def make_type_checker(annotation):
"""Builds a PyTypeChecker for the given type annotation."""
if type_annotations.is_generic_union(annotation):
type_args = type_annotations.get_generic_type_args(annotation)
options = [make_type_checker(t) for t in type_args]
return _api_dispatcher.MakeUnionChecker(options)
elif type_annotations.is_generic_list(annotation):
type_args = type_annotations.get_generic_type_args(annotation)
if len(type_args) != 1:
raise AssertionError(
"Expected List[...] to have a single type parameter")
elt_type = make_type_checker(type_args[0])
return _api_dispatcher.MakeListChecker(elt_type)
elif isinstance(annotation, type):
if annotation not in _is_instance_checker_cache:
checker = _api_dispatcher.MakeInstanceChecker(annotation)
_is_instance_checker_cache[annotation] = checker
return _is_instance_checker_cache[annotation]
elif annotation is None:
return make_type_checker(type(None))
else:
raise ValueError(
f"Type annotation {annotation} is not currently supported"
" by dispatch. Supported annotations: type objects, "
" List[...], and Union[...]")
def testGenericTypePredicates(self, tp, expected):
self.assertEqual(type_annotations.is_generic_union(tp),
expected == 'Union')
self.assertEqual(type_annotations.is_generic_tuple(tp),
expected == 'Tuple')
self.assertEqual(type_annotations.is_generic_mapping(tp),
expected == 'Mapping')
def _convert_value(value, expected_type, path, for_spec=False):
"""Type-checks and converts a value.
Args:
value: The value to type-check.
expected_type: The expected type for the value.
path: Tuple of `str` naming the value (used for exception messages).
for_spec: If false, then expect a value for tensor-like types; if true, then
expect a TensorSpec for tensor-like types.
Returns:
A copy of `value`, converted to the expected type.
Raises:
TypeError: If `value` can not be converted to the expected type.
"""
assert isinstance(path, tuple)
if expected_type is None:
expected_type = _NoneType
if expected_type is ops.Tensor:
return _convert_tensor(value, path, for_spec)
elif isinstance(expected_type, tensor_spec.TensorSpec):
return _convert_tensor_spec(value, expected_type, path, for_spec)
elif isinstance(expected_type, type_spec.TypeSpec):
return _convert_type_spec(value, expected_type, path, for_spec)
elif (isinstance(expected_type, type)
and issubclass(expected_type, composite_tensor.CompositeTensor)):
return _convert_composite_tensor(value, expected_type, path, for_spec)
elif expected_type is tensor_shape.TensorShape:
try:
return tensor_shape.as_shape(value)
except TypeError as e:
raise TypeError(
f'{"".join(path)}: expected tf.TensorShape, got {value!r}'
) from e
elif expected_type is dtypes.DType:
try:
return dtypes.as_dtype(value)
except TypeError as e:
raise TypeError(
f'{"".join(path)}: expected tf.DType, got {value!r}') from e
elif expected_type in (int, float, bool, str, bytes, _NoneType):
if not isinstance(value, expected_type):
raise TypeError(f'{"".join(path)}: expected '
f'{expected_type.__name__}, got {value!r}')
return value
elif type_annotations.is_generic_tuple(expected_type):
return _convert_tuple(value, expected_type, path, for_spec)
elif type_annotations.is_generic_mapping(expected_type):
return _convert_mapping(value, expected_type, path, for_spec)
elif type_annotations.is_generic_union(expected_type):
return _convert_union(value, expected_type, path, for_spec)
else:
raise TypeError(f'{"".join(path)}: Unsupported type annotation '
f'{expected_type!r}')
def contains_cls(x):
"""Returns true if `x` contains `cls`."""
if isinstance(x, dict):
return any(contains_cls(v) for v in x.values())
elif x is cls:
return True
elif (type_annotations.is_generic_list(x)
or type_annotations.is_generic_union(x)):
type_args = type_annotations.get_generic_type_args(x)
return any(contains_cls(arg) for arg in type_args)
else:
return False
def validate_field_value_type(value_type,
in_mapping_key=False,
allow_forward_references=False):
"""Checks that `value_type` contains only supported type annotations.
