def visit_Lambda(self, node):
op = issimpleoperator(node)
if op is not None:
if mangle('operator') not in self.global_declarations:
import_ = ast.Import(
[ast.alias('operator', mangle('operator'))])
self.imports.append(import_)
operator_module = MODULES['operator']
self.global_declarations[mangle('operator')] = operator_module
return ast.Attribute(
ast.Name(mangle('operator'), ast.Load(), None, None), op,
ast.Load())
self.generic_visit(node)
forged_name = "{0}_lambda{1}".format(self.prefix,
len(self.lambda_functions))
ii = self.gather(ImportedIds, node)
ii.difference_update(self.lambda_functions) # remove current lambdas
binded_args = [
ast.Name(iin, ast.Load(), None, None) for iin in sorted(ii)
]
node.args.args = (
[ast.Name(iin, ast.Param(), None, None)
for iin in sorted(ii)] + node.args.args)
for patternname, pattern in self.patterns.items():
if issamelambda(pattern, node):
proxy_call = ast.Name(patternname, ast.Load(), None, None)
break
else:
duc = ExtendedDefUseChains()
nodepattern = deepcopy(node)
duc.visit(ast.Module([ast.Expr(nodepattern)], []))
self.patterns[forged_name] = nodepattern, duc
forged_fdef = ast.FunctionDef(forged_name, copy(node.args),
[ast.Return(node.body)], [], None,
None)
metadata.add(forged_fdef, metadata.Local())
self.lambda_functions.append(forged_fdef)
self.global_declarations[forged_name] = forged_fdef
proxy_call = ast.Name(forged_name, ast.Load(), None, None)
if binded_args:
if MODULES['functools'] not in self.global_declarations.values():
import_ = ast.Import(
[ast.alias('functools', mangle('functools'))])
self.imports.append(import_)
functools_module = MODULES['functools']
self.global_declarations[mangle(
'functools')] = functools_module
return ast.Call(
ast.Attribute(
ast.Name(mangle('functools'), ast.Load(), None, None),
"partial", ast.Load()), [proxy_call] + binded_args, [])
else:
return proxy_call
def insert_import_module_with_postion(node,
mdl_name="paddle",
pos=IMPROT_PADDLE_POS):
"""insert import module with pos number
Args:
node (gast)
mdl_name (str, optional): Defaults to "paddle"
pos (int, optional): Defaults to IMPROT_PADDLE_POS.
Returns:
node (gast)
"""
assert isinstance(node, gast.gast.Module)
stat = -1
for b in node.body:
if not isinstance(b, gast.gast.Import):
continue
for name in b.names:
if "paddle" != name.name:
continue
else:
stat = 0
break
if stat != 0:
def_alias = gast.alias(name=mdl_name, asname=None)
new_import_node = gast.gast.Import(names=[def_alias])
print("insert paddle with position: %s" % (pos + 1))
node.body.insert(pos + 1, new_import_node)
return node
def visit_Lambda(self, node):
if MODULES['functools'] not in self.global_declarations.values():
import_ = ast.Import([ast.alias('functools', mangle('functools'))])
self.imports.append(import_)
functools_module = MODULES['functools']
self.global_declarations[mangle('functools')] = functools_module
self.generic_visit(node)
forged_name = "{0}_lambda{1}".format(self.prefix,
len(self.lambda_functions))
ii = self.passmanager.gather(ImportedIds, node, self.ctx)
ii.difference_update(self.lambda_functions) # remove current lambdas
binded_args = [ast.Name(iin, ast.Load(), None) for iin in sorted(ii)]
node.args.args = (
[ast.Name(iin, ast.Param(), None)
for iin in sorted(ii)] + node.args.args)
forged_fdef = ast.FunctionDef(forged_name, copy(node.args),
[ast.Return(node.body)], [], None)
self.lambda_functions.append(forged_fdef)
self.global_declarations[forged_name] = forged_fdef
proxy_call = ast.Name(forged_name, ast.Load(), None)
if binded_args:
return ast.Call(
ast.Attribute(ast.Name(mangle('functools'), ast.Load(), None),
"partial", ast.Load()),
[proxy_call] + binded_args, [])
else:
return proxy_call
def visit_ImportFrom(self, node):
for alias in node.names:
if alias.name == "*":
self.update = True
node.names.pop()
node.names.extend(ast.alias(fname, None) for fname in MODULES[node.module])
return node
def visit_Module(self, node):
self.need_import = False
self.generic_visit(node)
if self.need_import:
importIt = ast.Import(names=[ast.alias(name='numpy', asname=None)])
node.body.insert(0, importIt)
return node
def visit_Module(self, node):
"""
When we normalize call, we need to add correct import for method
to function transformation.
a.max()
for numpy array will become:
numpy.max(a)
so we have to import numpy.
