tf.compat.v1.train.range_input_producer

Produces the integers from 0 to limit-1 in a queue. (deprecated)

tf.compat.v1.train.range_input_producer(
    limit, num_epochs=None, shuffle=True, seed=None, capacity=32, shared_name=None,
    name=None
)

Warning: 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 Instructions for updating: Queue-based input pipelines have been replaced by tf.data. Use tf.data.Dataset.range(limit).shuffle(limit).repeat(num_epochs). If shuffle=False, omit the .shuffle(...).

Note: if num_epochs is not None, this function creates local counter epochs. Use local_variables_initializer() to initialize local variables.

Args
limit	An int32 scalar tensor.
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.
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.