Internal cleanup: retire support for converting whole classes, which is not supported in TF2 and is unlikely to have real uses.
PiperOrigin-RevId: 302550027 Change-Id: I0127d56a3cc45ea38205df9a88480a75d25ea39c
This commit is contained in:
Dan Moldovan
TensorFlower Gardener
parent
ec5c9bebf8
commit
b5c7256118
@ -52,12 +52,11 @@ from tensorflow.python.autograph.core import naming
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from tensorflow.python.autograph.core import unsupported_features_checker
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from tensorflow.python.autograph.lang import special_functions
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from tensorflow.python.autograph.pyct import ast_util
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from tensorflow.python.autograph.pyct import loader
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from tensorflow.python.autograph.pyct import inspect_utils
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from tensorflow.python.autograph.pyct import loader
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from tensorflow.python.autograph.pyct import origin_info
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from tensorflow.python.autograph.pyct import parser
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from tensorflow.python.autograph.pyct import pretty_printer
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from tensorflow.python.autograph.pyct import qual_names
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from tensorflow.python.autograph.pyct import templates
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from tensorflow.python.autograph.pyct import transformer
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from tensorflow.python.autograph.utils import ag_logging as logging
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@ -299,15 +298,8 @@ def _instantiate(entity, converted_entity_info, free_nonglobal_var_names):
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"""Creates a converted instance and binds it to match original entity."""
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factory = converted_entity_info.get_factory()
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# `factory` is currently bound to the empty module it was loaded from.
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# It must instead be bound to the globals and closure from the original
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# entity.
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if tf_inspect.isfunction(entity) or tf_inspect.ismethod(entity):
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entity_globals = entity.__globals__
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entity_closure = entity.__closure__ or ()
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elif hasattr(entity, '__module__'):
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entity_globals = sys.modules[entity.__module__].__dict__
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entity_closure = ()
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assert len(entity_closure) == len(free_nonglobal_var_names)
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# Fit the original entity's cells to match the order of factory's cells.
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@ -328,7 +320,6 @@ def _instantiate(entity, converted_entity_info, free_nonglobal_var_names):
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ag_internal, converted_entity_info.source_map,
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converted_entity_info.get_module())
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if tf_inspect.isfunction(entity) or tf_inspect.ismethod(entity):
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# Attach the default argument to the converted function.
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converted_entity.__defaults__ = entity.__defaults__
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if hasattr(entity, '__kwdefaults__'):
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@ -340,14 +331,11 @@ def _instantiate(entity, converted_entity_info, free_nonglobal_var_names):
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def convert(entity, program_ctx):
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"""Converts an entity into an equivalent entity."""
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if tf_inspect.isfunction(entity) or tf_inspect.ismethod(entity):
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if not hasattr(entity, '__code__'):
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raise ValueError('Cannot apply autograph to a function that doesn\'t '
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'expose a __code__ object. If this is a @tf.function,'
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' try passing f.python_function instead.')
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free_nonglobal_var_names = entity.__code__.co_freevars
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else:
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free_nonglobal_var_names = ()
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for i, name in enumerate(free_nonglobal_var_names):
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if (name == 'ag__' and
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@ -505,22 +493,7 @@ def convert_entity_to_ast(o, program_ctx):
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"""
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logging.log(1, 'Converting %s', o)
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if tf_inspect.isclass(o):
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nodes, name, entity_info = convert_class_to_ast(o, program_ctx)
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elif tf_inspect.isfunction(o):
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nodes, name, entity_info = convert_func_to_ast(o, program_ctx)
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elif tf_inspect.ismethod(o):
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nodes, name, entity_info = convert_func_to_ast(o, program_ctx)
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elif hasattr(o, '__class__'):
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# Note: this should only be raised when attempting to convert the object
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# directly. converted_call should still support it.
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raise NotImplementedError(
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'cannot convert entity "{}": object conversion is not yet'
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' supported.'.format(o))
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else:
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raise NotImplementedError(
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'Entity "%s" has unsupported type "%s". Only functions and classes are '
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'supported for now.' % (o, type(o)))
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if logging.has_verbosity(2):
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logging.log(2, 'Compiled output of %s:\n\n%s\n', o, parser.unparse(nodes))
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@ -532,106 +505,6 @@ def convert_entity_to_ast(o, program_ctx):
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return nodes, name, entity_info
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def convert_class_to_ast(c, program_ctx):
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"""Specialization of `convert_entity_to_ast` for classes."""
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# TODO(mdan): Revisit this altogether. Not sure we still need it.
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converted_members = {}
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method_filter = lambda m: tf_inspect.isfunction(m) or tf_inspect.ismethod(m)
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members = tf_inspect.getmembers(c, predicate=method_filter)
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if not members:
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raise ValueError('cannot convert %s: no member methods' % c)
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# TODO(mdan): Don't clobber namespaces for each method in one class namespace.
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# The assumption that one namespace suffices for all methods only holds if
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# all methods were defined in the same module.
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# If, instead, functions are imported from multiple modules and then spliced
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# into the class, then each function has its own globals and __future__
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# imports that need to stay separate.
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# For example, C's methods could both have `global x` statements referring to
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# mod1.x and mod2.x, but using one namespace for C would cause a conflict.
