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# tf.edit_distance

Computes the Levenshtein distance between sequences.

This operation takes variable-length sequences (hypothesis and truth), each provided as a SparseTensor, and computes the Levenshtein distance. You can normalize the edit distance by length of truth by setting normalize to true.

#### For example:

Given the following input,

hypothesis = tf.SparseTensor(
[[0, 0, 0],
[1, 0, 0]],
["a", "b"],
(2, 1, 1))
truth = tf.SparseTensor(
[[0, 1, 0],
[1, 0, 0],
[1, 0, 1],
[1, 1, 0]],
["a", "b", "c", "a"],
(2, 2, 2))
tf.edit_distance(hypothesis, truth, normalize=True)
<tf.Tensor: shape=(2, 2), dtype=float32, numpy=
array([[inf, 1. ],
[0.5, 1. ]], dtype=float32)>

The operation returns a dense Tensor of shape [2, 2] with edit distances normalized by truth lengths.

For the following inputs,

# 'hypothesis' is a tensor of shape `[2, 1]` with variable-length values:
#   (0,0) = ["a"]
#   (1,0) = ["b"]
hypothesis = tf.sparse.SparseTensor(
[[0, 0, 0],
[1, 0, 0]],
["a", "b"],
(2, 1, 1))

# 'truth' is a tensor of shape `[2, 2]` with variable-length values:
#   (0,0) = []
#   (0,1) = ["a"]
#   (1,0) = ["b", "c"]
#   (1,1) = ["a"]
truth = tf.sparse.SparseTensor(
[[0, 1, 0],
[1, 0, 0],
[1, 0, 1],
[1, 1, 0]],
["a", "b", "c", "a"],
(2, 2, 2))

normalize = True

# The output would be a dense Tensor of shape `(2,)`, with edit distances
normalized by 'truth' lengths.
# output => array([0., 0.5], dtype=float32)

hypothesis A SparseTensor containing hypothesis sequences.
truth A SparseTensor containing truth sequences.
normalize A bool. If True, normalizes the Levenshtein distance by length of truth.
name A name for the operation (optional).

A dense Tensor with rank R - 1, where R is the rank of the SparseTensor inputs hypothesis and truth.

TypeError If either hypothesis or truth are not a SparseTensor.

[{ "type": "thumb-down", "id": "missingTheInformationINeed", "label":"没有我需要的信息" },{ "type": "thumb-down", "id": "tooComplicatedTooManySteps", "label":"太复杂/步骤太多" },{ "type": "thumb-down", "id": "outOfDate", "label":"内容需要更新" },{ "type": "thumb-down", "id": "samplesCodeIssue", "label":"Samples / code issue" },{ "type": "thumb-down", "id": "otherDown", "label":"其他" }]
[{ "type": "thumb-up", "id": "easyToUnderstand", "label":"易于理解" },{ "type": "thumb-up", "id": "solvedMyProblem", "label":"解决了我的问题" },{ "type": "thumb-up", "id": "otherUp", "label":"其他" }]