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 Instructions for updating: Queue-based input pipelines have been replaced by tf.data.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.