View source on GitHub |
Adds operations to read, queue, batch Example
protos. (deprecated)
tf.contrib.learn.read_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.
Args | |
---|---|
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 | |
---|---|
String Tensor of batched Example proto.
|
Raises | |
---|---|
ValueError
|
for invalid inputs. |