'t exist in the Module transformed from AST.'
+            % func_name
+        )
     # After transform dygraph function into callable_func saved in tmp file,
     # it lost the global variables from imported statements or defined in source file.
     # Recovers the necessary variables by `__globals__`.
@@ -628,10 +666,14 @@ def ast_to_func(ast_root, dyfunc, delete_on_exit=True):
 
 def _inject_import_statements():
     import_statements = [
-        "import paddle", "from paddle import Tensor",
-        "import paddle.fluid as fluid", "import paddle.jit.dy2static as _jst",
-        "from typing import *", "import numpy as np", "import warnings",
-        "warnings.filterwarnings('ignore', category=DeprecationWarning)"
+        "import paddle",
+        "from paddle import Tensor",
+        "import paddle.fluid as fluid",
+        "import paddle.jit.dy2static as _jst",
+        "from typing import *",
+        "import numpy as np",
+        "import warnings",
+        "warnings.filterwarnings('ignore', category=DeprecationWarning)",
     ]
     return '\n'.join(import_statements) + '\n'
 
@@ -654,8 +696,10 @@ def func_to_source_code(function, dedent=True):
     """
     if not (inspect.isfunction(function) or inspect.ismethod(function)):
         raise TypeError(
-            "The type of 'function' should be a function or method, but received {}."
-            .format(type(function).__name__))
+            "The type of 'function' should be a function or method, but received {}.".format(
+                type(function).__name__
+            )
+        )
     source_code_list, _ = inspect.getsourcelines(function)
     # Replace comments with blank lines so that error messages are not misplaced
     source_code_list = [
@@ -675,8 +719,9 @@ def ast_to_source_code(ast_node):
     """
     if not isinstance(ast_node, (gast.AST, ast.AST)):
         raise TypeError(
-            "Type of ast_root should be gast.AST or ast.AST, but received %s." %
-            type(ast_node))
+            "Type of ast_root should be gast.AST or ast.AST, but received %s."
+            % type(ast_node)
+        )
     if isinstance(ast_node, gast.AST):
         ast_node = gast.gast_to_ast(ast_node)
 
@@ -692,8 +737,17 @@ def is_candidate_node(node):
     """
     Nodes with specified type will be dependent on tensor.
     """
-    is_compare_node = isinstance(node, (gast.Compare, gast.BoolOp, gast.UnaryOp,
-                                        gast.For, gast.If, gast.While))
+    is_compare_node = isinstance(
+        node,
+        (
+            gast.Compare,
+            gast.BoolOp,
+            gast.UnaryOp,
+            gast.For,
+            gast.If,
+            gast.While,
+        ),
+    )
     # TODO(Aurelius84): `.numpy()` may be an customized function,
     # and should consider a more elegant way to solve this problem.
     has_numpy_attr = ".numpy()" in ast_to_source_code(node)
@@ -709,9 +763,9 @@ def compare_with_none(node):
             # node.comparators is a list.
             if isinstance(child, list):
                 child = child[0]
-            if (isinstance(child, gast.Constant)
-                    and child.value is None) or (isinstance(child, gast.Name)
-                                                 and child.id == 'None'):
+            if (isinstance(child, gast.Constant) and child.value is None) or (
+                isinstance(child, gast.Name) and child.id == 'None'
+            ):
                 return True
     return False
 
@@ -746,20 +800,22 @@ class IsControlFlowVisitor(gast.NodeVisitor):
              because reshape_op may be called before this statement.
     """
 
-    def __init__(self,
-                 ast_node,
-                 static_analysis_visitor=None,
-                 node_var_type_map=None):
+    def __init__(
+        self, ast_node, static_analysis_visitor=None, node_var_type_map=None
+    ):
         assert isinstance(
             ast_node, gast.AST
         ), "Type of input node should be gast.AST, but received %s." % type(
-            ast_node)
+            ast_node
+        )
         self.ast_root = ast_node
         if static_analysis_visitor is None:
             from .static_analysis import StaticAnalysisVisitor
+
             static_analysis_visitor = StaticAnalysisVisitor(ast_node)
         self.static_analysis_visitor = static_analysis_visitor
-        self.node_to_wrapper_map = self.static_analysis_visitor.get_node_to_wrapper_map(
+        self.node_to_wrapper_map = (
+            self.static_analysis_visitor.get_node_to_wrapper_map()
         )
         self.node_var_type_map = node_var_type_map
 