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# from mod1 import f1
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# from mod2 import f2
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# class C(object):
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# method1 = f1
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# method2 = f2
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class_namespace = {}
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future_features = None
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for _, m in members:
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# Only convert the members that are directly defined by the class.
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if inspect_utils.getdefiningclass(m, c) is not c:
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continue
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(node,), _, entity_info = convert_func_to_ast(
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m, program_ctx=program_ctx, do_rename=False)
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class_namespace.update(entity_info.namespace)
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converted_members[m] = node
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# TODO(mdan): Similarly check the globals.
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if future_features is None:
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future_features = entity_info.future_features
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elif frozenset(future_features) ^ frozenset(entity_info.future_features):
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# Note: we can support this case if ever needed.
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raise ValueError(
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'cannot convert {}: if has methods built with mismatched future'
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' features: {} and {}'.format(c, future_features,
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entity_info.future_features))
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namer = naming.Namer(class_namespace)
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class_name = namer.class_name(c.__name__)
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# Process any base classes: if the superclass if of a whitelisted type, an
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# absolute import line is generated.
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output_nodes = []
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renames = {}
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base_names = []
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for base in c.__bases__:
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if isinstance(object, base):
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base_names.append('object')
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continue
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if is_whitelisted(base):
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alias = namer.new_symbol(base.__name__, ())
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output_nodes.append(
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gast.ImportFrom(
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module=base.__module__,
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names=[gast.alias(name=base.__name__, asname=alias)],
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level=0))
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else:
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raise NotImplementedError(
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'Conversion of classes that do not directly extend classes from'
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' whitelisted modules is temporarily suspended. If this breaks'
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' existing code please notify the AutoGraph team immediately.')
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base_names.append(alias)
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renames[qual_names.QN(base.__name__)] = qual_names.QN(alias)
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# Generate the definition of the converted class.
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bases = [
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gast.Name(n, ctx=gast.Load(), annotation=None, type_comment=None)
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for n in base_names]
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class_def = gast.ClassDef(
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class_name,
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bases=bases,
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keywords=[],
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body=list(converted_members.values()),
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decorator_list=[])
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# Make a final pass to replace references to the class or its base classes.
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# Most commonly, this occurs when making super().__init__() calls.
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# TODO(mdan): Making direct references to superclass' superclass will fail.
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class_def = qual_names.resolve(class_def)
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renames[qual_names.QN(c.__name__)] = qual_names.QN(class_name)
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class_def = ast_util.rename_symbols(class_def, renames)
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output_nodes.append(class_def)
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# TODO(mdan): Find a way better than forging this object.
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entity_info = transformer.EntityInfo(
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source_code=None,
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source_file=None,
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future_features=future_features,
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namespace=class_namespace)
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return output_nodes, class_name, entity_info
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def _add_reserved_symbol(namespace, name, entity):
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if name not in namespace:
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namespace[name] = entity
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@ -36,7 +36,6 @@ from tensorflow.python.autograph.impl.testing import pybind_for_testing
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from tensorflow.python.autograph.pyct import parser
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from tensorflow.python.eager import function
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from tensorflow.python.framework import constant_op
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from tensorflow.python.keras.engine import training
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from tensorflow.python.platform import test
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@ -127,11 +126,6 @@ class ConversionTest(test.TestCase):
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# Note: currently, native bindings are whitelisted by a separate check.
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self.assertFalse(conversion.is_whitelisted(test_object.method))
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def test_convert_entity_to_ast_unsupported_types(self):
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with self.assertRaises(NotImplementedError):
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program_ctx = self._simple_program_ctx()
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conversion.convert_entity_to_ast('dummy', program_ctx)
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def test_convert_entity_to_ast_callable(self):
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b = 2
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@ -174,53 +168,6 @@ class ConversionTest(test.TestCase):
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f_node, = nodes
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self.assertEqual('tf__f', f_node.name)
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def test_convert_entity_to_ast_class_hierarchy(self):
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class TestBase(object):
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def __init__(self, x='base'):
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self.x = x
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def foo(self):
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return self.x
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def bar(self):
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return self.x
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class TestSubclass(TestBase):
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def __init__(self, y):
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super(TestSubclass, self).__init__('sub')
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self.y = y
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def foo(self):
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return self.y
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def baz(self):
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return self.y
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program_ctx = self._simple_program_ctx()
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with self.assertRaisesRegex(NotImplementedError, 'classes.*whitelisted'):
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conversion.convert_entity_to_ast(TestSubclass, program_ctx)
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def test_convert_entity_to_ast_class_hierarchy_whitelisted(self):
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class TestSubclass(training.Model):
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def __init__(self, y):
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super(TestSubclass, self).__init__()
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self.built = False
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def call(self, x):
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return 3 * x
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program_ctx = self._simple_program_ctx()
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(import_node, class_node), name, _ = conversion.convert_entity_to_ast(
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TestSubclass, program_ctx)
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self.assertEqual(import_node.names[0].name, 'Model')
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self.assertEqual(name, 'TfTestSubclass')
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self.assertEqual(class_node.name, 'TfTestSubclass')
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def test_convert_entity_to_ast_lambda(self):
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b = 2
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f = lambda x: b * x if x > 0 else -x
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