"""
self.skip_functions = True
self.generic_visit(node)
self.skip_functions = False
self.generic_visit(node)
new_imports = self.to_import - self.globals
imports = [
ast.Import(names=[ast.alias(name=mod[17:], asname=mod)])
for mod in new_imports
]
node.body = imports + node.body
self.update |= bool(imports)
return node
def visit_Module(self, node):
self.need_import = False
self.generic_visit(node)
if self.need_import:
importIt = ast.Import(names=[ast.alias(name='numpy', asname=None)])
node.body.insert(0, importIt)
return node
def visit_FunctionDef(self, node):
self.update = True
if MODULES['functools'] not in self.global_declarations.values():
import_ = ast.Import([ast.alias('functools', mangle('functools'))])
self.ctx.module.body.insert(0, import_)
functools_module = MODULES['functools']
self.global_declarations[mangle('functools')] = functools_module
self.ctx.module.body.append(node)
former_name = node.name
seed = 0
new_name = "pythran_{}{}"
while new_name.format(former_name, seed) in self.identifiers:
seed += 1
new_name = new_name.format(former_name, seed)
self.identifiers.add(new_name)
ii = self.gather(ImportedIds, node)
binded_args = [
ast.Name(iin, ast.Load(), None, None) for iin in sorted(ii)
]
node.args.args = (
[ast.Name(iin, ast.Param(), None, None)
for iin in sorted(ii)] + node.args.args)
metadata.add(node, metadata.Local())
class Renamer(ast.NodeTransformer):
def visit_Call(self, node):
self.generic_visit(node)
if (isinstance(node.func, ast.Name)
and node.func.id == former_name):
node.func.id = new_name
node.args = ([
ast.Name(iin, ast.Load(), None, None)
for iin in sorted(ii)
] + node.args)
return node
Renamer().visit(node)
node.name = new_name
self.global_declarations[node.name] = node
proxy_call = ast.Name(new_name, ast.Load(), None, None)
new_node = ast.Assign([ast.Name(former_name, ast.Store(), None, None)],
ast.Call(
ast.Attribute(
ast.Name(mangle('functools'), ast.Load(),
None, None), "partial",
ast.Load()),
[proxy_call] + binded_args,
[],
))
self.generic_visit(node)
return new_node
def visit_Lambda(self, node):
if MODULES["functools"] not in self.global_declarations.values():
import_ = ast.Import([ast.alias("functools", None)])
self.imports.append(import_)
self.global_declarations["functools"] = MODULES["functools"]
self.generic_visit(node)
forged_name = "{0}_lambda{1}".format(self.prefix, len(self.lambda_functions))
ii = self.passmanager.gather(ImportedIds, node, self.ctx)
ii.difference_update(self.lambda_functions) # remove current lambdas
binded_args = [ast.Name(iin, ast.Load(), None) for iin in sorted(ii)]
node.args.args = [ast.Name(iin, ast.Param(), None) for iin in sorted(ii)] + node.args.args
forged_fdef = ast.FunctionDef(forged_name, copy(node.args), [ast.Return(node.body)], [], None)
self.lambda_functions.append(forged_fdef)
self.global_declarations[forged_name] = forged_fdef
proxy_call = ast.Name(forged_name, ast.Load(), None)
if binded_args:
return ast.Call(
ast.Attribute(ast.Name("functools", ast.Load(), None), "partial", ast.Load()),
[proxy_call] + binded_args,
[],
)
else:
return proxy_call
def visit_FunctionDef(self, node):
self.update = True
if MODULES['functools'] not in self.global_declarations.values():
import_ = ast.Import([ast.alias('functools', mangle('functools'))])
self.ctx.module.body.insert(0, import_)
functools_module = MODULES['functools']
self.global_declarations[mangle('functools')] = functools_module
self.ctx.module.body.append(node)
former_name = node.name
seed = 0
new_name = "pythran_{}{}"
while new_name.format(former_name, seed) in self.identifiers:
seed += 1
new_name = new_name.format(former_name, seed)
self.identifiers.add(new_name)
ii = self.passmanager.gather(ImportedIds, node, self.ctx)
binded_args = [ast.Name(iin, ast.Load(), None) for iin in sorted(ii)]
node.args.args = ([ast.Name(iin, ast.Param(), None)
for iin in sorted(ii)] +
node.args.args)
class Renamer(ast.NodeTransformer):
def visit_Call(self, node):
self.generic_visit(node)
if (isinstance(node.func, ast.Name) and
node.func.id == former_name):
node.func.id = new_name
node.args = (
[ast.Name(iin, ast.Load(), None)
for iin in sorted(ii)] +
node.args
)
return node
Renamer().visit(node)
node.name = new_name
self.global_declarations[node.name] = node
proxy_call = ast.Name(new_name, ast.Load(), None)
new_node = ast.Assign(
[ast.Name(former_name, ast.Store(), None)],
ast.Call(
ast.Attribute(
ast.Name(mangle('functools'), ast.Load(), None),
"partial",
ast.Load()
),
[proxy_call] + binded_args,
[],
)
)
self.generic_visit(node)
return new_node
def visit_Module(self, node):
"""Add itertools import for imap, izip or ifilter iterator."""
