class_docstr: LayerNorm optimized for Apple Neural Engine (ANE) execution
  
  Note: This layer only supports normalization over the final dim. It expects `num_channels`
  as an argument and not `normalized_shape` which is used by `torch.nn.LayerNorm`.
class_docstr_tok: ["LayerNorm","optimized","for","Apple","Neural","Engine","(","ANE",")","execution","Note",":","This","layer","only","supports","normalization","over","the","final","dim",".","It","expects","`","num_channels","`","as","an","argument","and","not","`","normalized_shape","`","which","is","used","by","`","torch.nn.LayerNorm","`","."]
code: def _reset_parameters(self):
      if self.elementwise_affine:
          nn.init.ones_(self.weight)
          nn.init.zeros_(self.bias)
  
imports: import torch
  import torch.nn
label_desc: Use image node_id 2 for calling the LayerNormANE obj's underlying member method code with example usage: obj._reset_parameters() without return types