tf.contrib.learn.read_keyed_batch_examples_shared_queue

tf.contrib.learn.read_keyed_batch_examples_shared_queue(
    file_pattern,
    batch_size,
    reader,
    randomize_input=True,
    num_epochs=None,
    queue_capacity=10000,
    num_threads=1,
    read_batch_size=1,
    parse_fn=None,
    name=None,
    seed=None
)

Defined in tensorflow/contrib/learn/python/learn/learn_io/graph_io.py.

Adds operations to read, queue, batch Example protos. (deprecated)

THIS FUNCTION IS DEPRECATED. It will be removed in a future version. Instructions for updating: Use tf.data.

Given file pattern (or list of files), will setup a shared queue for file names, setup a worker queue that pulls from the shared queue, read Example protos using provided reader, use batch queue to create batches of examples of size batch_size. This provides at most once visit guarantees. Note that this only works if the parameter servers are not pre-empted or restarted or the session is not restored from a checkpoint since the state of a queue is not checkpointed and we will end up restarting from the entire list of files.

All queue runners are added to the queue runners collection, and may be started via start_queue_runners.

All ops are added to the default graph.

Use parse_fn if you need to do parsing / processing on single examples.

Args:

• file_pattern: List of files or patterns of file paths containing Example records. See tf.gfile.Glob for pattern rules.
• batch_size: An int or scalar Tensor specifying the batch size to use.
• reader: A function or class that returns an object with read method, (filename tensor) -> (example tensor).
• randomize_input: Whether the input should be randomized.
• num_epochs: Integer specifying the number of times to read through the dataset. If None, cycles through the dataset forever. NOTE - If specified, creates a variable that must be initialized, so call tf.local_variables_initializer() and run the op in a session.
• queue_capacity: Capacity for input queue.
• num_threads: The number of threads enqueuing examples.
• read_batch_size: An int or scalar Tensor specifying the number of records to read at once.
• parse_fn: Parsing function, takes Example Tensor returns parsed representation. If None, no parsing is done.
• name: Name of resulting op.
• seed: An integer (optional). Seed used if randomize_input == True.

Returns:

Returns tuple of: - Tensor of string keys. - String Tensor of batched Example proto.

Raises:

• ValueError: for invalid inputs.