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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:
```python
a = [
[
[
[1, 2],
[3],
],
[
[4],
[5, 6],
],
],
]
b = [
[
[
[1, 3],
[2],
],
[
[4, 5],
[5, 6, 7, 8],
],
],
]
set_intersection(a, b) = [
[
[
[1],
[],
],
[
[4],
[5, 6],
],
],
]
import tensorflow as tf
import collections
# Represent the following array of sets as a sparse tensor:
# a = np.array([[{1, 2}, {3}], [{4}, {5, 6}]])
a = collections.OrderedDict([
((0, 0, 0), 1),
((0, 0, 1), 2),
((0, 1, 0), 3),
((1, 0, 0), 4),
((1, 1, 0), 5),
((1, 1, 1), 6),
])
a = tf.SparseTensor(list(a.keys()), list(a.values()), dense_shape=[2,2,2])
# b = np.array([[{1}, {}], [{4}, {5, 6, 7, 8}]])
b = collections.OrderedDict([
((0, 0, 0), 1),
((1, 0, 0), 4),
((1, 1, 0), 5),
((1, 1, 1), 6),
((1, 1, 2), 7),
((1, 1, 3), 8),
])
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.
tf.sets.set_intersection(a, b)
# The result will be equivalent to either of:
#
# np.array([[{1}, {}], [{4}, {5, 6}]])
#
# collections.OrderedDict([
# ((0, 0, 0), 1),
# ((1, 0, 0), 4),
# ((1, 1, 0), 5),
# ((1, 1, 1), 6),
# ])
```
Args:
@ -202,42 +205,46 @@ def set_difference(a, b, aminusb=True, validate_indices=True):
Example:
```python
a = [
[
[
[1, 2],
[3],
],
[
[4],
[5, 6],
],
],
]
b = [
[
[
[1, 3],
[2],
],
[
[4, 5],
[5, 6, 7, 8],
],
],
]
set_difference(a, b, aminusb=True) = [
[
[
[2],
[3],
],
[
[],
[],
],
],
]
import tensorflow as tf
import collections
# Represent the following array of sets as a sparse tensor:
# a = np.array([[{1, 2}, {3}], [{4}, {5, 6}]])
a = collections.OrderedDict([
((0, 0, 0), 1),
((0, 0, 1), 2),
((0, 1, 0), 3),
((1, 0, 0), 4),
((1, 1, 0), 5),
((1, 1, 1), 6),
])
a = tf.SparseTensor(list(a.keys()), list(a.values()), dense_shape=[2, 2, 2])
# np.array([[{1, 3}, {2}], [{4, 5}, {5, 6, 7, 8}]])
b = collections.OrderedDict([
((0, 0, 0), 1),
((0, 0, 1), 3),
((0, 1, 0), 2),
((1, 0, 0), 4),
((1, 0, 1), 5),
((1, 1, 0), 5),
((1, 1, 1), 6),
((1, 1, 2), 7),
((1, 1, 3), 8),
])
b = tf.SparseTensor(list(b.keys()), list(b.values()), dense_shape=[2, 2, 4])
# `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:
@ -268,42 +275,54 @@ def set_union(a, b, validate_indices=True):
Example:
```python
a = [
[
[
[1, 2],
[3],
],
[
[4],
[5, 6],
],
],
]
b = [
[
[
[1, 3],
[2],
],
[
[4, 5],
[5, 6, 7, 8],
],
],
]
set_union(a, b) = [
[
[
[1, 2, 3],
[2, 3],
],
[
[4, 5],
[5, 6, 7, 8],
],
],
]
import tensorflow as tf
import collections
# [[{1, 2}, {3}], [{4}, {5, 6}]]
a = collections.OrderedDict([
((0, 0, 0), 1),
((0, 0, 1), 2),
((0, 1, 0), 3),
((1, 0, 0), 4),
((1, 1, 0), 5),
((1, 1, 1), 6),
])
a = tf.SparseTensor(list(a.keys()), list(a.values()), dense_shape=[2, 2, 2])
# [[{1, 3}, {2}], [{4, 5}, {5, 6, 7, 8}]]
b = collections.OrderedDict([
((0, 0, 0), 1),
((0, 0, 1), 3),
((0, 1, 0), 2),
((1, 0, 0), 4),
((1, 0, 1), 5),
((1, 1, 0), 5),
((1, 1, 1), 6),
((1, 1, 2), 7),
((1, 1, 3), 8),
])
b = tf.SparseTensor(list(b.keys()), list(b.values()), dense_shape=[2, 2, 4])
# `set_union` is applied to each aligned pair of sets.
tf.sets.set_union(a, b)
# The result will be a equivalent to either of:
#
# 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: