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author | Derek Murray <mrry@google.com> | 2018-10-01 16:45:11 -0700 |
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committer | TensorFlower Gardener <gardener@tensorflow.org> | 2018-10-01 16:50:05 -0700 |
commit | b72265dc002e712fc3d0f33434f13c7a36a484b2 (patch) | |
tree | f92d1f23c329654772f95d93f5cf4458741b72df /tensorflow/contrib/eager | |
parent | bb1f9e1a57c8bc18325b3c86298be96e6647a0a3 (diff) |
[tf.data] Deprecate `tf.contrib.data` and introduce `tf.data.experimental` to replace it.
This change prepares `tf.data` for TensorFlow 2.0, where `tf.contrib` will no longer exist. It retains the pre-existing endpoints in `tf.contrib.data` with deprecation warnings.
Note there are some exceptions to the move:
* Deprecated symbols in `tf.contrib.data` have not been moved to `tf.data.experimental`, because replacements already exist.
* `tf.contrib.data.LMDBDataset` has not been moved, because we plan to move it to a SIG-maintained repository.
* `tf.contrib.data.assert_element_shape()` has not yet been moved, because it depends on functionality in `tf.contrib`, and it will move in a later change.
* `tf.contrib.data.AUTOTUNE` has not yet been moved, because we have not yet determined how to `tf_export()` a Python integer.
* The stats-related API endpoints have not yet appeared in a released version of TensorFlow, so these are moved to `tf.data.experimental` without retaining an endpoint in `tf.contrib.data`.
In addition, this change includes some build rule and ApiDef refactoring:
* Some of the "//third_party/tensorflow/python:training" dependencies had to be split in order to avoid a circular dependency.
* The `tf.contrib.stateless` ops now have a private core library for the generated wrappers (and accordingly are hidden in their ApiDef) so that `tf.data.experimental.sample_from_datasets()` can depend on them.
PiperOrigin-RevId: 215304249
Diffstat (limited to 'tensorflow/contrib/eager')
-rw-r--r-- | tensorflow/contrib/eager/python/datasets.py | 4 | ||||
-rw-r--r-- | tensorflow/contrib/eager/python/datasets_test.py | 6 | ||||
-rw-r--r-- | tensorflow/contrib/eager/python/examples/revnet/imagenet_input.py | 12 |
3 files changed, 12 insertions, 10 deletions
diff --git a/tensorflow/contrib/eager/python/datasets.py b/tensorflow/contrib/eager/python/datasets.py index 135095a979..3aed121233 100644 --- a/tensorflow/contrib/eager/python/datasets.py +++ b/tensorflow/contrib/eager/python/datasets.py @@ -18,7 +18,7 @@ from __future__ import absolute_import from __future__ import division from __future__ import print_function -from tensorflow.contrib.data.python.ops import prefetching_ops +from tensorflow.python.data.experimental.ops import prefetching_ops from tensorflow.python.data.ops import iterator_ops from tensorflow.python.eager import context from tensorflow.python.framework import ops @@ -54,7 +54,7 @@ class Iterator(iterator_ops.EagerIterator): """ if isinstance(dataset, prefetching_ops._PrefetchToDeviceDataset): # pylint: disable=protected-access raise TypeError( - "`tf.contrib.data.prefetch_to_device()` is not compatible with " + "`tf.data.experimental.prefetch_to_device()` is not compatible with " "`tf.contrib.eager.Iterator`. Use `for ... in dataset:` to iterate " "over the dataset instead.") diff --git a/tensorflow/contrib/eager/python/datasets_test.py b/tensorflow/contrib/eager/python/datasets_test.py index a753d77580..6a508fc6ba 100644 --- a/tensorflow/contrib/eager/python/datasets_test.py +++ b/tensorflow/contrib/eager/python/datasets_test.py @@ -24,11 +24,11 @@ import time import numpy as np from tensorflow.contrib import lookup -from tensorflow.contrib.data.python.ops import prefetching_ops -from tensorflow.contrib.data.python.ops import threadpool -from tensorflow.contrib.data.python.ops import unique from tensorflow.contrib.eager.python import datasets from tensorflow.python.data import Dataset +from tensorflow.python.data.experimental.ops import prefetching_ops +from tensorflow.python.data.experimental.ops import threadpool +from tensorflow.python.data.experimental.ops import unique from tensorflow.python.eager import test from tensorflow.python.framework import constant_op from tensorflow.python.framework import dtypes diff --git a/tensorflow/contrib/eager/python/examples/revnet/imagenet_input.py b/tensorflow/contrib/eager/python/examples/revnet/imagenet_input.py index 34a9984b0e..d85188de03 100644 --- a/tensorflow/contrib/eager/python/examples/revnet/imagenet_input.py +++ b/tensorflow/contrib/eager/python/examples/revnet/imagenet_input.py @@ -169,11 +169,11 @@ class ImageNetInput(object): # Read the data from disk in parallel dataset = dataset.apply( - tf.contrib.data.parallel_interleave( + tf.data.experimental.parallel_interleave( fetch_dataset, cycle_length=self.num_parallel_calls, sloppy=True)) if self.cache: dataset = dataset.cache().apply( - tf.contrib.data.shuffle_and_repeat(1024 * 16)) + tf.data.experimental.shuffle_and_repeat(1024 * 16)) else: dataset = dataset.shuffle(1024) @@ -188,9 +188,11 @@ class ImageNetInput(object): # batch size. As long as this validation is done with consistent batch size, # exactly the same images will be used. dataset = dataset.apply( - tf.contrib.data.map_and_batch( - self.dataset_parser, batch_size=batch_size, - num_parallel_batches=self.num_cores, drop_remainder=True)) + tf.data.experimental.map_and_batch( + self.dataset_parser, + batch_size=batch_size, + num_parallel_batches=self.num_cores, + drop_remainder=True)) # Transpose for performance on TPU if self.transpose_input: |