@@ -788,7 +844,10 @@ class IsControlFlowVisitor(gast.NodeVisitor):
         if isinstance(node.iter, gast.Call):
             # for in range(var[0]|var.numpy()[0]) or for in enumerate(var|var.numpy())
             if isinstance(node.iter.func, gast.Name):
-                if node.iter.func.id == "range" or node.iter.func.id == "enumerate":
+                if (
+                    node.iter.func.id == "range"
+                    or node.iter.func.id == "enumerate"
+                ):
                     for arg in node.iter.args:
                         self.visit(arg)
                 else:
@@ -887,7 +946,9 @@ class IsControlFlowVisitor(gast.NodeVisitor):
         return node
 
     def _is_node_with_tensor(self, node, name_id):
-        from paddle.fluid.dygraph.dygraph_to_static.static_analysis import NodeVarType
+        from paddle.fluid.dygraph.dygraph_to_static.static_analysis import (
+            NodeVarType,
+        )
 
         # Look up the node_var_type_map by name_id.
         if self.node_var_type_map:
@@ -917,7 +978,7 @@ def unwrap(func):
         return hasattr(f, '__wrapped__')
 
     unwrapped_f = func
-    while (_is_wrapped(unwrapped_f)):
+    while _is_wrapped(unwrapped_f):
         unwrapped_f = unwrapped_f.__wrapped__
 
     return unwrapped_f
@@ -941,10 +1002,12 @@ def input_specs_compatible(src_input_specs, desired_input_specs):
             if spec not in desired_input_specs:
                 return False
     else:
-        for (src_spec, desired_spec) in zip(src_input_specs,
-                                            desired_input_specs):
+        for (src_spec, desired_spec) in zip(
+            src_input_specs, desired_input_specs
+        ):
             if isinstance(src_spec, paddle.static.InputSpec) or isinstance(
-                    desired_spec, paddle.static.InputSpec):
+                desired_spec, paddle.static.InputSpec
+            ):
                 if not _compatible_tensor_spec(src_spec, desired_spec):
                     return False
             else:
@@ -1029,15 +1092,14 @@ def slice_is_num(slice_node):
 
 
 class NameScope:
-
     def __init__(self):
-        """ 
-            A NameScope is a object which manager all the variable names. 
-            only FunctionDef and Controlflow node will have a namescope property.
+        """
+        A NameScope is a object which manager all the variable names.
+        only FunctionDef and Controlflow node will have a namescope property.
 
-            type can be "function" and "controlflow"
+        type can be "function" and "controlflow"
 
-            we don't analyze the read only variable because they don't affect the analysis.
+        we don't analyze the read only variable because they don't affect the analysis.
         """
         self.globals = set()
         self.nonlocals = set()
@@ -1053,8 +1115,8 @@ class NameScope:
         self.father = father
 
     def existed_vars(self):
-        """ vars existing in current scope. 
-            they must not contain qualified names.
+        """vars existing in current scope.
+        they must not contain qualified names.
         """
         local_vars = self.w_vars - self.globals - self.nonlocals - self.args
         return set(filter(lambda x: '.' not in x, local_vars))
@@ -1067,9 +1129,9 @@ class NameScope:
         return self.w_vars
 
     def variadic_length_vars(self):
-        """ 
+        """
         At present, we do not support global append, such as
-        
+
         import numpy as np
         a = []
         def func():
@@ -1083,33 +1145,38 @@ class NameScope:
                     f"Find variable `{var}` defined in global scope"
                     f" and call `{var}.append() or {var}.pop()`"
                     f", which will be ignored and never be transfered into"
-                    f" tensor array.")
+                    f" tensor array."
+                )
             else:
                 non_global_push_pop_names.append(var)
         return set(non_global_push_pop_names)
 
     def control_flow_vars(self):
         valid_names = self.w_vars
-        tmp = self.father.global_vars & valid_names,
+        tmp = (self.father.global_vars & valid_names,)
         return {"global": tmp, "nonlocal": self.w_vars - tmp}
 
     def _is_simple_name(self, name):
-        if '.' in name or '[' in name: return False
+        if '.' in name or '[' in name:
+            return False
         return True
 
     def is_global_var(self, name):
-        """ 
+        """
         Return whether the name is a var created in global scope.
-        Search from bottom to top. If it is not created or modified, 
+        Search from bottom to top. If it is not created or modified,
         it means global vars; otherwise, it means local vars.
         Only valid after FunctionNameLivenessAnalysis visitor.
         """
         assert self._is_simple_name(
-            name), "is_global_var accept a simple name, but get `{name}`."
+            name
+        ), "is_global_var accept a simple name, but get `{name}`."
         ancestor = self
         while ancestor is not None:
-            if name in ancestor.globals: return True
-            if name in (ancestor.nonlocals | ancestor.w_vars): return False
+            if name in ancestor.globals:
+                return True
+            if name in (ancestor.nonlocals | ancestor.w_vars):
+                return False
             ancestor = ancestor.father
         return True
 
