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tf.contrib.framework.model_variable

tf.contrib.framework.model_variable

model_variable(
    name,
    shape=None,
    dtype=tf.float32,
    initializer=None,
    regularizer=None,
    trainable=True,
    collections=None,
    caching_device=None,
    device=None,
    partitioner=None,
    custom_getter=None,
    use_resource=None
)

Defined in tensorflow/contrib/framework/python/ops/variables.py.

See the guide: Framework (contrib) > Variables

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

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.

Returns:

The created or existing variable.

© 2017 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/api_docs/python/tf/contrib/framework/model_variable