any

paddle. any ( x, axis=None, keepdim=False, name=None ) [source]

Computes the the logical or of tensor elements over the given dimension.

Parameters
  • x (Tensor) – An N-D Tensor, the input data type should be bool.

  • axis (int|list|tuple, 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 \(rank + axis[i]\).

  • 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, optional) – The default value is None. Normally there is no need for user to set this property. For more information, please refer to Name

Returns

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

Return type

Tensor

Raises
  • ValueError – If the data type of x is not bool.

  • TypeError – The type of axis must be int, list or tuple.

Examples

import paddle
import numpy as np

# x is a bool Tensor with following elements:
#    [[True, False]
#     [False, False]]
x = paddle.assign(np.array([[1, 0], [1, 1]], dtype='int32'))
print(x)
x = paddle.cast(x, 'bool')

# out1 should be [True]
out1 = paddle.any(x)  # [True]
print(out1)

# out2 should be [True, False]
out2 = paddle.any(x, axis=0)  # [True, False]
print(out2)

# keep_dim=False, out3 should be [True, False], out.shape should be (2,)
out3 = paddle.any(x, axis=-1)  # [True, False]
print(out3)

# keep_dim=True, result should be [[True], [False]], out.shape should be (2,1)
out4 = paddle.any(x, axis=1, keepdim=True)
out4 = paddle.cast(out4, 'int32')  # [[True], [False]]
print(out4)