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[tf.data] Improve TFRecordDataset documentation.

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PiperOrigin-RevId: 239019801
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Jiri Simsa 2019-03-18 11:02:04 -07:00 committed by TensorFlower Gardener
parent 5b2c54de04
commit 128add4e08
1 changed files with 8 additions and 6 deletions
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14
tensorflow/python/data/ops/readers.py
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@ -178,19 +178,21 @@ class TFRecordDatasetV2(dataset_ops.DatasetV2):
num_parallel_reads=None):
"""Creates a `TFRecordDataset` to read one or more TFRecord files.
NOTE: The `num_parallel_reads` argument can be used to improve performance
when reading from a remote filesystem.
Args:
filenames: A `tf.string` tensor or `tf.data.Dataset` containing one or
more filenames.
compression_type: (Optional.) A `tf.string` scalar evaluating to one of
`""` (no compression), `"ZLIB"`, or `"GZIP"`.
buffer_size: (Optional.) A `tf.int64` scalar representing the number of
bytes in the read buffer. 0 means no buffering.
bytes in the read buffer. If your input pipeline is I/O bottlenecked,
consider setting this parameter to a value 1-100 MBs. If `None`, a
sensible default for both local and remote file systems is used.
num_parallel_reads: (Optional.) A `tf.int64` scalar representing the
number of files to read in parallel. Defaults to reading files
sequentially.
number of files to read in parallel. If greater than one, the records of
files read in parallel are outputted in an interleaved order. If your
input pipeline is I/O bottlenecked, consider setting this parameter to a
value greater than one to parallelize the I/O. If `None`, files will be
read sequentially.
Raises:
TypeError: If any argument does not have the expected type.