experiments/STT-tensorflow
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Change back the default value of read_batch_size: by default examples are read in batch of length batch_size.

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Change: 126307626
This commit is contained in:
A. Unique TensorFlower 2016-06-30 07:59:45 -08:00 committed by TensorFlower Gardener
parent 2cd93cab24
commit fdc2d055da
1 changed files with 4 additions and 9 deletions

13
tensorflow/contrib/learn/python/learn/io/graph_io.py
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@ -216,7 +216,7 @@ def read_keyed_batch_features(
file_pattern, batch_size, features, reader, file_pattern, batch_size, features, reader,
randomize_input=True, num_epochs=None, randomize_input=True, num_epochs=None,
queue_capacity=10000, reader_num_threads=1, queue_capacity=10000, reader_num_threads=1,
parser_num_threads=1, read_batch_size=1, name=None): parser_num_threads=1, name=None):
"""Adds operations to read, queue, batch and parse `Example` protos. """Adds operations to read, queue, batch and parse `Example` protos.
Given file pattern (or list of files), will setup a queue for file names, Given file pattern (or list of files), will setup a queue for file names,
@ -245,8 +245,6 @@ def read_keyed_batch_features(
queue_capacity: Capacity for input queue. queue_capacity: Capacity for input queue.
reader_num_threads: The number of threads to read examples. reader_num_threads: The number of threads to read examples.
parser_num_threads: The number of threads to parse examples. parser_num_threads: The number of threads to parse examples.
read_batch_size: An int or scalar `Tensor` specifying the number of
records to read at once
name: Name of resulting op. name: Name of resulting op.
Returns: Returns:
@ -260,7 +258,7 @@ def read_keyed_batch_features(
keys, examples = read_keyed_batch_examples( keys, examples = read_keyed_batch_examples(
file_pattern, batch_size, reader, randomize_input=randomize_input, file_pattern, batch_size, reader, randomize_input=randomize_input,
num_epochs=num_epochs, queue_capacity=queue_capacity, num_epochs=num_epochs, queue_capacity=queue_capacity,
num_threads=reader_num_threads, read_batch_size=read_batch_size, num_threads=reader_num_threads, read_batch_size=batch_size,
name=scope) name=scope)
if parser_num_threads == 1: if parser_num_threads == 1:
@ -286,8 +284,7 @@ def read_keyed_batch_features(
def read_batch_features(file_pattern, batch_size, features, reader, def read_batch_features(file_pattern, batch_size, features, reader,
randomize_input=True, num_epochs=None, randomize_input=True, num_epochs=None,
queue_capacity=10000, reader_num_threads=1, queue_capacity=10000, reader_num_threads=1,
parser_num_threads=1, read_batch_size=1, parser_num_threads=1, name=None):
name=None):
"""Adds operations to read, queue, batch and parse `Example` protos. """Adds operations to read, queue, batch and parse `Example` protos.
Given file pattern (or list of files), will setup a queue for file names, Given file pattern (or list of files), will setup a queue for file names,
@ -316,7 +313,6 @@ def read_batch_features(file_pattern, batch_size, features, reader,
queue_capacity: Capacity for input queue. queue_capacity: Capacity for input queue.
reader_num_threads: The number of threads to read examples. reader_num_threads: The number of threads to read examples.
parser_num_threads: The number of threads to parse examples. parser_num_threads: The number of threads to parse examples.
read_batch_size: An int or scalar `Tensor` specifying the number of
records to read at once records to read at once
name: Name of resulting op. name: Name of resulting op.
@ -331,8 +327,7 @@ def read_batch_features(file_pattern, batch_size, features, reader,
file_pattern, batch_size, features, reader, file_pattern, batch_size, features, reader,
randomize_input=randomize_input, num_epochs=num_epochs, randomize_input=randomize_input, num_epochs=num_epochs,
queue_capacity=queue_capacity, reader_num_threads=reader_num_threads, queue_capacity=queue_capacity, reader_num_threads=reader_num_threads,
parser_num_threads=parser_num_threads, read_batch_size=read_batch_size, parser_num_threads=parser_num_threads, name=name)
name=name)
return features return features