self.generic_visit(node)
import_alias = ast.alias(name='itertools', asname=mangle('itertools'))
if self.use_itertools:
importIt = ast.Import(names=[import_alias])
node.body.insert(0, importIt)
return node
def visit_alias(self, node):
new_node = gast.alias(
self._visit(node.name),
self._visit(node.asname),
)
new_node.lineno = new_node.col_offset = None
new_node.end_lineno = new_node.end_col_offset = None
return new_node
def visit_ImportFrom(self, node):
for alias in node.names:
if alias.name == '*':
self.update = True
node.names.pop()
node.names.extend(
ast.alias(fname, None) for fname in MODULES[node.module])
return node
def visit_Module(self, node):
self.use_itertools = False
self.generic_visit(node)
if self.use_itertools:
importIt = ast.Import(
names=[ast.alias(name='itertools', asname=None)])
node.body.insert(0, importIt)
return node
def visit_Module(self, node):
self.use_itertools = False
self.generic_visit(node)
if self.use_itertools:
importIt = ast.Import(
names=[ast.alias(name='itertools', asname=None)])
node.body.insert(0, importIt)
return node
def call_function(self, _, func_name):
# There was a direct call to a function from this builtin. It means it
# was imported in the caller module in the form: from builtin import
# foo. We need to add such node to be imported
importFrom = ast.ImportFrom(
module=self.name, names=[ast.alias(name=func_name, asname=None)], level=0
) # FIXME what is level?
self.exported_functions[func_name] = importFrom
return func_name
def call_function(self, _, func_name):
# There was a direct call to a function from this builtin. It means it
# was imported in the caller module in the form: from builtin import
# foo. We need to add such node to be imported
importFrom = ast.ImportFrom(
module=self.name,
names=[ast.alias(name=func_name, asname=None)],
level=0) # FIXME what is level?
self.exported_functions[func_name] = importFrom
return func_name
def import_fct(mod):
if mod.is_main_module:
# don't need to import anything from the main module
return
for alias, module_name in mod.dependent_modules.items():
import_node = ast.Import(
names=[ast.alias(name=module_name, asname=alias)])
import_list.append(import_node)
# Here we import the function itself (FunctionDef node)
# In case of builtin module, it is an ImportFrom node.
import_list.extend(list(mod.exported_functions.values()))
def generate_ImportList(self):
"""List of imported functions to be added to the main module. """
import_list = []
for mod in self.modules.values():
if mod.is_main_module:
# don't need to import anything from the main module
continue
for alias, module_name in mod.dependent_modules.items():
import_node = ast.Import(names=[ast.alias(name=module_name, asname=alias)])
import_list.append(import_node)
# Here we import the function itself (FunctionDef node)
# In case of builtin module, it is an ImportFrom node.
import_list.extend(list(mod.exported_functions.values()))
return import_list
class CbrtPattern(Pattern):
# X ** .33333 => numpy.cbrt(X)
pattern = ast.BinOp(Placeholder(0), ast.Pow(), ast.Constant(1./3., None))
@staticmethod
def sub():
return ast.Call(
func=ast.Attribute(value=ast.Name(id=mangle('numpy'),
ctx=ast.Load(),
annotation=None,
type_comment=None),
attr="cbrt", ctx=ast.Load()),
args=[Placeholder(0)], keywords=[])
extra_imports = [ast.Import([ast.alias('numpy', mangle('numpy'))])]
def generate_ImportList(self):
"""List of imported functions to be added to the main module. """
import_list = []
for mod in self.modules.values():
if mod.is_main_module:
# don't need to import anything from the main module
continue
for alias, module_name in mod.dependent_modules.items():
import_node = ast.Import(
names=[ast.alias(name=module_name, asname=alias)])
import_list.append(import_node)
# Here we import the function itself (FunctionDef node)
# In case of builtin module, it is an ImportFrom node.
import_list.extend(list(mod.exported_functions.values()))
return import_list
def import_from_ast(module: str, names: List[str]) -> ImportFrom:
"""Convenience function for creating 'from module import names, ...' as a AST node
Args:
module: The name of the module to import from.
names: List of names of symbols to import from the module.
Returns:
The created ImportFrom AST node.
"""
return ImportFrom(
module=module,
names=[alias(name=n, asname=None) for n in names],
# 0 -> use absolute import
level=0,
)
def visit_Module(self, node):
"""
Visit the whole module and add all import at the top level.
>> import numpy.linalg
Becomes
>> import numpy
"""
node.body = [k for k in (self.visit(n) for n in node.body) if k]
imports = [ast.Import([ast.alias(i, None)]) for i in self.imports]
node.body = imports + node.body
ast.fix_missing_locations(node)
return node
def visit_Module(self, node):
"""
Visit the whole module and add all import at the top level.
