code: def __init__(self, input_size, base_model, transform=None):
      super(_CAMWrapper, self).__init__()
      self.base_model = base_model
      input_image = torch.zeros(input_size)
  
      self.input_image = nn.Parameter(input_image, requires_grad=True)
  
      self.transform = (lambda x: x) if transform is None else transform
  
file_path: torchbearer/torchbearer/callbacks/imaging/inside_cnns.py
imports: import torch
  import torch.nn
  import torch.optim
  import torchbearer
  from torchbearer.callbacks.decorators import once_per_epoch
  from .None import imaging
label_desc: Use image node_id 1 to create a new _CAMWrapper object from inherited base classes: nn with example: obj = _CAMWrapper(input_size, base_model, transform)