Hardshrink

class torch.nn.Hardshrink(lambd=0.5) [source]

Применяет функцию жёсткой усадки (Hardshrink) поэлементно.

Функция жёсткой усадки определяется как:

$$\text{HardShrink}(x) = \begin{cases} x, & \text{ if } x > \lambda \\ x, & \text{ if } x < -\lambda \\ 0, & \text{ otherwise } \end{cases}$$

Параметры

lambd (float) – значение $\lambda$ для формулы HardShrink. По умолчанию: 0.5

Форма:

• Вход: $(*)$, где $*$ означает любое количество измерений.
• Выход: $(*)$, такая же форма, как у входа.

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