any

paddle. any ( x: Tensor, axis: int | Sequence[int] | None = None, keepdim: bool = False, name: str | None = None, *, out: Tensor | None = None ) → Tensor [source]

Computes the logical or of tensor elements over the given dimension, and return the result.

Note

Alias Support: The parameter name input can be used as an alias for x, and the parameter name dim can be used as an alias for axis. For example, any(input=tensor_x, dim=1) is equivalent to any(x=tensor_x, axis=1).

Parameters

x (Tensor) – An N-D Tensor, the input data type should be ‘bool’, ‘float32’, ‘float64’, ‘int32’, ‘int64’, ‘complex64’, ‘complex128’. alias: input.
axis (int|list|tuple|None, optional) – The dimensions along which the logical or is compute. If None, and all elements of x and return a Tensor with a single element, otherwise must be in the range \([-rank(x), rank(x))\). If \(axis[i] < 0\), the dimension to reduce is \(rank + axis[i]\). alias: dim.
keepdim (bool, optional) – Whether to reserve the reduced dimension in the output Tensor. The result Tensor will have one fewer dimension than the x unless keepdim is true, default value is False.
name (str|None, optional) – Name for the operation (optional, default is None). For more information, please refer to api_guide_Name.
out (Tensor|None, optional) – The output tensor. Default: None.

Returns

Results the logical or on the specified axis of input Tensor x, it’s data type is bool.

Return type

Tensor

Examples

           >>> import paddle

>>> # type: ignore

>>> x = paddle.to_tensor([[1, 0], [1, 1]], dtype='int32')
>>> x = paddle.assign(x)
>>> x
Tensor(shape=[2, 2], dtype=int32, place=Place(cpu), stop_gradient=True,
[[1, 0],
 [1, 1]])
>>> x = paddle.cast(x, 'bool')
>>> # x is a bool Tensor with following elements:
>>> #    [[True, False]
>>> #     [True, True]]

>>> # out1 should be True
>>> out1 = paddle.any(x)
>>> out1
Tensor(shape=[], dtype=bool, place=Place(cpu), stop_gradient=True,
True)

>>> # out2 should be [True, True]
>>> out2 = paddle.any(x, axis=0)
>>> out2
Tensor(shape=[2], dtype=bool, place=Place(cpu), stop_gradient=True,
[True, True])

>>> # keepdim=False, out3 should be [True, True], out.shape should be (2,)
>>> out3 = paddle.any(x, axis=-1)
>>> out3
Tensor(shape=[2], dtype=bool, place=Place(cpu), stop_gradient=True,
[True, True])

>>> # keepdim=True, result should be [[True], [True]], out.shape should be (2,1)
>>> out4 = paddle.any(x, axis=1, keepdim=True)
>>> out4
Tensor(shape=[2, 1], dtype=bool, place=Place(cpu), stop_gradient=True,
[[True],
 [True]])

          