@@ -1125,46 +1192,46 @@ class NameScope:
 
 
 class FunctionNameLivenessAnalysis(gast.NodeVisitor):
-    """ analyze the liveness of a function.
-
-        every variables stored in this scope will be collected,
-        in addition with global/nonlocal information and 
-        push_pop information.
-
-        1. global variable is stored in node.var_globals.
-        2. nonlocal variable is stored in node.var_nonlocals.
-        3. arguments is stored in node.var_args.
-        4. if a variable's push and pop attribute is called, 
-           it will be collected in push_pop_vars. They are
-           used for transformation to tensor_array.
-           NOTE: push_pop_vars **may not** in w_vars. 
-           a.push(0) don't modify the variable a, but the content
-           of a.
-
-        For example:
-
-        def func(*args, **kargs):
-            a = 12
-            global i,j
-            nonlocal x,y
-            print(a)
-            i = k
-            b = []
-            c = [1,2,3]
-            for m in range(10):
-                q = 12
-                b.push(1)
-                c.pop()
-        
-        After this visitor we have: 
-        # node is the FunctionDef node with name: "func"
-        node.pd_scope = NameScope(
-            globals = ['i', 'j'],
-            nonlocals = ['x', 'y'],
-            args = ['args', 'kargs'], 
-            wr_vars = ['a', 'i', 'q', 'm', 'c', 'b']
-            push_pop_vars = ['b', 'c']
-        )
+    """analyze the liveness of a function.
+
+    every variables stored in this scope will be collected,
+    in addition with global/nonlocal information and
+    push_pop information.
+
+    1. global variable is stored in node.var_globals.
+    2. nonlocal variable is stored in node.var_nonlocals.
+    3. arguments is stored in node.var_args.
+    4. if a variable's push and pop attribute is called,
+       it will be collected in push_pop_vars. They are
+       used for transformation to tensor_array.
+       NOTE: push_pop_vars **may not** in w_vars.
+       a.push(0) don't modify the variable a, but the content
+       of a.
+
+    For example:
+
+    def func(*args, **kargs):
+        a = 12
+        global i,j
+        nonlocal x,y
+        print(a)
+        i = k
+        b = []
+        c = [1,2,3]
+        for m in range(10):
+            q = 12
+            b.push(1)
+            c.pop()
+
+    After this visitor we have:
+    # node is the FunctionDef node with name: "func"
+    node.pd_scope = NameScope(
+        globals = ['i', 'j'],
+        nonlocals = ['x', 'y'],
+        args = ['args', 'kargs'],
+        wr_vars = ['a', 'i', 'q', 'm', 'c', 'b']
+        push_pop_vars = ['b', 'c']
+    )
     """
 
     def __init__(self, root_node):
@@ -1184,25 +1251,26 @@ class FunctionNameLivenessAnalysis(gast.NodeVisitor):
         return self._get_name_scope(self.scope_node_stack[-1])
 
     def _father_name_scope(self):
-        if len(self.scope_node_stack) == 1: return None
+        if len(self.scope_node_stack) == 1:
+            return None
         return self._get_name_scope(self.scope_node_stack[-2])
 
     def _nearest_function_scope(self):
-        if len(self.scope_node_stack) == 1: return None
+        if len(self.scope_node_stack) == 1:
+            return None
         for node in self.scope_node_stack[-2::-1]:
             if isinstance(node, gast.FunctionDef):
                 return self._get_name_scope(node)
 
     def visit_ListComp(self, node):
-        """ [ i for i in range(10) ]
-            In this case, `i` will not created in FunctionScope. 
-            We don't collect `i` by not calling generic_visit.
+        """[ i for i in range(10) ]
+        In this case, `i` will not created in FunctionScope.
+        We don't collect `i` by not calling generic_visit.
         """
         pass
 
     def visit_DictComp(self, node):
-        """ the same as ListComp.
-        """
+        """the same as ListComp."""
         pass
 
     def visit_Name(self, node):
@@ -1212,62 +1280,86 @@ class FunctionNameLivenessAnalysis(gast.NodeVisitor):
             self._current_name_scope().w_vars.add(node.id)
 
     def visit_FunctionDef(self, node):
-
         def pre_func():
             self._current_name_scope().args |= set(
-                self._get_argument_names(node))
+                self._get_argument_names(node)
+            )
 
