IO

Pipeline functions

# TensorFlow.train.add_queue_runner — Function.

add_queue_runner(runner::QueueRunner)

Manually adds a queue runner to the graph's collection of queue runners. All runners in the collection will be executed in parallel when start_queue_runners is invoked.

# TensorFlow.train.start_queue_runners — Function.

start_queue_runners(session::Session)

Run all queue runners in parallel that were previously added to the graph's collection of queue runners via add_queue_runner.

Args:

• session: The TensorFlow session containing the queues

# TensorFlow.train.range_input_producer — Function.

range_input_producer(limit; num_epochs=nothing, do_shuffle=true, seed=0, capacity=32)

Produces the integers from 1 to limit in a queue.

Args:

• limit: Inclusive upper bound on the endpoint of the range of integers to produce
• num_epochs: Number of times to produce the integers.
• do_shuffle
• seed
• capacity

# TensorFlow.train.input_producer — Function.

input_producer(input; element_shape=nothing, num_epochs=nothing, do_shuffle=true, seed=0, capacity=32)

# TensorFlow.train.string_input_producer — Function.

string_input_producer(string_tensors; num_epochs=nothing, do_shuffle=true, seed=0, capacity=32)

# TensorFlow.train.shuffle_batch — Function.

shuffle_batch(tensors, batch_size; capacity=32, enqueue_many=false, shapes=nothing, dynamic_pad=false, allow_smaller_final_batch=false)

# TensorFlow.train.QueueRunner — Type.

QueueRunner

Represents an object that continually enqueues elements to a TensorFlow queue in parallel with other operations.

# TensorFlow.train.create_threads — Function.

create_threads(runner::QueueRunner, session::Session)

Creates tasks that run the enqueue operations in runner in parallel.

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