tf.raw_ops.EditDistance
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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).
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. |
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Last updated 2024-04-26 UTC.
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