         def post_func():
-            """ NOTE: why we need merge w_vars and push_pop_vars here ? 
-                because we do ifelse_transformer after loop_transformer. Loops will changed into functioons. but we know this function will be called in if. so we add w_vars to father function scope.
+            """NOTE: why we need merge w_vars and push_pop_vars here ?
+            because we do ifelse_transformer after loop_transformer. Loops will changed into functioons. but we know this function will be called in if. so we add w_vars to father function scope.
             """
-            from paddle.fluid.dygraph.dygraph_to_static.loop_transformer import WHILE_CONDITION_PREFIX, WHILE_BODY_PREFIX, FOR_CONDITION_PREFIX, FOR_BODY_PREFIX
-            from paddle.fluid.dygraph.dygraph_to_static.ifelse_transformer import TRUE_FUNC_PREFIX, FALSE_FUNC_PREFIX
+            from paddle.fluid.dygraph.dygraph_to_static.loop_transformer import (
+                WHILE_CONDITION_PREFIX,
+                WHILE_BODY_PREFIX,
+                FOR_CONDITION_PREFIX,
+                FOR_BODY_PREFIX,
+            )
+            from paddle.fluid.dygraph.dygraph_to_static.ifelse_transformer import (
+                TRUE_FUNC_PREFIX,
+                FALSE_FUNC_PREFIX,
+            )
+
             control_flow_function_def = [
-                WHILE_BODY_PREFIX, WHILE_BODY_PREFIX, FOR_CONDITION_PREFIX,
-                FOR_BODY_PREFIX, TRUE_FUNC_PREFIX, FALSE_FUNC_PREFIX
+                WHILE_BODY_PREFIX,
+                WHILE_BODY_PREFIX,
+                FOR_CONDITION_PREFIX,
+                FOR_BODY_PREFIX,
+                TRUE_FUNC_PREFIX,
+                FALSE_FUNC_PREFIX,
             ]
 
             def is_control_flow_def_node():
                 for prefix in control_flow_function_def:
-                    if node.name.startswith(prefix): return True
+                    if node.name.startswith(prefix):
+                        return True
                 return False
 
             if self._father_name_scope() and is_control_flow_def_node():
-                self._father_name_scope().w_vars |= self._current_name_scope(
-                ).w_vars
-                self._father_name_scope(
-                ).push_pop_vars |= self._current_name_scope().push_pop_vars
+                self._father_name_scope().w_vars |= (
+                    self._current_name_scope().w_vars
+                )
+                self._father_name_scope().push_pop_vars |= (
+                    self._current_name_scope().push_pop_vars
+                )
 
         self._visit_scope_node(node, pre_func, post_func)
 
     def _visit_scope_node(self, node, pre_func, post_func):
-        """ scope node main visit logic.
-            pre_func and post_func is callbacks
+        """scope node main visit logic.
+        pre_func and post_func is callbacks
         """
         self._reset_name_scope(node)
         self.scope_node_stack.append(node)
         self._current_name_scope().set_father(self._nearest_function_scope())
-        if pre_func: pre_func()
+        if pre_func:
+            pre_func()
         self.generic_visit(node)
-        if post_func: post_func()
+        if post_func:
+            post_func()
         self.scope_node_stack.pop()
 
     def _visit_controlflow_node(self, node):
-
         def post_func():
             self._father_name_scope().merge_from(self._current_name_scope())
             self._nearest_function_scope().merge_from(
-                self._current_name_scope())
-            self._current_name_scope().created = self._nearest_function_scope(
-            ).existed_vars() - node.before_created
+                self._current_name_scope()
+            )
+            self._current_name_scope().created = (
+                self._nearest_function_scope().existed_vars()
+                - node.before_created
+            )
             # gather created vars into father and used in CreateUndefinedVarTransform
-            self._nearest_function_scope().created |= self._current_name_scope(
-            ).created
+            self._nearest_function_scope().created |= (
+                self._current_name_scope().created
+            )
 
         def pre_func():
-            setattr(node, "before_created",
-                    self._nearest_function_scope().existed_vars())
+            setattr(
+                node,
+                "before_created",
+                self._nearest_function_scope().existed_vars(),
+            )
 
         self._visit_scope_node(node, pre_func, post_func)
 
