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tf.raw_ops.EditDistance

Computes the (possibly normalized) Levenshtein Edit Distance.

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:

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).

The output is:
name A name for the operation (optional).
Returns
A Tensor of type float32.

© 2022 The TensorFlow Authors. All rights reserved.
Licensed under the Creative Commons Attribution License 4.0.
Code samples licensed under the Apache 2.0 License.
https://www.tensorflow.org/versions/r2.9/api_docs/python/tf/raw_ops/EditDistance