class_docstr: Darknet Basic Block. Which is a 1x1 reduce conv followed by 3x3 conv.
  
  Parameters
  ----------
  channel : int
      Convolution channels for 1x1 conv.
  norm_layer : object
      Normalization layer used (default: :class:`mxnet.gluon.nn.BatchNorm`)
      Can be :class:`mxnet.gluon.nn.BatchNorm` or :class:`mxnet.gluon.contrib.nn.SyncBatchNorm`.
  norm_kwargs : dict
      Additional `norm_layer` arguments, for example `num_devices=4`
      for :class:`mxnet.gluon.contrib.nn.SyncBatchNorm`.
class_docstr_tok: ["Darknet","Basic","Block",".","Which","is","a","1x1","reduce","conv","followed","by","3x3","conv",".","Parameters","--","--","--","--","--","channel",":","int","Convolution","channels","for","1x1","conv",".","norm_layer",":","object","Normalization","layer","used","(","default",":",":","class",":","`","mxnet.gluon.nn.BatchNorm","`",")","Can","be",":","class",":","`","mxnet.gluon.nn.BatchNorm","`","or",":","class",":","`","mxnet.gluon.contrib.nn.SyncBatchNorm","`",".","norm_kwargs",":","dict","Additional","`","norm_layer","`","arguments",",","for","example","`","num_devices=4","`","for",":","class",":","`","mxnet.gluon.contrib.nn.SyncBatchNorm","`","."]
code: def hybrid_forward(self, F, x, *args):
      residual = x
      x = self.body(x)
      return x + residual
  
file_path: gluon-cv/gluoncv/model_zoo/yolo/darknet.py
imports: from __future__ import absolute_import
  import os
  import mxnet
  from mxnet import gluon
  from mxnet.gluon import nn
  from mxnet.gluon.nn import BatchNorm
label_desc: Use image node_id 2 for calling the DarknetBasicBlockV3 obj's underlying member method code with example usage: obj.hybrid_forward(F, x) and returns: unknown