tf.contrib.learn.read_keyed_batch_examples

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

tf.contrib.learn.read_keyed_batch_examples(
    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
)

Given file pattern (or list of files), will setup a queue for file names, read Example proto using provided reader, use batch queue to create batches of examples of size batch_size.

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.

file_pattern List of files or patterns of file paths containing Example records. See tf.io.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.compat.v1.local_variables_initializer() and run the op in a session.
queue_capacity Capacity for input queue.
num_threads The number of threads enqueuing examples. In order to have predictable and repeatable order of reading and enqueueing, such as in prediction and evaluation mode, num_threads should be 1.
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 tuple of:

  • Tensor of string keys.
  • String Tensor of batched Example proto.

ValueError for invalid inputs.