/
unique.py
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/
unique.py
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# Copyright 2017 The TensorFlow Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
# ==============================================================================
"""Unique element dataset transformations."""
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
from tensorflow.contrib.data.python.ops import contrib_op_loader # pylint: disable=unused-import
from tensorflow.contrib.data.python.ops import gen_dataset_ops
from tensorflow.python.data.ops import dataset_ops
from tensorflow.python.framework import dtypes
def unique():
"""Creates a `Dataset` from another `Dataset`, discarding duplicates.
Use this transformation to produce a dataset that contains one instance of
each unique element in the input. For example:
```python
dataset = tf.data.Dataset.from_tensor_slices([1, 37, 2, 37, 2, 1])
# Using `unique()` will drop the duplicate elements.
dataset = dataset.apply(tf.contrib.data.unique()) # ==> { 1, 37, 2 }
```
Returns:
A `Dataset` transformation function, which can be passed to
@{tf.data.Dataset.apply}.
"""
def _apply_fn(dataset):
return _UniqueDataset(dataset)
return _apply_fn
class _UniqueDataset(dataset_ops.Dataset):
"""A `Dataset` contains the unique elements from its input."""
def __init__(self, input_dataset):
"""See `unique()` for details."""
super(_UniqueDataset, self).__init__()
self._input_dataset = input_dataset
if input_dataset.output_types not in (dtypes.int32, dtypes.int64,
dtypes.string):
raise TypeError(
"`tf.contrib.data.unique()` only supports inputs with a single "
"`tf.int32`, `tf.int64`, or `tf.string` component.")
def _as_variant_tensor(self):
return gen_dataset_ops.unique_dataset(
self._input_dataset._as_variant_tensor(), # pylint: disable=protected-access
**dataset_ops.flat_structure(self))
@property
def output_classes(self):
return self._input_dataset.output_classes
@property
def output_shapes(self):
return self._input_dataset.output_shapes
@property
def output_types(self):
return self._input_dataset.output_types