tf.unique_with_counts
tf.unique_with_counts
tf.unique_with_counts
unique_with_counts( x, out_idx=None, name=None )
Defined in tensorflow/python/ops/gen_array_ops.py
.
See the guide: Tensor Transformations > Slicing and Joining
Finds unique elements in a 1-D tensor.
This operation returns a tensor y
containing all of the unique elements of x
sorted in the same order that they occur in x
. This operation also returns a tensor idx
the same size as x
that contains the index of each value of x
in the unique output y
. Finally, it returns a third tensor count
that contains the count of each element of y
in x
. In other words:
y[idx[i]] = x[i] for i in [0, 1,...,rank(x) - 1]
For example:
# tensor 'x' is [1, 1, 2, 4, 4, 4, 7, 8, 8] y, idx, count = unique_with_counts(x) y ==> [1, 2, 4, 7, 8] idx ==> [0, 0, 1, 2, 2, 2, 3, 4, 4] count ==> [2, 1, 3, 1, 2]
Args:
-
x
: ATensor
. 1-D. -
out_idx
: An optionaltf.DType
from:tf.int32, tf.int64
. Defaults totf.int32
. -
name
: A name for the operation (optional).
Returns:
A tuple of Tensor
objects (y, idx, count).
-
y
: ATensor
. Has the same type asx
. 1-D. -
idx
: ATensor
of typeout_idx
. 1-D. -
count
: ATensor
of typeout_idx
. 1-D.
© 2017 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/api_docs/python/tf/unique_with_counts