Class QueueBase
Aliases:
- Class
tf.QueueBase
- Class
tf.io.QueueBase
- Class
tf.queue.QueueBase
Defined in tensorflow/python/ops/data_flow_ops.py
.
Base class for queue implementations.
A queue is a TensorFlow data structure that stores tensors across multiple steps, and exposes operations that enqueue and dequeue tensors.
Each queue element is a tuple of one or more tensors, where each tuple component has a static dtype, and may have a static shape. The queue implementations support versions of enqueue and dequeue that handle single elements, versions that support enqueuing and dequeuing a batch of elements at once.
See tf.FIFOQueue
and
tf.RandomShuffleQueue
for concrete
implementations of this class, and instructions on how to create
them.
__init__
__init__(
dtypes,
shapes,
names,
queue_ref
)
Constructs a queue object from a queue reference.
The two optional lists, shapes
and names
, must be of the same length
as dtypes
if provided. The values at a given index i
indicate the
shape and name to use for the corresponding queue component in dtypes
.
Args:
dtypes
: A list of types. The length of dtypes must equal the number of tensors in each element.shapes
: Constraints on the shapes of tensors in an element: A list of shape tuples or None. This list is the same length as dtypes. If the shape of any tensors in the element are constrained, all must be; shapes can be None if the shapes should not be constrained.names
: Optional list of names. If provided, theenqueue()
anddequeue()
methods will use dictionaries with these names as keys. Must be None or a list or tuple of the same length asdtypes
.queue_ref
: The queue reference, i.e. the output of the queue op.
Raises:
ValueError
: If one of the arguments is invalid.
Properties
dtypes
The list of dtypes for each component of a queue element.
name
The name of the underlying queue.
names
The list of names for each component of a queue element.
queue_ref
The underlying queue reference.
shapes
The list of shapes for each component of a queue element.
Methods
tf.queue.QueueBase.close
close(
cancel_pending_enqueues=False,
name=None
)
Closes this queue.
This operation signals that no more elements will be enqueued in
the given queue. Subsequent enqueue
and enqueue_many
operations will fail. Subsequent dequeue
and dequeue_many
operations will continue to succeed if sufficient elements remain
in the queue. Subsequently dequeue and dequeue_many operations
that would otherwise block waiting for more elements (if close
hadn't been called) will now fail immediately.
If cancel_pending_enqueues
is True
, all pending requests will also
be canceled.
Args:
cancel_pending_enqueues
: (Optional.) A boolean, defaulting toFalse
(described above).name
: A name for the operation (optional).
Returns:
The operation that closes the queue.
tf.queue.QueueBase.dequeue
dequeue(name=None)
Dequeues one element from this queue.
If the queue is empty when this operation executes, it will block until there is an element to dequeue.
At runtime, this operation may raise an error if the queue is
tf.QueueBase.close
before or during its execution. If the
queue is closed, the queue is empty, and there are no pending
enqueue operations that can fulfill this request,
tf.errors.OutOfRangeError
will be raised. If the session is
tf.Session.close
,
tf.errors.CancelledError
will be raised.
Args:
name
: A name for the operation (optional).
Returns:
The tuple of tensors that was dequeued.
tf.queue.QueueBase.dequeue_many
dequeue_many(
n,
name=None
)
Dequeues and concatenates n
elements from this queue.
This operation concatenates queue-element component tensors along
the 0th dimension to make a single component tensor. All of the
components in the dequeued tuple will have size n
in the 0th dimension.
If the queue is closed and there are less than n
elements left, then an
OutOfRange
exception is raised.
At runtime, this operation may raise an error if the queue is
tf.QueueBase.close
before or during its execution. If the
queue is closed, the queue contains fewer than n
elements, and
there are no pending enqueue operations that can fulfill this
request, tf.errors.OutOfRangeError
will be raised. If the
session is tf.Session.close
,
tf.errors.CancelledError
will be raised.
Args:
n
: A scalarTensor
containing the number of elements to dequeue.name
: A name for the operation (optional).
Returns:
The list of concatenated tensors that was dequeued.
tf.queue.QueueBase.dequeue_up_to
dequeue_up_to(
n,
name=None
)
Dequeues and concatenates n
elements from this queue.
Note This operation is not supported by all queues. If a queue does not
support DequeueUpTo, then a tf.errors.UnimplementedError
is raised.
This operation concatenates queue-element component tensors along
the 0th dimension to make a single component tensor. If the queue
has not been closed, all of the components in the dequeued tuple
will have size n
in the 0th dimension.
If the queue is closed and there are more than 0
but fewer than
n
elements remaining, then instead of raising a
tf.errors.OutOfRangeError
like tf.QueueBase.dequeue_many
,
less than n
elements are returned immediately. If the queue is
closed and there are 0
elements left in the queue, then a
tf.errors.OutOfRangeError
is raised just like in dequeue_many
.
Otherwise the behavior is identical to dequeue_many
.
Args:
n
: A scalarTensor
containing the number of elements to dequeue.name
: A name for the operation (optional).
Returns:
The tuple of concatenated tensors that was dequeued.
tf.queue.QueueBase.enqueue
enqueue(
vals,
name=None
)
Enqueues one element to this queue.
If the queue is full when this operation executes, it will block until the element has been enqueued.
At runtime, this operation may raise an error if the queue is
tf.QueueBase.close
before or during its execution. If the
queue is closed before this operation runs,
tf.errors.CancelledError
will be raised. If this operation is
blocked, and either (i) the queue is closed by a close operation
with cancel_pending_enqueues=True
, or (ii) the session is
tf.Session.close
,
tf.errors.CancelledError
will be raised.
Args:
vals
: A tensor, a list or tuple of tensors, or a dictionary containing the values to enqueue.name
: A name for the operation (optional).
Returns:
The operation that enqueues a new tuple of tensors to the queue.
tf.queue.QueueBase.enqueue_many
enqueue_many(
vals,
name=None
)
Enqueues zero or more elements to this queue.
This operation slices each component tensor along the 0th dimension to
make multiple queue elements. All of the tensors in vals
must have the
same size in the 0th dimension.
If the queue is full when this operation executes, it will block until all of the elements have been enqueued.
At runtime, this operation may raise an error if the queue is
tf.QueueBase.close
before or during its execution. If the
queue is closed before this operation runs,
tf.errors.CancelledError
will be raised. If this operation is
blocked, and either (i) the queue is closed by a close operation
with cancel_pending_enqueues=True
, or (ii) the session is
tf.Session.close
,
tf.errors.CancelledError
will be raised.
Args:
vals
: A tensor, a list or tuple of tensors, or a dictionary from which the queue elements are taken.name
: A name for the operation (optional).
Returns:
The operation that enqueues a batch of tuples of tensors to the queue.
tf.queue.QueueBase.from_list
@staticmethod
from_list(
index,
queues
)
Create a queue using the queue reference from queues[index]
.
Args:
index
: An integer scalar tensor that determines the input that gets selected.queues
: A list ofQueueBase
objects.
Returns:
A QueueBase
object.
Raises:
TypeError
: Whenqueues
is not a list ofQueueBase
objects, or when the data types ofqueues
are not all the same.
tf.queue.QueueBase.is_closed
is_closed(name=None)
Returns true if queue is closed.
This operation returns true if the queue is closed and false if the queue is open.
Args:
name
: A name for the operation (optional).
Returns:
True if the queue is closed and false if the queue is open.
tf.queue.QueueBase.size
size(name=None)
Compute the number of elements in this queue.
Args:
name
: A name for the operation (optional).
Returns:
A scalar tensor containing the number of elements in this queue.