class_docstr: Focal loss for heatmaps.
  
  Parameters
  ----------
  from_logits : bool
      Whether predictions are after sigmoid or softmax.
  batch_axis : int
      Batch axis.
  weight : float
      Loss weight.
class_docstr_tok: ["Focal","loss","for","heatmaps",".","Parameters","--","--","--","--","--","from_logits",":","bool","Whether","predictions","are","after","sigmoid","or","softmax",".","batch_axis",":","int","Batch","axis",".","weight",":","float","Loss","weight","."]
code: def __init__(
      self, from_logits=False, batch_axis=0, weight=None, **kwargs
  ):
      super(HeatmapFocalLoss, self).__init__(
          weight, batch_axis, **kwargs
      )
      self._from_logits = from_logits
  
imports: from __future__ import absolute_import
  from mxnet import gluon
  from mxnet import nd
  from mxnet.gluon.loss import Loss, _apply_weighting, _reshape_like
label_desc: Use image node_id 1 to create a new HeatmapFocalLoss object from inherited base classes: Loss with example: obj = HeatmapFocalLoss(from_logits, batch_axis, weight)