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make tf.sets examples executable

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Fixes #12969

PiperOrigin-RevId: 168549712
This commit is contained in:
Mark Daoust 2017-09-13 09:26:41 -07:00 committed by TensorFlower Gardener
parent bece65c6f3
commit c8a6131e9f
1 changed files with 127 additions and 108 deletions
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235
tensorflow/python/ops/sets_impl.py
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@ -139,42 +139,45 @@ def set_intersection(a, b, validate_indices=True):
Example: Example:
```python ```python
a = [ import tensorflow as tf
[ import collections
[
[1, 2], # Represent the following array of sets as a sparse tensor:
[3], # a = np.array([[{1, 2}, {3}], [{4}, {5, 6}]])
], a = collections.OrderedDict([
[ ((0, 0, 0), 1),
[4], ((0, 0, 1), 2),
[5, 6], ((0, 1, 0), 3),
], ((1, 0, 0), 4),
], ((1, 1, 0), 5),
] ((1, 1, 1), 6),
b = [ ])
[ a = tf.SparseTensor(list(a.keys()), list(a.values()), dense_shape=[2,2,2])
[
[1, 3], # b = np.array([[{1}, {}], [{4}, {5, 6, 7, 8}]])
[2], b = collections.OrderedDict([
], ((0, 0, 0), 1),
[ ((1, 0, 0), 4),
[4, 5], ((1, 1, 0), 5),
[5, 6, 7, 8], ((1, 1, 1), 6),
], ((1, 1, 2), 7),
], ((1, 1, 3), 8),
] ])
set_intersection(a, b) = [ b = tf.SparseTensor(list(b.keys()), list(b.values()), dense_shape=[2, 2, 4])
[
[ # `tf.sets.set_intersection` is applied to each aligned pair of sets.
[1], tf.sets.set_intersection(a, b)
[],
], # The result will be equivalent to either of:
[ #
[4], # np.array([[{1}, {}], [{4}, {5, 6}]])
[5, 6], #
], # collections.OrderedDict([
], # ((0, 0, 0), 1),
] # ((1, 0, 0), 4),
# ((1, 1, 0), 5),
# ((1, 1, 1), 6),
# ])
``` ```
Args: Args:
@ -202,42 +205,46 @@ def set_difference(a, b, aminusb=True, validate_indices=True):
Example: Example:
```python ```python
a = [ import tensorflow as tf
[ import collections
[
[1, 2], # Represent the following array of sets as a sparse tensor:
[3], # a = np.array([[{1, 2}, {3}], [{4}, {5, 6}]])
], a = collections.OrderedDict([
[ ((0, 0, 0), 1),
[4], ((0, 0, 1), 2),
[5, 6], ((0, 1, 0), 3),
], ((1, 0, 0), 4),
], ((1, 1, 0), 5),
] ((1, 1, 1), 6),
b = [ ])
[ a = tf.SparseTensor(list(a.keys()), list(a.values()), dense_shape=[2, 2, 2])
[
[1, 3], # np.array([[{1, 3}, {2}], [{4, 5}, {5, 6, 7, 8}]])
[2], b = collections.OrderedDict([
], ((0, 0, 0), 1),
[ ((0, 0, 1), 3),
[4, 5], ((0, 1, 0), 2),
[5, 6, 7, 8], ((1, 0, 0), 4),
], ((1, 0, 1), 5),
], ((1, 1, 0), 5),
] ((1, 1, 1), 6),
set_difference(a, b, aminusb=True) = [ ((1, 1, 2), 7),
[ ((1, 1, 3), 8),
[ ])
[2], b = tf.SparseTensor(list(b.keys()), list(b.values()), dense_shape=[2, 2, 4])
[3],
], # `set_difference` is applied to each aligned pair of sets.
[ tf.sets.set_difference(a, b)
[],
[], # The result will be equivalent to either of:
], #
], # np.array([[{2}, {3}], [{}, {}]])
] #
# collections.OrderedDict([
# ((0, 0, 0), 2),
# ((0, 0, 1), 3),
# ])
``` ```
Args: Args:
@ -268,42 +275,54 @@ def set_union(a, b, validate_indices=True):
Example: Example:
```python ```python
a = [ import tensorflow as tf
[ import collections
[
[1, 2], # [[{1, 2}, {3}], [{4}, {5, 6}]]
[3], a = collections.OrderedDict([
], ((0, 0, 0), 1),
[ ((0, 0, 1), 2),
[4], ((0, 1, 0), 3),
[5, 6], ((1, 0, 0), 4),
], ((1, 1, 0), 5),
], ((1, 1, 1), 6),
] ])
b = [ a = tf.SparseTensor(list(a.keys()), list(a.values()), dense_shape=[2, 2, 2])
[
[ # [[{1, 3}, {2}], [{4, 5}, {5, 6, 7, 8}]]
[1, 3], b = collections.OrderedDict([
[2], ((0, 0, 0), 1),
], ((0, 0, 1), 3),
[ ((0, 1, 0), 2),
[4, 5], ((1, 0, 0), 4),
[5, 6, 7, 8], ((1, 0, 1), 5),
], ((1, 1, 0), 5),
], ((1, 1, 1), 6),
] ((1, 1, 2), 7),
set_union(a, b) = [ ((1, 1, 3), 8),
[ ])
[ b = tf.SparseTensor(list(b.keys()), list(b.values()), dense_shape=[2, 2, 4])
[1, 2, 3],
[2, 3], # `set_union` is applied to each aligned pair of sets.
], tf.sets.set_union(a, b)
[
[4, 5], # The result will be a equivalent to either of:
[5, 6, 7, 8], #
], # np.array([[{1, 2, 3}, {2, 3}], [{4, 5}, {5, 6, 7, 8}]])
], #
] # collections.OrderedDict([
# ((0, 0, 0), 1),
# ((0, 0, 1), 2),
# ((0, 0, 2), 3),
# ((0, 1, 0), 2),
# ((0, 1, 1), 3),
# ((1, 0, 0), 4),
# ((1, 0, 1), 5),
# ((1, 1, 0), 5),
# ((1, 1, 1), 6),
# ((1, 1, 2), 7),
# ((1, 1, 3), 8),
# ])
``` ```
Args: Args: