def func_attr_value():
func = NameAttrList(name='test_attr_list_name',
attr={
'int': AttrValue(i=3333),
'bool': AttrValue(b=True)
})
return AttrValue(func=func)
def attr_value_to_python_type(attr_value: tf.AttrValue) -> Any:
"""
Inverse of python_type_to_attr_value().
Args:
attr_value: Protocol buffer version of a node's attribute value
Returns:
A Python object or built-in type corresponding to the field in
`attr_value` that is in use.
"""
# TODO(frreiss): Handle AttrValues that are lists
if attr_value.HasField("s"): # str
# TODO(frreiss): Should we return the binary value here?
return tf.compat.as_str(attr_value.s)
elif attr_value.HasField("i"): # int
return attr_value.i
elif attr_value.HasField("f"): # float
return attr_value.f
elif attr_value.HasField("b"): # bool
return attr_value.b
elif attr_value.HasField("type"): # DType
return tf.DType(attr_value.type)
elif attr_value.HasField("shape"): # TensorShape
# Undocumented behavior of public API: tf.TensorShape constructor accepts
# a TensorShapeProto.
return tf.TensorShape(attr_value.shape)
elif attr_value.HasField("tensor"): # TensorProto
return tf.make_ndarray(attr_value.tensor)
# TODO(frreiss): Convert the "func" and "placeholder" fields of the union
# here
else:
raise ValueError("Don't know how to convert AttrValue {} to "
"a Python object".format(attr_value))
def int_attr_value():
return AttrValue(i=3333)
def placeholder_attr_value():
return AttrValue(placeholder='placeholder')
def bool_attr_value():
return AttrValue(b=True)
def float_attr_value():
return AttrValue(f=3.14159)
def bytes_attr_value():
return AttrValue(s=b'bytes')