class_docstr: Spatial NL block for image classification.
  
  This was adapted from https://github.com/BA-Transform/BAT-Image-Classification
  Their NonLocal impl inspired by https://github.com/facebookresearch/video-nonlocal-net.
class_docstr_tok: ["Spatial","NL","block","for","image","classification",".","This","was","adapted","from","https",":","\/\/github.com\/BA-Transform\/BAT-Image-Classification","Their","NonLocal","impl","inspired","by","https",":","\/\/github.com\/facebookresearch\/video-nonlocal-net","."]
code: def reset_parameters(self):
      for name, m in self.named_modules():
          if isinstance(m, nn.Conv2d):
              nn.init.kaiming_normal_(
                  m.weight, mode="fan_out", nonlinearity="relu"
              )
              if len(list(m.parameters())) > 1:
                  nn.init.constant_(m.bias, 0.0)
          elif isinstance(m, nn.BatchNorm2d):
              nn.init.constant_(m.weight, 0)
              nn.init.constant_(m.bias, 0)
          elif isinstance(m, nn.GroupNorm):
              nn.init.constant_(m.weight, 0)
              nn.init.constant_(m.bias, 0)
  
file_path: pytorch-image-models/timm/layers/non_local_attn.py
imports: import torch
  from torch import nn
  from torch.nn import functional
  from .conv_bn_act import ConvNormAct
  from .helpers import make_divisible
  from .trace_utils import _assert
label_desc: Use image node_id 3 for calling the NonLocalAttn obj's underlying member method code with example usage: obj.reset_parameters() without return types