>> import numpy.linalg
Becomes
>> import numpy
"""
node.body = [k for k in (self.visit(n) for n in node.body) if k]
imports = [ast.Import([ast.alias(i, mangle(i))]) for i in self.imports]
node.body = imports + node.body
ast.fix_missing_locations(node)
return node
def insert_import_module(node, mdl_name="paddle"):
assert isinstance(node, gast.gast.Module)
stat = -1
for b in node.body:
if not isinstance(b, gast.gast.Import):
continue
for name in b.names:
if "paddle" != name.name:
continue
else:
stat = 0
break
if stat != 0:
def_alias = gast.alias(name=mdl_name, asname=None)
new_import_node = gast.gast.Import(names=[def_alias])
node.body.insert(IMPROT_PADDLE_POS, new_import_node)
return node
def insert_import_module_with_postion(node, mdl_name="paddle", pos=IMPROT_PADDLE_POS):
assert isinstance(node, gast.gast.Module)
stat = -1
for b in node.body:
if not isinstance(b, gast.gast.Import):
continue
for name in b.names:
if "paddle" != name.name:
continue
else:
stat = 0
break
if stat != 0:
def_alias = gast.alias(name=mdl_name, asname=None)
new_import_node = gast.gast.Import(names=[def_alias])
print("insert paddle into %s"%(pos+1))
node.body.insert(pos+1, new_import_node)
return node
def visit_Module(self, node):
"""
When we normalize call, we need to add correct import for method
to function transformation.
a.max()
for numpy array will become:
numpy.max(a)
so we have to import numpy.
"""
self.generic_visit(node)
new_imports = self.to_import - self.globals
imports = [ast.Import(names=[ast.alias(name=mod, asname=None)])
for mod in new_imports]
node.body = imports + node.body
self.update |= bool(imports)
return node
def _wrap_into_dynamic_factory(nodes, entity_name, factory_factory_name,
factory_name, closure_vars, future_features):
"""Wraps an AST into the body of a dynamic factory.
This uses the dynamic factory (factory of factory) pattern to achieve the
following:
1. The inner factory, dynamically creates the entity represented by nodes.
2. The entity is parametrized by `ag__`, the internal AutoGraph module.
3. The outer factory creates the inner factory with a lexical scope
in which `closure_vars` are bound local variables. This in turn allows the
caller to control the exact closure (i.e. non-global free variables) for
the inner factory.
The AST is expected to define some symbol named by `entity_name`.
Args:
nodes: ast.AST
entity_name: Union[Text, ast.AST]
factory_factory_name: Text
factory_name: Text
closure_vars: Iterable[Text]
future_features: Iterable[Text], see EntityInfo.future_features.
Returns:
ast.AST
"""
if not isinstance(nodes, (list, tuple)):
nodes = (nodes,)
dummy_closure_defs = []
for var_name in closure_vars:
template = """
var_name = None
"""
dummy_closure_defs.extend(templates.replace(template, var_name=var_name))
if future_features:
future_imports = gast.ImportFrom(
module='__future__',
names=[gast.alias(name=name, asname=None) for name in future_features],
level=0)
else:
future_imports = []
# These dummy symbol declarations create local fariables in a function scope,
# so that the Python parser correctly marks them as free non-global variables
# upon load (that is, it creates cell slots for each symbol). Their values are
# not used, as the cells are swapped with the original entity's cells after
# the code has been loaded.
template = """
future_imports
def factory_factory_name():
dummy_closure_defs
def factory_name(ag__, ag_source_map__, ag_module__):
entity_defs
entity_name.ag_source_map = ag_source_map__
entity_name.ag_module = ag_module__
entity_name.autograph_info__ = {}
return entity_name
return factory_name
"""
return templates.replace(
template,
future_imports=future_imports,
factory_factory_name=factory_factory_name,
factory_name=factory_name,
dummy_closure_defs=dummy_closure_defs,
entity_defs=nodes,
entity_name=entity_name)
def class_to_graph(c, program_ctx):
"""Specialization of `entity_to_graph` for classes."""
# TODO(mdan): Revisit this altogether. Not sure we still need it.
converted_members = {}
method_filter = lambda m: tf_inspect.isfunction(m) or tf_inspect.ismethod(m
)
members = tf_inspect.getmembers(c, predicate=method_filter)
if not members:
raise ValueError('Cannot convert %s: it has no member methods.' % c)
class_namespace = {}
for _, m in members:
# Only convert the members that are directly defined by the class.
if inspect_utils.getdefiningclass(m, c) is not c:
continue
nodes, _, namespace = function_to_graph(
m,
program_ctx=program_ctx,
arg_values={},
arg_types={'self': (c.__name__, c)},
do_rename=False)
if class_namespace is None:
class_namespace = namespace
else:
class_namespace.update(namespace)
converted_members[m] = nodes[0]
namer = naming.Namer(class_namespace)
class_name = namer.class_name(c.__name__)
# Process any base classes: if the superclass if of a whitelisted type, an
# absolute import line is generated.
output_nodes = []
renames = {}
base_names = []
for base in c.__bases__:
if isinstance(object, base):
base_names.append('object')
continue
if is_whitelisted_for_graph(base):
alias = namer.new_symbol(base.__name__, ())
output_nodes.append(
gast.ImportFrom(
module=base.__module__,
names=[gast.alias(name=base.__name__, asname=alias)],
level=0))
else:
raise NotImplementedError(
'Conversion of classes that do not directly extend classes from'
' whitelisted modules is temporarily suspended. If this breaks'
' existing code please notify the AutoGraph team immediately.')
