# tf.raw_ops.EditDistance

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Computes the (possibly normalized) Levenshtein Edit Distance.

#### View aliases


**Compat aliases for migration**

See
[Migration guide](https://www.tensorflow.org/guide/migrate) for
more details.

[`tf.compat.v1.raw_ops.EditDistance`](https://www.tensorflow.org/api_docs/python/tf/raw_ops/EditDistance)

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    tf.raw_ops.EditDistance(
        hypothesis_indices,
        hypothesis_values,
        hypothesis_shape,
        truth_indices,
        truth_values,
        truth_shape,
        normalize=True,
        name=None
    )

The inputs are variable-length sequences provided by SparseTensors
(hypothesis_indices, hypothesis_values, hypothesis_shape)
and
(truth_indices, truth_values, truth_shape).

#### The inputs are:

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| ## Args ||
|---|---|
| `hypothesis_indices` | A `Tensor` of type `int64`. The indices of the hypothesis list SparseTensor. This is an N x R int64 matrix. |
| `hypothesis_values` | A `Tensor`. The values of the hypothesis list SparseTensor. This is an N-length vector. |
| `hypothesis_shape` | A `Tensor` of type `int64`. The shape of the hypothesis list SparseTensor. This is an R-length vector. |
| `truth_indices` | A `Tensor` of type `int64`. The indices of the truth list SparseTensor. This is an M x R int64 matrix. |
| `truth_values` | A `Tensor`. Must have the same type as `hypothesis_values`. The values of the truth list SparseTensor. This is an M-length vector. |
| `truth_shape` | A `Tensor` of type `int64`. truth indices, vector. |
| `normalize` | An optional `bool`. Defaults to `True`. boolean (if true, edit distances are normalized by length of truth). <br /> The output is: |
| `name` | A name for the operation (optional). |

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| ## Returns ||
|---|---|
| A `Tensor` of type `float32`. ||

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