def dequeue(self, 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.
Args:
name: A name for the operation (optional).
Returns:
The tuple of tensors that was dequeued.
"""
if name is None:
name = "%s_Dequeue" % self._name
ret = gen_data_flow_ops._queue_dequeue(self._queue_ref,
self._dtypes,
name=name)
# NOTE(mrry): Not using a shape function because we need access to
# the `QueueBase` object.
op = ret[0].op
for output, shape in zip(op.values(), self._shapes):
output.set_shape(shape)
return ret if len(ret) != 1 else ret[0]
def dequeue(self, 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
[closed](#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 fulfil this request,
`tf.errors.OutOfRangeError` will be raised. If the session is
[closed](../../api_docs/python/client.md#Session.close),
`tf.errors.CancelledError` will be raised.
Args:
name: A name for the operation (optional).
Returns:
The tuple of tensors that was dequeued.
"""
if name is None:
name = "%s_Dequeue" % self._name
ret = gen_data_flow_ops._queue_dequeue(
self._queue_ref, self._dtypes, name=name)
# NOTE(mrry): Not using a shape function because we need access to
# the `QueueBase` object.
op = ret[0].op
for output, shape in zip(op.values(), self._shapes):
output.set_shape(shape)
return self._dequeue_return_value(ret)
def dequeue(self, 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
[closed](#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 fulfil this request,
`tf.errors.OutOfRangeError` will be raised. If the session is
[closed](../../api_docs/python/client.md#Session.close),
`tf.errors.CancelledError` will be raised.
Args:
name: A name for the operation (optional).
Returns:
The tuple of tensors that was dequeued.
"""
if name is None:
name = "%s_Dequeue" % self._name
ret = gen_data_flow_ops._queue_dequeue(self._queue_ref,
self._dtypes,
name=name)
# NOTE(mrry): Not using a shape function because we need access to
# the `QueueBase` object.
op = ret[0].op
for output, shape in zip(op.values(), self._shapes):
output.set_shape(shape)
return self._dequeue_return_value(ret)
def dequeue(self, 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.
Args:
name: A name for the operation (optional).
Returns:
The tuple of tensors that was dequeued.
"""
if name is None:
name = "%s_Dequeue" % self._name
ret = gen_data_flow_ops._queue_dequeue(self._queue_ref, self._dtypes, name=name)
# NOTE(mrry): Not using a shape function because we need access to
# the `QueueBase` object.
op = ret[0].op
for output, shape in zip(op.values(), self._shapes):
output.set_shape(shape)
return ret if len(ret) != 1 else ret[0]