View source on GitHub |

A queue implementation that dequeues elements in a random order.

Inherits From: `QueueBase`

tf.queue.RandomShuffleQueue( capacity, min_after_dequeue, dtypes, shapes=None, names=None, seed=None, shared_name=None, name='random_shuffle_queue' )

See `tf.queue.QueueBase`

for a description of the methods on this class.

Args | |
---|---|

`capacity` | An integer. The upper bound on the number of elements that may be stored in this queue. |

`min_after_dequeue` | An integer (described above). |

`dtypes` | A list of `DType` objects. The length of `dtypes` must equal the number of tensors in each queue element. |

`shapes` | (Optional.) A list of fully-defined `TensorShape` objects with the same length as `dtypes` , or `None` . |

`names` | (Optional.) A list of string 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. |

`seed` | A Python integer. Used to create a random seed. See `tf.compat.v1.set_random_seed` for behavior. |

`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. |

Attributes | |
---|---|

`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. |

`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 to `False` (described above). |

`name` | A name for the operation (optional). |

Returns | |
---|---|

The operation that closes the queue. |

`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. |

`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 scalar `Tensor` containing the number of elements to dequeue. |

`name` | A name for the operation (optional). |

Returns | |
---|---|

The list of concatenated tensors that was dequeued. |

`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 scalar `Tensor` containing the number of elements to dequeue. |

`name` | A name for the operation (optional). |

Returns | |
---|---|

The tuple of concatenated tensors that was dequeued. |

`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. |

`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. |

`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 of `QueueBase` objects. |

Returns | |
---|---|

A `QueueBase` object. |

Raises | |
---|---|

`TypeError` | When `queues` is not a list of `QueueBase` objects, or when the data types of `queues` are not all the same. |

`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. |

`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. |

© 2020 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/versions/r2.4/api_docs/python/tf/queue/RandomShuffleQueue