Base class for TensorFlow ExtensionType
classes.
meridian
.
backend
.
ExtensionType
(
*
args
,
**
kwargs
)
Tensorflow ExtensionType
classes are specialized Python classes that can be
used transparently with TensorFlow -- e.g., they can be used with ops
such as tf.cond
or tf.while_loop
and used as inputs or outputs for tf.function
and Keras layers.
New ExtensionType
classes are defined by creating a subclass of tf.ExtensionType
that
contains type annotations for all instance variables. The following type
annotations are supported:
| Type | Example |
|---|---|
| Python integers | i: int
|
| Python floats | f: float
|
| Python strings | s: str
|
| Python booleans | b: bool
|
| Python None | n: None
|
| Python tuple | params: tuple[int, float, int, int]
|
| Python tuple w/ Ellipsis | lengths: tuple[int, ...]
|
| Tensors | t: tf.Tensor
|
| Composite Tensors | rt: tf.RaggedTensor
|
| Extension Types | m: MyMaskedTensor
|
| Tensor shapes | shape: tf.TensorShape
|
| Tensor dtypes | dtype: tf.DType
|
| Type unions | length: typing.Union[int, float]
|
| Tuples | params: typing.Tuple[int, float, int, int]
|
| Tuples w/ Ellipsis | lengths: typing.Tuple[int, ...]
|
| Mappings | tags: typing.Mapping[str, str]
|
Fields annotated with typing.Mapping
will be stored using an immutable
mapping type.
ExtensionType values are immutable -- i.e., once constructed, you can not modify or delete any of their instance members.
Examples
>>> class
MaskedTensor
( ExtensionType
):
... values:
tf
. Tensor
... mask:
tf
. Tensor
>>> class
Toy
( ExtensionType
):
... name:
str
... price:
tensor
. Tensor
... features:
typing
. Mapping
[ str
, tf
. Tensor
]
>>> class
ToyStore
( ExtensionType
):
... name:
str
... toys:
typing
. Tuple
[ Toy
, ...]
Methods
__eq__
__eq__
(
other
)
Return self==value.
__ne__
__ne__
(
other
)
Return self!=value.
