mode

paddle. mode ( x: Tensor, axis: int = -1, keepdim: bool = False, name: str | None = None, *, out: tuple[Tensor, Tensor] | None = None ) → ModeRetType [source]

Used to find values and indices of the modes at the optional axis.

Parameters

x (Tensor) – Tensor, an input N-D Tensor with type float32, float64, int32, int64. Alias: input.
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. Default is -1. Alias: dim.
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 dimensions is one fewer than x since the axis is squeezed. Default is False.
name (str|None, optional) – For details, please refer to api_guide_Name. Generally, no setting is required. Default: None.

Keyword Arguments

out (tuple(Tensor), optional) – The output tensor.

Returns

tuple (Tensor), return the values and indices. The value data type is the same as the input x. The indices data type is int64.

Examples

           >>> import paddle

>>> tensor = paddle.to_tensor(
...     [
...         [[1, 2, 2], [2, 3, 3]],
...         [[0, 5, 5], [9, 9, 0]],
...     ],
...     dtype=paddle.float32,
... )
>>> values, indices = paddle.mode(tensor, 2)
>>> print(values)
Tensor(shape=[2, 2], dtype=float32, place=Place(cpu), stop_gradient=True,
[[2., 3.],
 [5., 9.]])
>>> print(indices)
Tensor(shape=[2, 2], dtype=int64, place=Place(cpu), stop_gradient=True,
[[2, 2],
 [2, 1]])

          