Python tf.Graph.container用法及代码示例

用法

@tf_contextlib.contextmanager
container(
    container_name
)

返回指定要使用的资源容器的上下文管理器。

有状态的操作，例如变量和队列，可以在设备上维护它们的状态，以便它们可以被多个进程共享。资源容器是跟踪这些有状态操作的字符串名称。可以使用 tf.Session.reset() 释放或清除这些资源。

例如：

with g.container('experiment0'):
  # All stateful Operations constructed in this context will be placed
  # in resource container "experiment0".
  v1 = tf.Variable([1.0])
  v2 = tf.Variable([2.0])
  with g.container("experiment1"):
    # All stateful Operations constructed in this context will be
    # placed in resource container "experiment1".
    v3 = tf.Variable([3.0])
    q1 = tf.queue.FIFOQueue(10, tf.float32)
  # All stateful Operations constructed in this context will be
  # be created in the "experiment0".
  v4 = tf.Variable([4.0])
  q1 = tf.queue.FIFOQueue(20, tf.float32)
  with g.container(""):
    # All stateful Operations constructed in this context will be
    # be placed in the default resource container.
    v5 = tf.Variable([5.0])
    q3 = tf.queue.FIFOQueue(30, tf.float32)

# Resets container "experiment0", after which the state of v1, v2, v4, q1
# will become undefined (such as uninitialized).
tf.Session.reset(target, ["experiment0"])