code: def from_float(module: torch.nn.Linear, input_scale):
      int8_module = W8A8BFP32OFP32Linear(
          module.in_features, module.out_features
      )
      int8_weight, weight_scale = quantize_per_tensor_absmax(
          module.weight
      )
      alpha = input_scale * weight_scale
      int8_module.weight = int8_weight
      int8_module.a = alpha
      int8_module.input_scale = input_scale
      int8_module.weight_scale = weight_scale
  
      if module.bias is not None:
          int8_module.bias = module.bias.to(torch.float32)
  
      return int8_module
  
imports: import torch
label_desc: Use image node_id 5 for calling the W8A8BFP32OFP32Linear obj's underlying member method code with example usage: obj.from_float(module, input_scale) and returns: int8_module