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tf.contrib.checkpoint.Mapping

Class Mapping

An append-only trackable mapping data structure with string keys.

Defined in python/training/tracking/data_structures.py.

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.

__init__

__init__(
    *args,
    **kwargs
)

Construct a new sequence. Arguments are passed to dict().

Properties

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

__contains__

__contains__(key)

__eq__

__eq__(other)

__getitem__

__getitem__(key)

__iter__

__iter__()

__len__

__len__()

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