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. |
© 2020 The TensorFlow Authors. All rights reserved.
Licensed under the Creative Commons Attribution License 3.0.
Code samples licensed under the Apache 2.0 License.
https://www.tensorflow.org/versions/r2.3/api_docs/python/tf/raw_ops/EditDistance