Args:
value_type: The type annotation to check.
in_mapping_key: True if `value_type` is nested in the key of a mapping.
allow_forward_references: If false, then raise an exception if a
`value_type` contains a forward reference (i.e., a string literal).
Raises:
TypeError: If `value_type` contains an unsupported type annotation.
"""
if isinstance(value_type,
str) or type_annotations.is_forward_ref(value_type):
if allow_forward_references:
return
else:
raise TypeError(f'Unresolved forward reference {value_type!r}')
if value_type in (int, float, str, bytes, bool, None, _NoneType,
dtypes.DType):
return
elif (value_type in (ops.Tensor, tensor_shape.TensorShape)
or (isinstance(value_type, type)
and issubclass(value_type, composite_tensor.CompositeTensor))):
if in_mapping_key:
raise TypeError(
f"Mapping had a key '{value_type.__name__}' with type "
f"'{type(value_type).__name__}'")
elif (type_annotations.is_generic_tuple(value_type)
or type_annotations.is_generic_union(value_type)):
type_args = type_annotations.get_generic_type_args(value_type)
if (len(type_args) == 2 and type_args[1] is Ellipsis
and type_annotations.is_generic_tuple(value_type)
): # `Tuple[X, ...]`
validate_field_value_type(type_args[0], in_mapping_key,
allow_forward_references)
else:
for arg in type_annotations.get_generic_type_args(value_type):
validate_field_value_type(arg, in_mapping_key,
allow_forward_references)
elif type_annotations.is_generic_mapping(value_type):
key_type, value_type = type_annotations.get_generic_type_args(
value_type)
validate_field_value_type(key_type, True, allow_forward_references)
validate_field_value_type(value_type, in_mapping_key,
allow_forward_references)
elif isinstance(value_type, type):
raise TypeError(f'Unsupported type annotation `{value_type.__name__}`')
else:
raise TypeError(f'Unsupported type annotation {value_type!r}')
def make_type_checker(annotation):
"""Builds a PyTypeChecker for the given type annotation."""
if type_annotations.is_generic_union(annotation):
type_args = type_annotations.get_generic_type_args(annotation)
# If the union contains two or more simple types, then use a single
# InstanceChecker to check them.
simple_types = [t for t in type_args if isinstance(t, type)]
simple_types = tuple(sorted(simple_types, key=id))
if len(simple_types) > 1:
if simple_types not in _is_instance_checker_cache:
checker = _api_dispatcher.MakeInstanceChecker(*simple_types)
_is_instance_checker_cache[simple_types] = checker
options = ([_is_instance_checker_cache[simple_types]] + [
make_type_checker(t)
for t in type_args if not isinstance(t, type)
])
return _api_dispatcher.MakeUnionChecker(options)
options = [make_type_checker(t) for t in type_args]
return _api_dispatcher.MakeUnionChecker(options)
elif type_annotations.is_generic_list(annotation):
type_args = type_annotations.get_generic_type_args(annotation)
if len(type_args) != 1:
raise AssertionError(
"Expected List[...] to have a single type parameter")
elt_type = make_type_checker(type_args[0])
return _api_dispatcher.MakeListChecker(elt_type)
elif isinstance(annotation, type):
if annotation not in _is_instance_checker_cache:
checker = _api_dispatcher.MakeInstanceChecker(annotation)
_is_instance_checker_cache[annotation] = checker
return _is_instance_checker_cache[annotation]
elif annotation is None:
return make_type_checker(type(None))
else:
raise ValueError(
f"Type annotation {annotation} is not currently supported"
" by dispatch. Supported annotations: type objects, "
" List[...], and Union[...]")
