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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/python/debug | |
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/python/debug')
-rw-r--r-- | tensorflow/python/debug/examples/debug_tflearn_iris.py | 14 |
1 files changed, 8 insertions, 6 deletions
diff --git a/tensorflow/python/debug/examples/debug_tflearn_iris.py b/tensorflow/python/debug/examples/debug_tflearn_iris.py index 019f13c450..f9bb3148fb 100644 --- a/tensorflow/python/debug/examples/debug_tflearn_iris.py +++ b/tensorflow/python/debug/examples/debug_tflearn_iris.py @@ -94,13 +94,15 @@ def main(_): "sepal_length", "sepal_width", "petal_length", "petal_width", "label"] batch_size = 32 def training_input_fn(): - return tf.contrib.data.make_csv_dataset( - [training_data_path], batch_size, - column_names=column_names, label_name="label") + return tf.data.experimental.make_csv_dataset([training_data_path], + batch_size, + column_names=column_names, + label_name="label") def test_input_fn(): - return tf.contrib.data.make_csv_dataset( - [test_data_path], batch_size, - column_names=column_names, label_name="label") + return tf.data.experimental.make_csv_dataset([test_data_path], + batch_size, + column_names=column_names, + label_name="label") feature_columns = [tf.feature_column.numeric_column(feature) for feature in column_names[:-1]] |