tf.contrib.checkpoint.Mapping
An append-only trackable mapping data structure with string keys.
tf.contrib.checkpoint.Mapping( *args, **kwargs )
Maintains checkpoint dependencies on its contents (which must also be trackable), named based on its keys.
Note that once a key has been added, it may not be deleted or replaced. If names may not be unique, see tf.contrib.checkpoint.UniqueNameTracker
.
Attributes | |
---|---|
layers |
|
losses |
Aggregate losses from any Layer instances. |
non_trainable_variables |
|
non_trainable_weights |
|
trainable |
|
trainable_variables |
|
trainable_weights |
|
updates |
Aggregate updates from any Layer instances. |
variables |
|
weights |
Methods
get
get( key, default=None )
D.get(k[,d]) -> D[k] if k in D, else d. d defaults to None.
items
items()
D.items() -> a set-like object providing a view on D's items
keys
keys()
D.keys() -> a set-like object providing a view on D's keys
update
update( *args, **kwargs )
values
values()
D.values() -> an object providing a view on D's values
__contains__
__contains__( key )
__eq__
__eq__( other )
Return self==value.
__getitem__
__getitem__( key )
__iter__
__iter__()
__len__
__len__()
© 2020 The TensorFlow Authors. All rights reserved.
Licensed under the Creative Commons Attribution License 3.0.
Code samples licensed under the Apache 2.0 License.
https://www.tensorflow.org/versions/r1.15/api_docs/python/tf/contrib/checkpoint/Mapping