Method as_default

tensorflow/python/framework/ops.py:3840–3880

Returns a context manager that makes this `Graph` the default graph. This method should be used if you want to create multiple graphs in the same process. For convenience, a global default graph is provided, and all ops will be added to this graph if you do not create a new graph ex

(self)

      return op_def

  def as_default(self):
    """Returns a context manager that makes this `Graph` the default graph.

    This method should be used if you want to create multiple graphs
    in the same process. For convenience, a global default graph is
    provided, and all ops will be added to this graph if you do not
    create a new graph explicitly.

    Use this method with the `with` keyword to specify that ops created within
    the scope of a block should be added to this graph. In this case, once
    the scope of the `with` is exited, the previous default graph is set again
    as default. There is a stack, so it's ok to have multiple nested levels
    of `as_default` calls.

    The default graph is a property of the current thread. If you
    create a new thread, and wish to use the default graph in that
    thread, you must explicitly add a `with g.as_default():` in that
    thread's function.

    The following code examples are equivalent:

    ```python
    # 1. Using Graph.as_default():
    g = tf.Graph()
    with g.as_default():
      c = tf.constant(5.0)
      assert c.graph is g

    # 2. Constructing and making default:
    with tf.Graph().as_default() as g:
      c = tf.constant(5.0)
      assert c.graph is g
    ```

    If eager execution is enabled ops created under this context manager will be
    added to the graph instead of executed eagerly.

    Returns:
      A context manager for using this graph as the default graph.
    """
    return _default_graph_stack.get_controller(self)

  @property
  def collections(self):