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author | A. Unique TensorFlower <gardener@tensorflow.org> | 2018-09-11 17:12:11 -0700 |
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committer | TensorFlower Gardener <gardener@tensorflow.org> | 2018-09-11 17:19:51 -0700 |
commit | ed7ae86228c58e0a32f0dc21aedc9dad62db97c7 (patch) | |
tree | 48177388b001ef2f817606766bcd73aff4fda4a8 /tensorflow/python/data | |
parent | 7ac29a47561493a7f775cea5b03fe7284f1fa1b7 (diff) |
Automated rollback of commit d31f360e1574553ed23b8d483512a2065ac426eb
PiperOrigin-RevId: 212551965
Diffstat (limited to 'tensorflow/python/data')
-rw-r--r-- | tensorflow/python/data/util/nest.py | 34 |
1 files changed, 4 insertions, 30 deletions
diff --git a/tensorflow/python/data/util/nest.py b/tensorflow/python/data/util/nest.py index 9d621fcd30..e5abc654da 100644 --- a/tensorflow/python/data/util/nest.py +++ b/tensorflow/python/data/util/nest.py @@ -96,37 +96,11 @@ def _yield_value(iterable): yield value -def is_sequence(seq): - """Returns a true if `seq` is a Sequence or dict (except strings/lists). +# See the swig file (../../util/util.i) for documentation. +is_sequence = _pywrap_tensorflow.IsSequenceForData - NOTE(mrry): This differs from `tensorflow.python.util.nest.is_sequence()`, - which *does* treat a Python list as a sequence. For ergonomic - reasons, `tf.data` users would prefer to treat lists as - implicit `tf.Tensor` objects, and dicts as (nested) sequences. - - Args: - seq: an input sequence. - - Returns: - True if the sequence is a not a string or list and is a - collections.Sequence. - """ - return _pywrap_tensorflow.IsSequenceForData(seq) - - -def flatten(nest): - """Returns a flat sequence from a given nested structure. - - If `nest` is not a sequence, this returns a single-element list: `[nest]`. - - Args: - nest: an arbitrarily nested structure or a scalar object. - Note, numpy arrays are considered scalars. - - Returns: - A Python list, the flattened version of the input. - """ - return _pywrap_tensorflow.FlattenForData(nest) +# See the swig file (../../util/util.i) for documentation. +flatten = _pywrap_tensorflow.FlattenForData def assert_same_structure(nest1, nest2, check_types=True): |