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

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

See the guide: Inputs and Readers > Input pipeline

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

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.

Defined in tensorflow/python/training/input.py.