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tf.contrib.training.FeedingQueueRunner

Class FeedingQueueRunner

Inherits From: QueueRunner

Defined in tensorflow/python/estimator/inputs/queues/feeding_queue_runner.py.

A queue runner that allows the feeding of values such as numpy arrays.

Properties

cancel_op

close_op

enqueue_ops

exceptions_raised

Exceptions raised but not handled by the QueueRunner threads.

Exceptions raised in queue runner threads are handled in one of two ways depending on whether or not a Coordinator was passed to create_threads():

  • With a Coordinator, exceptions are reported to the coordinator and forgotten by the QueueRunner.
  • Without a Coordinator, exceptions are captured by the QueueRunner and made available in this exceptions_raised property.

Returns:

A list of Python Exception objects. The list is empty if no exception was captured. (No exceptions are captured when using a Coordinator.)

name

The string name of the underlying Queue.

queue

queue_closed_exception_types

Methods

__init__

__init__(
    queue=None,
    enqueue_ops=None,
    close_op=None,
    cancel_op=None,
    feed_fns=None,
    queue_closed_exception_types=None
)

Initialize the queue runner.

For further documentation, see queue_runner.py. Note that FeedingQueueRunner does not support construction from protobuffer nor serialization to protobuffer.

Args:

  • queue: A Queue.
  • enqueue_ops: List of enqueue ops to run in threads later.
  • close_op: Op to close the queue. Pending enqueue ops are preserved.
  • cancel_op: Op to close the queue and cancel pending enqueue ops.
  • feed_fns: a list of functions that return a dictionary mapping fed Tensors to values. Must be the same length as enqueue_ops.
  • queue_closed_exception_types: Optional tuple of Exception types that indicate that the queue has been closed when raised during an enqueue operation. Defaults to (tf.errors.OutOfRangeError, tf.errors.CancelledError).

Raises:

  • ValueError: feed_fns is not None and has different length than enqueue_ops.

create_threads

create_threads(
    sess,
    coord=None,
    daemon=False,
    start=False
)

Create threads to run the enqueue ops for the given session.

This method requires a session in which the graph was launched. It creates a list of threads, optionally starting them. There is one thread for each op passed in enqueue_ops.

The coord argument is an optional coordinator, that the threads will use to terminate together and report exceptions. If a coordinator is given, this method starts an additional thread to close the queue when the coordinator requests a stop.

If previously created threads for the given session are still running, no new threads will be created.

Args:

  • sess: A Session.
  • coord: Optional Coordinator object for reporting errors and checking stop conditions.
  • daemon: Boolean. If True make the threads daemon threads.
  • start: Boolean. If True starts the threads. If False the caller must call the start() method of the returned threads.

Returns:

A list of threads.

from_proto

from_proto(
    queue_runner_def,
    import_scope=None
)

Returns a QueueRunner object created from queue_runner_def.

to_proto

to_proto()

Converts this QueueRunner to a QueueRunnerDef protocol buffer.

Args:

  • export_scope: Optional string. Name scope to remove.

Returns:

A QueueRunnerDef protocol buffer, or None if the Variable is not in the specified name scope.

© 2018 The TensorFlow Authors. All rights reserved.
Licensed under the Creative Commons Attribution License 3.0.
Code samples licensed under the Apache 2.0 License.
https://www.tensorflow.org/api_docs/python/tf/contrib/training/FeedingQueueRunner