Threshold

class torch.nn.Threshold(threshold, value, inplace=False)

Thresholds each element of the input Tensor.

Threshold is defined as:

$$y = \begin{cases} x, &\text{ if } x > \text{threshold} \\ \text{value}, &\text{ otherwise } \end{cases}$$

Parameters

• threshold (float) – The value to threshold at

• value (float) – The value to replace with

• inplace (bool) – can optionally do the operation in-place. Default: False

Shape:

• Input: $(*)$, where $*$ means any number of dimensions.

• Output: $(*)$, same shape as the input.

Examples:

>>> m = nn.Threshold(0, 0.5)
>>> input = torch.arange(-3, 3)
>>> output = m(input)

extra_repr()

Return the extra representation of the module.

Return type

str

forward(input)

Runs the forward pass.

Return type

Tensor