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 .
|