tf.contrib.framework.model_variable()

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

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.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.
Returns:

The created or existing variable.

doc_TensorFlow
2016-10-14 13:04:49
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