parameters: (self, capacity, types, shapes=None, names=None, shared_name=None,
                 name="priority_queue")
docstring: 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.
docstring_summary: Creates a queue that dequeues elements in a first-in first-out order.
docstring_tokens: Creates a queue that dequeues elements in a first - in first - out order .
function: def __init__(self, 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.
      """
      types = _as_type_list(types)
      shapes = _as_shape_list(shapes, types)
  
      queue_ref = gen_data_flow_ops._priority_queue_v2(
          component_types=types, shapes=shapes, capacity=capacity,
          shared_name=shared_name, name=name)
  
      priority_dtypes = [_dtypes.int64] + types
      priority_shapes = [()] + shapes if shapes else shapes
  
      super(PriorityQueue, self).__init__(
          priority_dtypes, priority_shapes, names, queue_ref)
function_tokens: def __init__ ( self , capacity , types , shapes = None , names = None , shared_name = None , name = "priority_queue" ) : types = _as_type_list ( types ) shapes = _as_shape_list ( shapes , types ) queue_ref = gen_data_flow_ops . _priority_queue_v2 ( component_types = types , shapes = shapes , capacity = capacity , shared_name = shared_name , name = name ) priority_dtypes = [ _dtypes . int64 ] + types priority_shapes = [ ( ) ] + shapes if shapes else shapes super ( PriorityQueue , self ) . __init__ ( priority_dtypes , priority_shapes , names , queue_ref )