tf.RandomShuffleQueue.__init__()

tf.RandomShuffleQueue.__init__(capacity, min_after_dequeue, dtypes, shapes=None, names=None, seed=None, shared_name=None, name='random_shuffle_queue')

Create a queue that dequeues elements in a random order.

A RandomShuffleQueue has bounded capacity; supports multiple concurrent producers and consumers; and provides exactly-once delivery.

A RandomShuffleQueue holds a list of up to capacity elements. Each element is a fixed-length tuple of tensors whose dtypes are described by dtypes, and whose shapes are optionally described by the shapes argument.

If the shapes argument is specified, each component of a queue element must have the respective fixed shape. If it is unspecified, different queue elements may have different shapes, but the use of dequeue_many is disallowed.

The min_after_dequeue argument allows the caller to specify a minimum number of elements that will remain in the queue after a dequeue or dequeue_many operation completes, to ensure a minimum level of mixing of elements. This invariant is maintained by blocking those operations until sufficient elements have been enqueued. The min_after_dequeue argument is ignored after the queue has been closed.

Args:

• capacity: An integer. The upper bound on the number of elements that may be stored in this queue.
• min_after_dequeue: An integer (described above).
• dtypes: A list of DType objects. The length of dtypes must equal the number of tensors in each queue element.
• shapes: (Optional.) A list of fully-defined TensorShape objects with the same length as dtypes, or None.
• names: (Optional.) A list of string naming the components in the queue with the same length as dtypes, or None. If specified the dequeue methods return a dictionary with the names as keys.
• seed: A Python integer. Used to create a random seed. See set_random_seed for behavior.
• shared_name: (Optional.) If non-empty, this queue will be shared under the given name across multiple sessions.
• name: Optional name for the queue operation.