





from torch import nn







def       A__							(   SCREAMING_SNAKE_CASE__)       ->   Dict:
  if act_fn in ["swish", "silu"]:
    return nn.SiLU()
  elif act_fn == "mish":
    return nn.Mish()
  elif act_fn == "gelu":
    return nn.GELU()
  else:
    raise ValueError(F'''Unsupported activation function: {act_fn}''')













from __future__ import annotations

import numpy as np







def       A__							(   SCREAMING_SNAKE_CASE__)       ->   List[str]:
  return np.maximum(0 , SCREAMING_SNAKE_CASE__)


if __name__ == "__main__":
      print(np.array(relu([-1, 0, 5])))  # --> [0, 0, 5]