base_names.append(alias)
renames[qual_names.QN(base.__name__)] = qual_names.QN(alias)
# Generate the definition of the converted class.
bases = [gast.Name(n, gast.Load(), None) for n in base_names]
class_def = gast.ClassDef(class_name,
bases=bases,
keywords=[],
body=list(converted_members.values()),
decorator_list=[])
# Make a final pass to replace references to the class or its base classes.
# Most commonly, this occurs when making super().__init__() calls.
# TODO(mdan): Making direct references to superclass' superclass will fail.
class_def = qual_names.resolve(class_def)
renames[qual_names.QN(c.__name__)] = qual_names.QN(class_name)
class_def = ast_util.rename_symbols(class_def, renames)
output_nodes.append(class_def)
return output_nodes, class_name, class_namespace
def _wrap_into_factory(nodes, entity_name, inner_factory_name,
outer_factory_name, closure_vars, factory_args,
future_features):
"""Wraps an AST into the body of a factory with consistent lexical context.
The AST is expected to define some symbol with a name given by `entity_name`.
This mechanism ensures that the resulting transformed entity has lexical
scoping identical to that of the source entity, while allowing extra
parametrization.
Two nested factories achieve the following:
1. The inner factory dynamically creates the entity represented by `nodes`.
2. The inner factory is parametrized by a custom set of arguments.
3. The inner factory has a closure identical to that of the transformed
entity.
4. The inner factory has local variables named like `args`, which `nodes` may
use as additional parameters.
5. The inner factory returns the variables given by `entity_name`.
6. The outer factory is niladic.
7. The outer factory has no closure.
8. The outer factory creates the necessary lexical scope for the inner
factory, so that the loaded code has the given configuration for
closure/globals.
9. The outer factory returns the inner factory.
Roughly speaking, the following code is generated:
from __future__ import future_feature_1
from __future__ import future_feature_2
...
def outer_factory():
closure_var_1 = None
closure_var_2 = None
...
def inner_factory(arg_1, arg_2, ...):
<<nodes>>
return entity
return inner_factory
The lexical scoping is created using dummy symbol declarations which create
local fariables in the body of the outer factory, so that the Python parser
correctly marks them as free non-global variables upon load (that is, it
creates cell slots for each symbol. Thes symbols are initialized with None,
but their values are not expected to be used; instead, the caller is expected
to replace them with the cells of the source entity. For more details, see:
https://docs.python.org/3/reference/executionmodel.html#binding-of-names
Args:
nodes: Tuple[ast.AST], the source code to wrap.
entity_name: Union[Text, ast.AST], the name of the principal entity that
`nodes` define.
inner_factory_name: Text, the name of the inner factory.
outer_factory_name: Text, the name of the outer factory.
closure_vars: Iterable[Text], names of the closure variables for the inner
factory.
factory_args: Iterable[Text], names of additional arguments for the
inner factory. Useful to configure variables that the converted code can
use. Typically, these are modules.
future_features: Iterable[Text], names of future statements to associate the
code with.
Returns:
ast.AST
"""
dummy_closure_defs = []
for var_name in closure_vars:
template = """
var_name = None
"""
dummy_closure_defs.extend(templates.replace(template, var_name=var_name))
if future_features:
future_imports = gast.ImportFrom(
module='__future__',
names=[gast.alias(name=name, asname=None) for name in future_features],
level=0)
else:
future_imports = []
factory_args = [
gast.Name(name, ctx=gast.Param(), annotation=None, type_comment=None)
for name in factory_args
]
template = """
future_imports
def outer_factory_name():
dummy_closure_defs
def inner_factory_name(factory_args):
entity_defs
return entity_name
return inner_factory_name
"""
return templates.replace(
template,
dummy_closure_defs=dummy_closure_defs,
entity_defs=nodes,
entity_name=entity_name,
factory_args=factory_args,
future_imports=future_imports,
inner_factory_name=inner_factory_name,
outer_factory_name=outer_factory_name)
def visit_Module(self, node):
self.generic_visit(node)
if MODULE != '__builtin__':
importIt = ast.Import(names=[ast.alias(name=MODULE, asname=None)])
node.body.insert(0, importIt)
return node
def visit_Module(self, node):
self.generic_visit(node)
if MODULE != '__builtin__':
importIt = ast.Import(names=[ast.alias(name=MODULE, asname=None)])
node.body.insert(0, importIt)
return node
def _wrap_into_dynamic_factory(nodes, entity_name, factory_factory_name,
factory_name, closure_vars, future_features):
"""Wraps an AST into the body of a dynamic factory.
