tf.PriorityQueue.__init__()

tf.PriorityQueue.__init__(capacity, types, shapes=None, names=None, shared_name=None, name='priority_queue')

Creates a queue that dequeues elements in a first-in first-out order.

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

A PriorityQueue holds a list of up to capacity elements. Each element is a fixed-length tuple of tensors whose dtypes are described by types, 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.

Enqueues and Dequeues to the PriorityQueue must include an additional tuple entry at the beginning: the priority. The priority must be an int64 scalar (for enqueue) or an int64 vector (for enqueue_many).

Args:

• capacity: An integer. The upper bound on the number of elements that may be stored in this queue.
• types: A list of DType objects. The length of types must equal the number of tensors in each queue element, except the first priority element. The first tensor in each element is the priority, which must be type int64.
• shapes: (Optional.) A list of fully-defined TensorShape objects, with the same length as types, or None.
• names: (Optional.) A list of strings 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.
• 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.