class_docstr: This is the quantized equivalent of :class:`~torch.nn.LeakyReLU`.
  
  Args:
      scale: quantization scale of the output tensor
      zero_point: quantization zero point of the output tensor
      negative_slope: Controls the angle of the negative slope. Default: 1e-2
class_docstr_tok: ["This","is","the","quantized","equivalent","of",":","class",":","`","~torch.nn.LeakyReLU","`",".","Args",":","scale",":","quantization","scale","of","the","output","tensor","zero_point",":","quantization","zero","point","of","the","output","tensor","negative_slope",":","Controls","the","angle","of","the","negative","slope",".","Default",":","1e-2"]
code: def __init__(
      self,
      scale: float,
      zero_point: int,
      negative_slope: float = 1e-2,
      inplace: bool = False,
      device=None,
      dtype=None,
  ) -> None:
      factory_kwargs = {"device": device, "dtype": dtype}
      super().__init__(negative_slope, inplace)
      self.register_buffer(
          "scale", torch.tensor(scale, **factory_kwargs)
      )
      self.register_buffer(
          "zero_point", torch.tensor(zero_point, **factory_kwargs)
      )
  
imports: import torch
  from warnings import warn
label_desc: Use image node_id 1 to create a new LeakyReLU object from inherited base classes: torch.nn with example: obj = LeakyReLU(scale, zero_point, negative_slope, inplace, device, dtype)