|  View source on GitHub | 
Converts the argument into an instance of tff.Type.
tff.types.to_type(
    obj: object
) -> tff.types.Type
Examples of arguments convertible to tensor types:
np.int32
(np.int32, [10])
(np.int32, [None])
Examples of arguments convertible to flat named tuple types:
[np.int32, np.bool]
(np.int32, np.bool)
[('a', np.int32), ('b', np.bool)]
('a', np.int32)
collections.OrderedDict([('a', np.int32), ('b', np.bool)])
Examples of arguments convertible to nested named tuple types:
(np.int32, (np.float32, np.bool))
(np.int32, (('x', np.float32), np.bool))
((np.int32, [1]), (('x', (np.float32, [2])), (np.bool, [3])))
attr.s class instances can also be used to describe TFF types by populating
the fields with the corresponding types:
@attr.s(auto_attribs=True)
class MyDataClass:
  int_scalar
  string_array
obj = MyDataClass(...)
type_spec = tff.types.to_type(obj)
@tff.tensorflow.computation(type_spec)
def work(my_data):
  assert isinstance(my_data, MyDataClass)
  ...
| Args | |
|---|---|
| obj | Either an instance of tff.Type, or an argument convertible totff.Type. | 
| Returns | |
|---|---|
| An instance of tff.Typecorresponding to the givenobj. |