This uses the dynamic factory (factory of factory) pattern to achieve the
following:
1. The inner factory, dynamically creates the entity represented by nodes.
2. The entity is parametrized by `ag__`, the internal AutoGraph module.
3. The outer factory creates the inner factory with a lexical scope
in which `closure_vars` are bound local variables. This in turn allows the
caller to control the exact closure (i.e. non-global free variables) for
the inner factory.
The AST is expected to define some symbol named by `entity_name`.
Args:
nodes: ast.AST
entity_name: Union[Text, ast.AST]
factory_factory_name: Text
factory_name: Text
closure_vars: Iterable[Text]
future_features: Iterable[Text], see EntityInfo.future_features.
Returns:
ast.AST
"""
if not isinstance(nodes, (list, tuple)):
nodes = (nodes, )
dummy_closure_defs = []
for var_name in closure_vars:
template = """
var_name = None
"""
dummy_closure_defs.extend(
templates.replace(template, var_name=var_name))
if future_features:
future_imports = gast.ImportFrom(module='__future__',
names=[
gast.alias(name=name, asname=None)
for name in future_features
],
level=0)
else:
future_imports = []
# These dummy symbol declarations create local fariables in a function scope,
# so that the Python parser correctly marks them as free non-global variables
# upon load (that is, it creates cell slots for each symbol). Their values are
# not used, as the cells are swapped with the original entity's cells after
# the code has been loaded.
template = """
future_imports
def factory_factory_name():
dummy_closure_defs
def factory_name(ag__, ag_source_map__, ag_module__):
entity_defs
entity_name.ag_source_map = ag_source_map__
entity_name.ag_module = ag_module__
entity_name.autograph_info__ = {}
return entity_name
return factory_name
"""
return templates.replace(template,
future_imports=future_imports,
factory_factory_name=factory_factory_name,
factory_name=factory_name,
dummy_closure_defs=dummy_closure_defs,
entity_defs=nodes,
entity_name=entity_name)
def visit_Module(self, node):
""" Add itertools import for imap, izip or ifilter iterator. """
self.generic_visit(node)
importIt = ast.Import(names=[ast.alias(name='itertools', asname=None)])
return ast.Module(body=([importIt] + node.body))
def class_to_graph(c, program_ctx):
"""Specialization of `entity_to_graph` for classes."""
converted_members = {}
method_filter = lambda m: tf_inspect.isfunction(m) or tf_inspect.ismethod(m)
members = tf_inspect.getmembers(c, predicate=method_filter)
if not members:
raise ValueError('Cannot convert %s: it has no member methods.' % c)
class_namespace = {}
for _, m in members:
# Only convert the members that are directly defined by the class.
if inspect_utils.getdefiningclass(m, c) is not c:
continue
node, _, namespace = function_to_graph(
m,
program_ctx=program_ctx,
arg_values={},
arg_types={'self': (c.__name__, c)},
owner_type=c)
if class_namespace is None:
class_namespace = namespace
else:
class_namespace.update(namespace)
converted_members[m] = node[0]
namer = program_ctx.new_namer(class_namespace)
class_name = namer.compiled_class_name(c.__name__, c)
# TODO(mdan): This needs to be explained more thoroughly.
# Process any base classes: if the superclass if of a whitelisted type, an
# absolute import line is generated. Otherwise, it is marked for conversion
# (as a side effect of the call to namer.compiled_class_name() followed by
# program_ctx.update_name_map(namer)).
output_nodes = []
renames = {}
base_names = []
for base in c.__bases__:
if isinstance(object, base):
base_names.append('object')
continue
if is_whitelisted_for_graph(base):
alias = namer.new_symbol(base.__name__, ())
output_nodes.append(
gast.ImportFrom(
module=base.__module__,
names=[gast.alias(name=base.__name__, asname=alias)],
level=0))
else:
# This will trigger a conversion into a class with this name.
alias = namer.compiled_class_name(base.__name__, base)
base_names.append(alias)
renames[qual_names.QN(base.__name__)] = qual_names.QN(alias)
program_ctx.update_name_map(namer)
# Generate the definition of the converted class.
bases = [gast.Name(n, gast.Load(), None) for n in base_names]
class_def = gast.ClassDef(
class_name,
bases=bases,
keywords=[],
body=list(converted_members.values()),
decorator_list=[])
# Make a final pass to replace references to the class or its base classes.
# Most commonly, this occurs when making super().__init__() calls.
# TODO(mdan): Making direct references to superclass' superclass will fail.
class_def = qual_names.resolve(class_def)
renames[qual_names.QN(c.__name__)] = qual_names.QN(class_name)
class_def = ast_util.rename_symbols(class_def, renames)
output_nodes.append(class_def)
return output_nodes, class_name, class_namespace
def convert_class_to_ast(c, program_ctx):
"""Specialization of `convert_entity_to_ast` for classes."""
# TODO(mdan): Revisit this altogether. Not sure we still need it.
converted_members = {}
method_filter = lambda m: tf_inspect.isfunction(m) or tf_inspect.ismethod(m)
members = tf_inspect.getmembers(c, predicate=method_filter)
if not members:
raise ValueError('cannot convert %s: no member methods' % c)
# TODO(mdan): Don't clobber namespaces for each method in one class namespace.
# The assumption that one namespace suffices for all methods only holds if
# all methods were defined in the same module.
# If, instead, functions are imported from multiple modules and then spliced
# into the class, then each function has its own globals and __future__
# imports that need to stay separate.
# For example, C's methods could both have `global x` statements referring to
# mod1.x and mod2.x, but using one namespace for C would cause a conflict.
# from mod1 import f1
# from mod2 import f2
# class C(object):
# method1 = f1
# method2 = f2
class_namespace = {}
future_features = None
for _, m in members:
# Only convert the members that are directly defined by the class.
if inspect_utils.getdefiningclass(m, c) is not c:
continue
(node,), _, entity_info = convert_func_to_ast(
m,
program_ctx=program_ctx,
do_rename=False)
class_namespace.update(entity_info.namespace)
converted_members[m] = node
# TODO(mdan): Similarly check the globals.
if future_features is None:
future_features = entity_info.future_features
elif frozenset(future_features) ^ frozenset(entity_info.future_features):
# Note: we can support this case if ever needed.
raise ValueError(
'cannot convert {}: if has methods built with mismatched future'
' features: {} and {}'.format(c, future_features,
entity_info.future_features))
namer = naming.Namer(class_namespace)
class_name = namer.class_name(c.__name__)
# Process any base classes: if the superclass if of a whitelisted type, an
# absolute import line is generated.
output_nodes = []
renames = {}
base_names = []
for base in c.__bases__:
if isinstance(object, base):
base_names.append('object')
continue
if is_whitelisted_for_graph(base):
alias = namer.new_symbol(base.__name__, ())
output_nodes.append(
gast.ImportFrom(
module=base.__module__,
names=[gast.alias(name=base.__name__, asname=alias)],
level=0))
else:
raise NotImplementedError(
'Conversion of classes that do not directly extend classes from'
' whitelisted modules is temporarily suspended. If this breaks'
' existing code please notify the AutoGraph team immediately.')
base_names.append(alias)
renames[qual_names.QN(base.__name__)] = qual_names.QN(alias)
# Generate the definition of the converted class.
bases = [gast.Name(n, gast.Load(), None) for n in base_names]
class_def = gast.ClassDef(
class_name,
bases=bases,
keywords=[],
body=list(converted_members.values()),
decorator_list=[])
# Make a final pass to replace references to the class or its base classes.
# Most commonly, this occurs when making super().__init__() calls.
# TODO(mdan): Making direct references to superclass' superclass will fail.
class_def = qual_names.resolve(class_def)
renames[qual_names.QN(c.__name__)] = qual_names.QN(class_name)
class_def = ast_util.rename_symbols(class_def, renames)
output_nodes.append(class_def)
# TODO(mdan): Find a way better than forging this object.
entity_info = transformer.EntityInfo(
source_code=None,
source_file=None,
future_features=future_features,
namespace=class_namespace)
return output_nodes, class_name, entity_info
def visit_Module(self, node):
self.generic_visit(node)
importIt = ast.Import(names=[ast.alias(name=MODULE, asname=ASMODULE)])
node.body.insert(0, importIt)
return node
def convert_class_to_ast(c, program_ctx):
"""Specialization of `convert_entity_to_ast` for classes."""
# TODO(mdan): Revisit this altogether. Not sure we still need it.
converted_members = {}
method_filter = lambda m: tf_inspect.isfunction(m) or tf_inspect.ismethod(m
)
members = tf_inspect.getmembers(c, predicate=method_filter)
if not members:
raise ValueError('cannot convert %s: no member methods' % c)
