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[tf.data] Add documentation for supporting tf.data.experimental.AUTOTUNE as a value for the num_parallel_calls argument of map(), interleave(), and map_and_batch().

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PiperOrigin-RevId: 224381264
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Jiri Simsa 2018-12-06 12:00:29 -08:00 committed by TensorFlower Gardener
parent 0fb46cf913
commit 2947a28510
2 changed files with 10 additions and 5 deletions
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5
tensorflow/python/data/experimental/ops/batching.py
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@ -627,8 +627,9 @@ def map_and_batch(map_func,
desired; the default behavior is not to drop the smaller batch. desired; the default behavior is not to drop the smaller batch.
num_parallel_calls: (Optional.) A `tf.int32` scalar `tf.Tensor`, num_parallel_calls: (Optional.) A `tf.int32` scalar `tf.Tensor`,
representing the number of elements to process in parallel. If not representing the number of elements to process in parallel. If not
specified, `batch_size * num_parallel_batches` elements will be specified, `batch_size * num_parallel_batches` elements will be processed
processed in parallel. in parallel. If the value `tf.data.experimental.AUTOTUNE` is used, then
the number of parallel calls is set dynamically based on available CPU.
Returns: Returns:
A `Dataset` transformation function, which can be passed to A `Dataset` transformation function, which can be passed to

8
tensorflow/python/data/ops/dataset_ops.py
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@ -947,7 +947,9 @@ class DatasetV2(object):
`self.output_types`) to another nested structure of tensors. `self.output_types`) to another nested structure of tensors.
num_parallel_calls: (Optional.) A `tf.int32` scalar `tf.Tensor`, num_parallel_calls: (Optional.) A `tf.int32` scalar `tf.Tensor`,
representing the number elements to process in parallel. If not representing the number elements to process in parallel. If not
specified, elements will be processed sequentially. specified, elements will be processed sequentially. If the value
`tf.data.experimental.AUTOTUNE` is used, then the number of parallel
calls is set dynamically based on available CPU.
Returns: Returns:
Dataset: A `Dataset`. Dataset: A `Dataset`.
@ -1058,7 +1060,9 @@ class DatasetV2(object):
num_parallel_calls: (Optional.) If specified, the implementation creates num_parallel_calls: (Optional.) If specified, the implementation creates
a threadpool, which is used to fetch inputs from cycle elements a threadpool, which is used to fetch inputs from cycle elements
asynchronously and in parallel. The default behavior is to fetch inputs asynchronously and in parallel. The default behavior is to fetch inputs
from cycle elements synchronously with no parallelism. from cycle elements synchronously with no parallelism. If the value
`tf.data.experimental.AUTOTUNE` is used, then the number of parallel
calls is set dynamically based on available CPU.
Returns: Returns:
Dataset: A `Dataset`. Dataset: A `Dataset`.