code: def group_conv(
      model,
      blob_in,
      blob_out,
      dim_in,
      dim_out,
      kernel,
      weight_init=None,
      bias_init=None,
      group=1,
      **kwargs,
  ):
      """Group Convolution.
  
      This is essentially the same as Conv with a group argument passed in.
      We specialize this for backward interface compatibility.
      """
      return conv(
          model,
          blob_in,
          blob_out,
          dim_in,
          dim_out,
          kernel,
          weight_init=weight_init,
          bias_init=bias_init,
          group=group,
          **kwargs,
      )
  
file_path: pytorch/caffe2/python/helpers/conv.py
imports: from caffe2.python import core
  from caffe2.python.modeling import initializers
  from caffe2.python.modeling.parameter_info import ParameterTags
label_desc: Use image node_id 5 for calling a global function with example usage: group_conv(model, blob_in, blob_out, dim_in, dim_out, kernel, weight_init, bias_init, group) and returns: conv