Method reset

tensorflow/python/client/session.py:1652–1683

Resets resource containers on `target`, and close all connected sessions. A resource container is distributed across all workers in the same cluster as `target`. When a resource container on `target` is reset, resources associated with that container will be cleared. In particular,

(target, containers=None, config=None)

  @staticmethod
  def reset(target, containers=None, config=None):
    """Resets resource containers on `target`, and close all connected sessions.

    A resource container is distributed across all workers in the
    same cluster as `target`.  When a resource container on `target`
    is reset, resources associated with that container will be cleared.
    In particular, all Variables in the container will become undefined:
    they lose their values and shapes.

    NOTE:
    (i) reset() is currently only implemented for distributed sessions.
    (ii) Any sessions on the master named by `target` will be closed.

    If no resource containers are provided, all containers are reset.

    Args:
      target: The execution engine to connect to.
      containers: A list of resource container name strings, or `None` if all of
        all the containers are to be reset.
      config: (Optional.) Protocol buffer with configuration options.

    Raises:
      tf.errors.OpError: Or one of its subclasses if an error occurs while
        resetting containers.
    """
    if target is not None:
      target = compat.as_bytes(target)
    if containers is not None:
      containers = [compat.as_bytes(c) for c in containers]
    else:
      containers = []
    tf_session.TF_Reset(target, containers, config)


@tf_export(v1=['InteractiveSession'])