class_docstr: Same as CrossEntropyLossFlat but with focal paramter, `gamma`. Focal loss is introduced by Lin et al. 
  https://arxiv.org/pdf/1708.02002.pdf. Note the class weighting factor in the paper, alpha, can be 
  implemented through pytorch `weight` argument passed through to F.cross_entropy.
code: def __init__(
      self,
      *args,
      gamma: float = 2.0,  # Focusing parameter. Higher values down-weight easy examples' contribution to loss
      axis: int = -1,  # Class axis
      **kwargs,
  ):
      super().__init__(
          FocalLoss, *args, gamma=gamma, axis=axis, **kwargs
      )
  
imports: from __future__ import annotations
  from .imports import *
  from .torch_imports import *
  from .torch_core import *
  from .layers import *
label_desc: Use image node_id 1 to create a new FocalLossFlat object from inherited base classes: BaseLoss with example: obj = FocalLossFlat()