docstr: ConvAffine adds a Conv op followed by a AffineChannel op (which
  replaces BN during fine tuning).
docstr_tok: ["ConvAffine","adds","a","Conv","op","followed","by","a","AffineChannel","op","(","which","replaces","BN","during","fine","tuning",")","."]
code: def ConvAffine(  # args in the same order of Conv()
      self,
      blob_in,
      prefix,
      dim_in,
      dim_out,
      kernel,
      stride,
      pad,
      group=1,
      dilation=1,
      weight_init=None,
      bias_init=None,
      suffix="_bn",
      inplace=False,
  ):
      """ConvAffine adds a Conv op followed by a AffineChannel op (which
      replaces BN during fine tuning).
      """
      conv_blob = self.Conv(
          blob_in,
          prefix,
          dim_in,
          dim_out,
          kernel,
          stride=stride,
          pad=pad,
          group=group,
          dilation=dilation,
          weight_init=weight_init,
          bias_init=bias_init,
          no_bias=1,
      )
      blob_out = self.AffineChannel(
          conv_blob, prefix + suffix, dim=dim_out, inplace=inplace
      )
      return blob_out
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  from __future__ import unicode_literals
  import numpy
  import logging
  from caffe2.python import cnn
  from caffe2.python import core
  from caffe2.python import workspace
  from caffe2.python.modeling import initializers
  from caffe2.python.modeling.parameter_info import ParameterTags
  from detectron.core.config import cfg
  from detectron.ops.collect_and_distribute_fpn_rpn_proposals import CollectAndDistributeFpnRpnProposalsOp
  from detectron.ops.generate_proposal_labels import GenerateProposalLabelsOp
  from detectron.ops.generate_proposals import GenerateProposalsOp
  import detectron.roi_data.fast_rcnn
  import detectron.utils.c2
label_desc: Use image node_id 11 for calling the DetectionModelHelper obj's underlying member method code with example usage: obj.ConvAffine(blob_in, prefix, dim_in, dim_out, kernel, stride, pad, group, dilation, weight_init, bias_init, suffix, inplace) and returns: blob_out