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# tf.sets.intersection

Compute set intersection of elements in last dimension of `a` and `b`.

All but the last dimension of `a` and `b` must match.

#### Example:

``````  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.intersection` is applied to each aligned pair of sets.
tf.sets.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),
# ])
``````

`a` `Tensor` or `SparseTensor` of the same type as `b`. If sparse, indices must be sorted in row-major order.
`b` `Tensor` or `SparseTensor` of the same type as `a`. If sparse, indices must be sorted in row-major order.
`validate_indices` Whether to validate the order and range of sparse indices in `a` and `b`.

A `SparseTensor` whose shape is the same rank as `a` and `b`, and all but the last dimension the same. Elements along the last dimension contain the intersections.

[{ "type": "thumb-down", "id": "missingTheInformationINeed", "label":"Missing the information I need" },{ "type": "thumb-down", "id": "tooComplicatedTooManySteps", "label":"Too complicated / too many steps" },{ "type": "thumb-down", "id": "outOfDate", "label":"Out of date" },{ "type": "thumb-down", "id": "samplesCodeIssue", "label":"Samples / code issue" },{ "type": "thumb-down", "id": "otherDown", "label":"Other" }]
[{ "type": "thumb-up", "id": "easyToUnderstand", "label":"Easy to understand" },{ "type": "thumb-up", "id": "solvedMyProblem", "label":"Solved my problem" },{ "type": "thumb-up", "id": "otherUp", "label":"Other" }]