def to_code(e,
recursive=True,
arg_values=None,
arg_types=None,
partial_types=None,
indentation=' '):
"""Return the equivalent of an entity in TensorFlow code.
See `to_graph` for more details.
Args:
e: A Python entity.
recursive: See to_graph.
arg_values: See to_graph.
arg_types: See to_graph.
partial_types: See to_graph.
indentation: String, when to use for each level of indentation.
Returns:
String.
"""
conversion_map = conversion.ConversionMap(
recursive=recursive,
nocompile_decorators=(convert, graph_ready, convert_inline),
partial_types=partial_types,
api_module=tf_inspect.getmodule(to_graph))
conversion.entity_to_graph(e, conversion_map, arg_values, arg_types)
imports = '\n'.join(config.COMPILED_IMPORT_STATEMENTS)
code = '\n'.join(
compiler.ast_to_source(dep, indentation)
for dep in reversed(tuple(
six.itervalues(conversion_map.dependency_cache))))
return imports + '\n\n' + code
def to_code(e,
recursive=True,
arg_values=None,
arg_types=None,
partial_types=None,
indentation=' '):
"""Return the equivalent of an entity in TensorFlow code.
See `to_graph` for more details.
Args:
e: A Python entity.
recursive: See to_graph.
arg_values: See to_graph.
arg_types: See to_graph.
partial_types: See to_graph.
indentation: String, when to use for each level of indentation.
Returns:
String.
"""
conversion_map = conversion.ConversionMap(
recursive=recursive,
nocompile_decorators=(convert, graph_ready, convert_inline),
partial_types=partial_types,
api_module=tf_inspect.getmodule(to_graph))
conversion.entity_to_graph(e, conversion_map, arg_values, arg_types)
imports = '\n'.join(config.COMPILED_IMPORT_STATEMENTS)
code = '\n'.join(
compiler.ast_to_source(dep, indentation) for dep in reversed(
tuple(six.itervalues(conversion_map.dependency_cache))))
return imports + '\n\n' + code
def to_code(o,
recursive=True,
arg_value_hints=None,
partial_types=None,
indentation=' '):
"""Return the equivalent of an entity in TensorFlow code.
See `to_graph` for more details.
Args:
o: A Python function or class.
recursive: Whether to recusrively convert any functions that the decorator
function may call.
arg_value_hints: A dict mapping parameter names to objects that can hint
at the type of those parameters.
partial_types: A set of types (e.g. classes) that will not be converted
entirely. Calls to member functions for these types will be renamed
independently.
indentation: String, when to use for each level of indentation.
Returns:
String.
"""
conversion_map = conversion.ConversionMap(
recursive=recursive,
nocompile_decorators=(convert, graph_ready, convert_inline),
partial_types=partial_types)
conversion.object_to_graph(o, conversion_map, arg_value_hints)
imports = '\n'.join(config.COMPILED_IMPORT_STATEMENTS)
code = '\n'.join(
compiler.ast_to_source(dep, indentation) for dep in reversed(
tuple(six.itervalues(conversion_map.dependency_cache))))
return imports + '\n\n' + code
def test_ast_to_source(self):
node = gast.If(
test=gast.Num(1),
body=[
gast.Assign(
targets=[gast.Name('a', gast.Store(), None)],
value=gast.Name('b', gast.Load(), None))
],
orelse=[
gast.Assign(
targets=[gast.Name('a', gast.Store(), None)],
value=gast.Str('c'))
])
self.assertEqual(
textwrap.dedent("""
if 1:
a = b
else:
a = 'c'
""").strip(),
compiler.ast_to_source(node, indentation=' ').strip())
def to_code(f, arg_value_hints=None, indentation=' '):
"""Return the equivalent of a function in TensorFlow code.
Args:
f: A Python function with arbitrary arguments and return values.
arg_value_hints: A dict mapping parameter names to objects that can hint
at the type of those parameters.
indentation: String, when to use for each level of indentation.
Returns:
String.
"""
conversion_map = conversion.ConversionMap()
conversion.object_to_graph(f, conversion_map, arg_value_hints)
imports = '\n'.join(config.COMPILED_IMPORT_STATEMENTS)
code = '\n'.join(
compiler.ast_to_source(dep, indentation) for dep in reversed(
tuple(six.itervalues(conversion_map.dependency_cache))))
return imports + '\n\n' + code
def to_code(f, arg_value_hints=None, indentation=' '):
"""Return the equivalent of a function in TensorFlow code.
Args:
f: A Python function with arbitrary arguments and return values.
arg_value_hints: A dict mapping parameter names to objects that can hint
at the type of those parameters.
indentation: String, when to use for each level of indentation.
Returns:
String.
"""
conversion_map = conversion.ConversionMap()
conversion.object_to_graph(f, conversion_map, arg_value_hints)
imports = '\n'.join(config.COMPILED_IMPORT_STATEMENTS)
code = '\n'.join(
compiler.ast_to_source(dep, indentation)
for dep in reversed(tuple(
six.itervalues(conversion_map.dependency_cache))))
return imports + '\n\n' + code
def to_code(o,
recursive=True,
arg_value_hints=None,
partial_types=None,
indentation=' '):
"""Return the equivalent of an entity in TensorFlow code.
See `to_graph` for more details.
Args:
o: A Python function or class.
recursive: Whether to recusrively convert any functions that the decorator
function may call.
arg_value_hints: A dict mapping parameter names to objects that can hint
at the type of those parameters.
partial_types: A set of types (e.g. classes) that will not be converted
entirely. Calls to member functions for these types will be renamed
independently.
indentation: String, when to use for each level of indentation.
Returns:
String.
"""
conversion_map = conversion.ConversionMap(
recursive=recursive,
nocompile_decorators=(convert, graph_ready, convert_inline),
partial_types=partial_types)
conversion.object_to_graph(o, conversion_map, arg_value_hints)
imports = '\n'.join(config.COMPILED_IMPORT_STATEMENTS)
code = '\n'.join(
compiler.ast_to_source(dep, indentation)
for dep in reversed(tuple(
six.itervalues(conversion_map.dependency_cache))))
return imports + '\n\n' + code
def try_ast_to_source(node):
try:
return compiler.ast_to_source(node)
except AssertionError:
return '<could not convert AST to source>'
def try_ast_to_source(node):
try:
return compiler.ast_to_source(node)
except AssertionError:
return '<could not convert AST to source>'
