tf.contrib.training.FeedingQueueRunner
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A queue runner that allows the feeding of values such as numpy arrays.
Inherits From: QueueRunner
tf.contrib.training.FeedingQueueRunner(
queue=None, enqueue_ops=None, close_op=None, cancel_op=None, feed_fns=None,
queue_closed_exception_types=None
)
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.
|
Attributes |
|---|
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.
|
name
|
The string name of the underlying Queue.
|
queue
|
|
queue_closed_exception_types
|
|
Methods
create_threads
View source
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
View source
@staticmethod
from_proto(
queue_runner_def, import_scope=None
)
Returns a QueueRunner object created from queue_runner_def.
to_proto
View source
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.
|
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Last updated 2020-10-01 UTC.
[[["Easy to understand","easyToUnderstand","thumb-up"],["Solved my problem","solvedMyProblem","thumb-up"],["Other","otherUp","thumb-up"]],[["Missing the information I need","missingTheInformationINeed","thumb-down"],["Too complicated / too many steps","tooComplicatedTooManySteps","thumb-down"],["Out of date","outOfDate","thumb-down"],["Samples / code issue","samplesCodeIssue","thumb-down"],["Other","otherDown","thumb-down"]],["Last updated 2020-10-01 UTC."],[],[],null,["# tf.contrib.training.FeedingQueueRunner\n\n\u003cbr /\u003e\n\n|----------------------------------------------------------------------------------------------------------------------------------------------------------|\n| [View source on GitHub](https://github.com/tensorflow/estimator/tree/master/tensorflow_estimator/python/estimator/inputs/queues/feeding_queue_runner.py) |\n\nA queue runner that allows the feeding of values such as numpy arrays.\n\nInherits From: [`QueueRunner`](../../../tf/train/queue_runner/QueueRunner) \n\n tf.contrib.training.FeedingQueueRunner(\n queue=None, enqueue_ops=None, close_op=None, cancel_op=None, feed_fns=None,\n queue_closed_exception_types=None\n )\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Args ---- ||\n|--------------------------------|----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|\n| `queue` | A `Queue`. |\n| `enqueue_ops` | List of enqueue ops to run in threads later. |\n| `close_op` | Op to close the queue. Pending enqueue ops are preserved. |\n| `cancel_op` | Op to close the queue and cancel pending enqueue ops. |\n| `feed_fns` | a list of functions that return a dictionary mapping fed `Tensor`s to values. Must be the same length as `enqueue_ops`. |\n| `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)`. |\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Raises ------ ||\n|--------------|-----------------------------------------------------------------------|\n| `ValueError` | `feed_fns` is not `None` and has different length than `enqueue_ops`. |\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Attributes ---------- ||\n|--------------------------------|-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|\n| `cancel_op` | \u003cbr /\u003e \u003cbr /\u003e |\n| `close_op` | \u003cbr /\u003e \u003cbr /\u003e |\n| `enqueue_ops` | \u003cbr /\u003e \u003cbr /\u003e |\n| `exceptions_raised` | Exceptions raised but not handled by the `QueueRunner` threads. \u003cbr /\u003e 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. |\n| `name` | The string name of the underlying Queue. |\n| `queue` | \u003cbr /\u003e |\n| `queue_closed_exception_types` | \u003cbr /\u003e \u003cbr /\u003e |\n\n\u003cbr /\u003e\n\nMethods\n-------\n\n### `create_threads`\n\n[View source](https://github.com/tensorflow/estimator/tree/master/tensorflow_estimator/python/estimator/inputs/queues/feeding_queue_runner.py) \n\n create_threads(\n sess, coord=None, daemon=False, start=False\n )\n\nCreate threads to run the enqueue ops for the given session.\n\nThis method requires a session in which the graph was launched. It creates\na list of threads, optionally starting them. There is one thread for each\nop passed in `enqueue_ops`.\n\nThe `coord` argument is an optional coordinator, that the threads will use\nto terminate together and report exceptions. If a coordinator is given,\nthis method starts an additional thread to close the queue when the\ncoordinator requests a stop.\n\nIf previously created threads for the given session are still running, no\nnew threads will be created.\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Args ||\n|----------|----------------------------------------------------------------------------------------------------------------------|\n| `sess` | A `Session`. |\n| `coord` | Optional `Coordinator` object for reporting errors and checking stop conditions. |\n| `daemon` | Boolean. If `True` make the threads daemon threads. |\n| `start` | Boolean. If `True` starts the threads. If `False` the caller must call the `start()` method of the returned threads. |\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Returns ||\n|---|---|\n| A list of threads. ||\n\n\u003cbr /\u003e\n\n### `from_proto`\n\n[View source](https://github.com/tensorflow/tensorflow/blob/v1.15.0/tensorflow/python/training/queue_runner_impl.py#L387-L391) \n\n @staticmethod\n from_proto(\n queue_runner_def, import_scope=None\n )\n\nReturns a `QueueRunner` object created from `queue_runner_def`.\n\n### `to_proto`\n\n[View source](https://github.com/tensorflow/estimator/tree/master/tensorflow_estimator/python/estimator/inputs/queues/feeding_queue_runner.py) \n\n to_proto()\n\nConverts this `QueueRunner` to a `QueueRunnerDef` protocol buffer.\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Args ||\n|----------------|------------------------------------------|\n| `export_scope` | Optional `string`. Name scope to remove. |\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Returns ||\n|---|---|\n| A `QueueRunnerDef` protocol buffer, or `None` if the `Variable` is not in the specified name scope. ||\n\n\u003cbr /\u003e"]]
View source on GitHub