An integer (optional). If specified, range_input_producer
produces each integer num_epochs times before generating an
OutOfRange error. If not specified, range_input_producer can cycle
through the integers an unlimited number of times.
shuffle
Boolean. If true, the integers are randomly shuffled within each
epoch.
seed
An integer (optional). Seed used if shuffle == True.
capacity
An integer. Sets the queue capacity.
shared_name
(optional). If set, this queue will be shared under the given
name across multiple sessions.
name
A name for the operations (optional).
Returns
A Queue with the output integers. A QueueRunner for the Queue
is added to the current Graph's QUEUE_RUNNER collection.
eager compatibility
Input pipelines based on Queues are not supported when eager execution is
enabled. Please use the tf.data API to ingest data under eager execution.
[null,null,["Last updated 2024-04-26 UTC."],[],[],null,["# tf.compat.v1.train.range_input_producer\n\n\u003cbr /\u003e\n\n|------------------------------------------------------------------------------------------------------------------------------|\n| [View source on GitHub](https://github.com/tensorflow/tensorflow/blob/v2.16.1/tensorflow/python/training/input.py#L278-L317) |\n\nProduces the integers from 0 to limit-1 in a queue. (deprecated) \n\n tf.compat.v1.train.range_input_producer(\n limit,\n num_epochs=None,\n shuffle=True,\n seed=None,\n capacity=32,\n shared_name=None,\n name=None\n )\n\n| **Deprecated:** THIS FUNCTION IS DEPRECATED. It will be removed in a future version. Instructions for updating: Queue-based input pipelines have been replaced by [`tf.data`](../../../../tf/data). Use `tf.data.Dataset.range(limit).shuffle(limit).repeat(num_epochs)`. If `shuffle=False`, omit the `.shuffle(...)`.\n| **Note:** if `num_epochs` is not `None`, this function creates local counter `epochs`. Use `local_variables_initializer()` to initialize local variables.\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Args ---- ||\n|---------------|---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|\n| `limit` | An int32 scalar tensor. |\n| `num_epochs` | An integer (optional). If specified, `range_input_producer` produces each integer `num_epochs` times before generating an OutOfRange error. If not specified, `range_input_producer` can cycle through the integers an unlimited number of times. |\n| `shuffle` | Boolean. If true, the integers are randomly shuffled within each epoch. |\n| `seed` | An integer (optional). Seed used if shuffle == True. |\n| `capacity` | An integer. Sets the queue capacity. |\n| `shared_name` | (optional). If set, this queue will be shared under the given name across multiple sessions. |\n| `name` | A name for the operations (optional). |\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Returns ------- ||\n|---|---|\n| A Queue with the output integers. A `QueueRunner` for the Queue is added to the current `Graph`'s `QUEUE_RUNNER` collection. ||\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\neager compatibility\n-------------------\n\n\u003cbr /\u003e\n\nInput pipelines based on Queues are not supported when eager execution is\nenabled. Please use the [`tf.data`](../../../../tf/data) API to ingest data under eager execution.\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e"]]