tf.contrib.framework.variable(args, *kwargs)

tf.contrib.framework.variable(*args, **kwargs)

See the guide: Framework (contrib) > Variables

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


  • 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. If None it would default to tf.GraphKeys.GLOBAL_VARIABLES.
  • 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.


The created or existing variable.

Defined in tensorflow/contrib/framework/python/ops/