# TODO(mdan): Don't clobber namespaces for each method in one class namespace.
# The assumption that one namespace suffices for all methods only holds if
# all methods were defined in the same module.
# If, instead, functions are imported from multiple modules and then spliced
# into the class, then each function has its own globals and __future__
# imports that need to stay separate.
# For example, C's methods could both have `global x` statements referring to
# mod1.x and mod2.x, but using one namespace for C would cause a conflict.
# from mod1 import f1
# from mod2 import f2
# class C(object):
# method1 = f1
# method2 = f2
class_namespace = {}
future_features = None
for _, m in members:
# Only convert the members that are directly defined by the class.
if inspect_utils.getdefiningclass(m, c) is not c:
continue
(node, ), _, entity_info = convert_func_to_ast(m,
program_ctx=program_ctx,
do_rename=False)
class_namespace.update(entity_info.namespace)
converted_members[m] = node
# TODO(mdan): Similarly check the globals.
if future_features is None:
future_features = entity_info.future_features
elif frozenset(future_features) ^ frozenset(
entity_info.future_features):
# Note: we can support this case if ever needed.
raise ValueError(
'cannot convert {}: if has methods built with mismatched future'
' features: {} and {}'.format(c, future_features,
entity_info.future_features))
namer = naming.Namer(class_namespace)
class_name = namer.class_name(c.__name__)
# Process any base classes: if the superclass if of a whitelisted type, an
# absolute import line is generated.
output_nodes = []
renames = {}
base_names = []
for base in c.__bases__:
if isinstance(object, base):
base_names.append('object')
continue
if is_whitelisted_for_graph(base):
alias = namer.new_symbol(base.__name__, ())
output_nodes.append(
gast.ImportFrom(
module=base.__module__,
names=[gast.alias(name=base.__name__, asname=alias)],
level=0))
else:
raise NotImplementedError(
'Conversion of classes that do not directly extend classes from'
' whitelisted modules is temporarily suspended. If this breaks'
' existing code please notify the AutoGraph team immediately.')
base_names.append(alias)
renames[qual_names.QN(base.__name__)] = qual_names.QN(alias)
# Generate the definition of the converted class.
bases = [gast.Name(n, gast.Load(), None) for n in base_names]
class_def = gast.ClassDef(class_name,
bases=bases,
keywords=[],
body=list(converted_members.values()),
decorator_list=[])
# Make a final pass to replace references to the class or its base classes.
# Most commonly, this occurs when making super().__init__() calls.
# TODO(mdan): Making direct references to superclass' superclass will fail.
class_def = qual_names.resolve(class_def)
renames[qual_names.QN(c.__name__)] = qual_names.QN(class_name)
class_def = ast_util.rename_symbols(class_def, renames)
output_nodes.append(class_def)
# TODO(mdan): Find a way better than forging this object.
entity_info = transformer.EntityInfo(source_code=None,
source_file=None,
future_features=future_features,
namespace=class_namespace)
return output_nodes, class_name, entity_info
def visit_Module(self, node):
self.generic_visit(node)
importIt = ast.Import(names=[ast.alias(name=MODULE, asname=ASMODULE)])
node.body.insert(0, importIt)
return node
def class_to_graph(c, program_ctx):
"""Specialization of `entity_to_graph` for classes."""
converted_members = {}
method_filter = lambda m: tf_inspect.isfunction(m) or tf_inspect.ismethod(m
)
members = tf_inspect.getmembers(c, predicate=method_filter)
if not members:
raise ValueError('Cannot convert %s: it has no member methods.' % c)
class_namespace = {}
for _, m in members:
# Only convert the members that are directly defined by the class.
if inspect_utils.getdefiningclass(m, c) is not c:
continue
node, _, namespace = function_to_graph(
m,
program_ctx=program_ctx,
arg_values={},
arg_types={'self': (c.__name__, c)},
owner_type=c)
if class_namespace is None:
class_namespace = namespace
else:
class_namespace.update(namespace)
converted_members[m] = node[0]
namer = program_ctx.new_namer(class_namespace)
class_name = namer.compiled_class_name(c.__name__, c)
# TODO(mdan): This needs to be explained more thoroughly.
# Process any base classes: if the superclass if of a whitelisted type, an
# absolute import line is generated. Otherwise, it is marked for conversion
# (as a side effect of the call to namer.compiled_class_name() followed by
# program_ctx.update_name_map(namer)).
output_nodes = []
renames = {}
base_names = []
for base in c.__bases__:
if isinstance(object, base):
base_names.append('object')
continue
if is_whitelisted_for_graph(base):
alias = namer.new_symbol(base.__name__, ())
output_nodes.append(
gast.ImportFrom(
module=base.__module__,
names=[gast.alias(name=base.__name__, asname=alias)],
level=0))
else:
# This will trigger a conversion into a class with this name.
alias = namer.compiled_class_name(base.__name__, base)
base_names.append(alias)
renames[qual_names.QN(base.__name__)] = qual_names.QN(alias)
program_ctx.update_name_map(namer)
# Generate the definition of the converted class.
bases = [gast.Name(n, gast.Load(), None) for n in base_names]
class_def = gast.ClassDef(class_name,
bases=bases,
keywords=[],
body=list(converted_members.values()),
decorator_list=[])
# Make a final pass to replace references to the class or its base classes.
# Most commonly, this occurs when making super().__init__() calls.
# TODO(mdan): Making direct references to superclass' superclass will fail.
class_def = qual_names.resolve(class_def)
renames[qual_names.QN(c.__name__)] = qual_names.QN(class_name)
class_def = ast_util.rename_symbols(class_def, renames)
output_nodes.append(class_def)
return output_nodes, class_name, class_namespace
def visit_Module(self, node):
""" Add itertools import for imap, izip or ifilter iterator. """
self.generic_visit(node)
importIt = ast.Import(names=[ast.alias(name='itertools', asname=None)])
return ast.Module(body=([importIt] + node.body))
