tf.contrib.framework.model_variable

Gets an existing model variable with these parameters or creates a new one.

tf.contrib.framework.model_variable(
    name, shape=None, dtype=tf.dtypes.float32, initializer=None, regularizer=None,
    trainable=True, collections=None, caching_device=None, device=None,
    partitioner=None, custom_getter=None, use_resource=None,
    synchronization=tf.VariableSynchronization.AUTO,
    aggregation=tf.VariableAggregation.NONE
)

Args
`name`	the name of the new or existing variable.
`shape`	shape of the new or existing variable.
`dtype`	type of the new or existing variable (defaults to `DT_FLOAT`).
`initializer`	initializer for the variable if one is created.
`regularizer`	a (Tensor -> Tensor or None) function; the result of applying it on a newly created variable will be added to the collection GraphKeys.REGULARIZATION_LOSSES and can be used for regularization.
`trainable`	If `True` also add the variable to the graph collection `GraphKeys.TRAINABLE_VARIABLES` (see `tf.Variable`).
`collections`	A list of collection names to which the Variable will be added. Note that the variable is always also added to the `GraphKeys.GLOBAL_VARIABLES` and `GraphKeys.MODEL_VARIABLES` collections.
`caching_device`	Optional device string or function describing where the Variable should be cached for reading. Defaults to the Variable's device.
`device`	Optional device to place the variable. It can be an string or a function that is called to get the device for the variable.
`partitioner`	Optional callable that accepts a fully defined `TensorShape` and dtype of the `Variable` to be created, and returns a list of partitions for each axis (currently only one axis can be partitioned).
`custom_getter`	Callable that allows overwriting the internal get_variable method and has to have the same signature.
`use_resource`	If `True` use a ResourceVariable instead of a Variable.
`synchronization`	Indicates when a distributed a variable will be aggregated. Accepted values are constants defined in the class `tf.VariableSynchronization`. By default the synchronization is set to `AUTO` and the current `DistributionStrategy` chooses when to synchronize.
`aggregation`	Indicates how a distributed variable will be aggregated. Accepted values are constants defined in the class `tf.VariableAggregation`.

Returns
The created or existing variable.

tf.contrib.framework.model_variable

Args

Returns