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 from_float(cls, mod):
      (
          scale,
          zero_point,
      ) = mod.activation_post_process.calculate_qparams()
      return cls(
          float(scale), int(zero_point), mod.negative_slope, mod.inplace
      )
  
imports: import torch
  from warnings import warn
label_desc: Use image node_id 4 for calling the LeakyReLU obj's underlying member method code with example usage: obj.from_float(cls, mod) and returns: cls