Home - News ( United States | United Kingdom | Italy | Germany ) - Football scores

Showing content from https://docs.pytorch.org/docs/stable/generated/torch.heaviside.html below:

torch.heaviside — PyTorch 2.8 documentation

Computes the Heaviside step function for each element in input. The Heaviside step function is defined as:

heaviside ( i n p u t , v a l u e s ) = { 0 , if input < 0 v a l u e s , if input == 0 1 , if input > 0 \text{{heaviside}}(input, values) = \begin{cases} 0, & \text{if input < 0}\\ values, & \text{if input == 0}\\ 1, & \text{if input > 0} \end{cases} heaviside(input,values)=⎩ ⎨ ⎧​0,values,1,​if input < 0if input == 0if input > 0​

Parameters

• input (Tensor) – the input tensor.

• values (Tensor) – The values to use where input is zero.

Keyword Arguments

out (Tensor, optional) – the output tensor.

Example:

>>> input = torch.tensor([-1.5, 0, 2.0])
>>> values = torch.tensor([0.5])
>>> torch.heaviside(input, values)
tensor([0.0000, 0.5000, 1.0000])
>>> values = torch.tensor([1.2, -2.0, 3.5])
>>> torch.heaviside(input, values)
tensor([0., -2., 1.])

RetroSearch is an open source project built by @garambo | Open a GitHub Issue

Search and Browse the WWW like it's 1997 | Search results from DuckDuckGo

HTML: 3.2 | Encoding: UTF-8 | Version: 0.7.4