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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. |
© 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/framework/model_variable