![]() |
Reads TFRecord, queues, batches and parses Example
proto. (deprecated)
tf.contrib.learn.read_batch_record_features(
file_pattern, batch_size, features, randomize_input=True, num_epochs=None,
queue_capacity=10000, reader_num_threads=1, name='dequeue_record_examples'
)
See more detailed description in read_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.
|
features
|
A dict mapping feature keys to FixedLenFeature or
VarLenFeature values.
|
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. |
reader_num_threads
|
The number of threads to read examples. In order to have
predictable and repeatable order of reading and enqueueing, such as in
prediction and evaluation mode, reader_num_threads should be 1.
|
name
|
Name of resulting op. |
Returns | |
---|---|
A dict of Tensor or SparseTensor objects for each in features .
|
Raises | |
---|---|
ValueError
|
for invalid inputs. |