- paddle. kthvalue ( x, k, axis=None, keepdim=False, name=None )
Find values and indices of the k-th smallest at the axis.
x (Tensor) – A N-D Tensor with type float16, float32, float64, int32, int64.
k (int) – The k for the k-th smallest number to look for along the axis.
axis (int, optional) – Axis to compute indices along. The effective range is [-R, R), where R is x.ndim. when axis < 0, it works the same way as axis + R. The default is None. And if the axis is None, it will computed as -1 by default.
keepdim (bool, optional) – Whether to keep the given axis in output. If it is True, the dimensions will be same as input x and with size one in the axis. Otherwise the output dimentions is one fewer than x since the axis is squeezed. Default is False.
name (str, optional) – For details, please refer to Name. Generally, no setting is required. Default: None.
tuple(Tensor), return the values and indices. The value data type is the same as the input x. The indices data type is int64.
import paddle x = paddle.randn((2,3,2)) # Tensor(shape=[2, 3, 2], dtype=float32, place=CUDAPlace(0), stop_gradient=True, # [[[ 0.22954939, -0.01296274], # [ 1.17135799, -0.34493217], # [-0.19550551, -0.17573971]], # # [[ 0.15104349, -0.93965352], # [ 0.14745511, 0.98209465], # [ 0.10732264, -0.55859774]]]) y = paddle.kthvalue(x, 2, 1) # (Tensor(shape=[2, 2], dtype=float32, place=CUDAPlace(0), stop_gradient=True, # [[ 0.22954939, -0.17573971], # [ 0.14745511, -0.55859774]]), Tensor(shape=[2, 2], dtype=int64, place=CUDAPlace(0), stop_gradient=True, # [[0, 2], # [1, 2]]))