code: def reduce_amax(input, axis=None, keepdims=True):
      """Compute the absolute maximum value of a tensor.
  
      Reduces input_tensor along the dimensions given in axis. Unless keepdims is true,
      the rank of the tensor is reduced by 1 for each entry in axis. If keepdims is true,
      the reduced dimensions are retained with length 1.
  
      .. note::
          Gradient computeation is disabled as this function is never meant learning reduces amax
  
      Args:
          input: Input tensor
          axis: The dimensions to reduce. None or int or tuple of ints. If None (the default),
              reduces all dimensions. Must be in the range [-rank(input_tensor), rank(input_tensor)).
          keepdims: A boolean. If true, retains reduced dimensions with length 1. Default True
          granularity: DEPRECTED. specifies if the statistic has to be calculated at tensor or channel granularity
  
      Returns:
          The reduced tensor.
  
      Raises:
          ValueError: Any axis which doesn't make sense or is not supported
          ValueError: If unknown granularity is passed in.
      """
      with torch.no_grad():
          output = input.abs()
          if axis is None:
              output = torch.max(output)
          else:
              if isinstance(axis, int):
                  output, _ = torch.max(
                      output, dim=axis, keepdim=keepdims
                  )
              else:
                  if (
                      isinstance(axis, tuple)
                      and len(axis) > input.dim()
                  ):
                      raise ValueError(
                          "Cannot reduce more axes than tensor's dim."
                      )
                  for i in axis:
                      output, _ = torch.max(output, dim=i, keepdim=True)
                  if not keepdims or output.numel() == 1:
                      output.squeeze_()
          return output
  
label_desc: Use image node_id 1 for calling a global function with example usage: reduce_amax(input, axis, keepdims) and returns: output