Sorts a tensor.
tf.sort( values, axis=-1, direction='ASCENDING', name=None )
Used in the notebooks
Usage:
a = [1, 10, 26.9, 2.8, 166.32, 62.3] tf.sort(a).numpy() array([ 1. , 2.8 , 10. , 26.9 , 62.3 , 166.32], dtype=float32)
tf.sort(a, direction='DESCENDING').numpy() array([166.32, 62.3 , 26.9 , 10. , 2.8 , 1. ], dtype=float32)
For multidimensional inputs you can control which axis the sort is applied along. The default axis=-1 sorts the innermost axis.
mat = [[3,2,1], [2,1,3], [1,3,2]] tf.sort(mat, axis=-1).numpy() array([[1, 2, 3], [1, 2, 3], [1, 2, 3]], dtype=int32) tf.sort(mat, axis=0).numpy() array([[1, 1, 1], [2, 2, 2], [3, 3, 3]], dtype=int32)
See also |
tf.argsort: Like sort, but it returns the sort indices. tf.math.top_k: A partial sort that returns a fixed number of top values and corresponding indices. |
Args |
values | 1-D or higher numeric Tensor. |
axis | The axis along which to sort. The default is -1, which sorts the last axis. |
direction | The direction in which to sort the values ('ASCENDING' or 'DESCENDING'). |
name | Optional name for the operation. |
Returns |
A Tensor with the same dtype and shape as values, with the elements sorted along the given axis. |
Raises |
tf.errors.InvalidArgumentError | If the values.dtype is not a float or int type. |
ValueError | If axis is not a constant scalar, or the direction is invalid. |