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 __init__(
      self, channel, norm_layer=BatchNorm, norm_kwargs=None, **kwargs
  ):
      super(DarknetBasicBlockV3, self).__init__(**kwargs)
      self.body = nn.HybridSequential(prefix="")
      # 1x1 reduce
      self.body.add(
          _conv2d(
              channel,
              1,
              0,
              1,
              norm_layer=norm_layer,
              norm_kwargs=norm_kwargs,
          )
      )
      # 3x3 conv expand
      self.body.add(
          _conv2d(
              channel * 2,
              3,
              1,
              1,
              norm_layer=norm_layer,
              norm_kwargs=norm_kwargs,
          )
      )
  
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 1 to create a new DarknetBasicBlockV3 object from inherited base classes: gluon with example: obj = DarknetBasicBlockV3(channel, norm_layer, norm_kwargs)