@@ -1305,12 +1397,13 @@ class FunctionNameLivenessAnalysis(gast.NodeVisitor):
         self._current_name_scope().push_pop_vars.add(name)
 
     def _get_argument_names(self, node):
-        """ get all arguments name in the functiondef node.
-            this node is local to the function and shouldn't 
-            be created.
+        """get all arguments name in the functiondef node.
+        this node is local to the function and shouldn't
+        be created.
         """
         assert isinstance(
-            node, gast.FunctionDef), "Input node is not function define node"
+            node, gast.FunctionDef
+        ), "Input node is not function define node"
         names = [a for a in node.args.args]
         names.append(node.args.vararg)
         names.append(node.args.kwarg)
@@ -1331,7 +1424,9 @@ def create_get_args_node(names):
         func_def = """
         def {func_name}():
             return
-        """.format(func_name=unique_name.generate(GET_ARGS_FUNC_PREFIX))
+        """.format(
+            func_name=unique_name.generate(GET_ARGS_FUNC_PREFIX)
+        )
         return gast.parse(textwrap.dedent(func_def)).body[0]
 
     assert isinstance(names, (list, tuple))
@@ -1350,7 +1445,8 @@ def create_get_args_node(names):
     func_def = template.format(
         func_name=unique_name.generate(GET_ARGS_FUNC_PREFIX),
         nonlocal_vars=nonlocal_vars,
-        vars=",".join(names))
+        vars=",".join(names),
+    )
     return gast.parse(textwrap.dedent(func_def)).body[0]
 
 
@@ -1367,8 +1463,9 @@ def create_set_args_node(names):
         func_def = """
         def {func_name}({args}):
             pass
-        """.format(func_name=unique_name.generate(SET_ARGS_FUNC_PREFIX),
-                   args=ARGS_NAME)
+        """.format(
+            func_name=unique_name.generate(SET_ARGS_FUNC_PREFIX), args=ARGS_NAME
+        )
         return gast.parse(textwrap.dedent(func_def)).body[0]
 
     assert isinstance(names, (list, tuple))
@@ -1388,7 +1485,8 @@ def create_set_args_node(names):
         func_name=unique_name.generate(SET_ARGS_FUNC_PREFIX),
         args=ARGS_NAME,
         nonlocal_vars=nonlocal_vars,
-        vars=",".join(names))
+        vars=",".join(names),
+    )
     return gast.parse(textwrap.dedent(func_def)).body[0]
 
 
@@ -1398,8 +1496,8 @@ def create_nonlocal_stmt_nodes(names):
     mapped = list(filter(lambda n: '.' not in n, names))
     mapped = list(filter(lambda n: '[' not in n, mapped))
     names = sorted(
-        mapped,
-        key=mapped.index)  # to keep the order, we can't use set() to unique
+        mapped, key=mapped.index
+    )  # to keep the order, we can't use set() to unique
     if not names:
         return []
     func_code = "nonlocal {}".format(','.join(names))
@@ -1407,10 +1505,10 @@ def create_nonlocal_stmt_nodes(names):
 
 
 class GetterSetterHelper:
-    """ we have two classes of names in setter and getter function: 
-        w_vars(loop_vars) + push_pop_vars
-        To simplify the setter logic in convert_while and convert_cond,
-        we extract the helper class here.
+    """we have two classes of names in setter and getter function:
+    w_vars(loop_vars) + push_pop_vars
+    To simplify the setter logic in convert_while and convert_cond,
+    we extract the helper class here.
     """
 
     def __init__(self, getter_func, setter_func, *name_lists):
@@ -1426,22 +1524,33 @@ class GetterSetterHelper:
         return self._union
 
     def get(self, names):
-        if names is None: names = []
+        if names is None:
+            names = []
         vars = self.getter()
-        if vars is None: return tuple()
+        if vars is None:
+            return tuple()
         for n in names:
-            assert n in self.name2id, "the name `{}` not in name union set`{}`.".format(
-                n, self.name2id.keys())
+            assert (
+                n in self.name2id
+            ), "the name `{}` not in name union set`{}`.".format(
+                n, self.name2id.keys()
+            )
         return tuple(map(lambda n: vars[self.name2id[n]], names))
 
     def set(self, names, values):
-        if names is None: names = []
-        if values is None: values = []
+        if names is None:
+            names = []
+        if values is None:
+            values = []
         vars = self.getter()
-        if vars is None: return
+        if vars is None:
+            return
         for n in names:
-            assert n in self.name2id, "the name `{}` not in name union set`{}`.".format(
-                n, self.name2id.keys())
+            assert (
+                n in self.name2id
+            ), "the name `{}` not in name union set`{}`.".format(
+                n, self.name2id.keys()
+            )
         vars = list(vars)
         indices = list(map(lambda n: self.name2id[n], names))
         for i, v in zip(indices, values):