What is the purpose of Python – torch.positive?

From documentation :

torch.positive(input) → Tensor

Returns input. Throws a runtime error if input is a bool tensor.

If it is a tensor, it simply returns input and throws an error, but this is not an effective way to check if the tensor is , nor is bool it bool a readable method.

As if pytorch addedpytorch.positive in parity with numpyit has a function of the same name .

Back to your question,positive is a unary operator that basically multiplies everything by +1. This is not a particularly useful operation, but it is not the same as negative symmetry, which multiplies everything by -1.

>>> import numpy as np
>>> a = np.arange(10)
>>> a
array([0, 1, 2, 3, 4, 5, 6, 7, 8, 9])
>>> np.positive(a)
array([0, 1, 2, 3, 4, 5, 6, 7, 8, 9])
>>> np.negative(a)
array([ 0, -1, -2, -3, -4, -5, -6, -7, -8, -9])

So why make a function that effectively returns (a copy) positive of the array you passed? It can be used to write generic code such asnumpy.positive numpy.negative and can be used dynamically based on certain conditions.