(channels, strides=(1, 1), bn_momentum=0.9, mode='train')
return [
      tl.BatchNorm(momentum=bn_momentum, mode=mode),
      tl.Relu(),
      tl.Conv(channels, (3, 3), strides, padding='SAME'),
      tl.BatchNorm(momentum=bn_momentum, mode=mode),
      tl.Relu(),
      tl.Conv(channels, (3, 3), padding='SAME'),
  ]
WideResnet convolutional block.
WideResnet convolutional block.
WideResnet convolutional block .
def WideResnetBlock(channels, strides=(1, 1), bn_momentum=0.9, mode='train'):
  """WideResnet convolutional block."""
  return [
      tl.BatchNorm(momentum=bn_momentum, mode=mode),
      tl.Relu(),
      tl.Conv(channels, (3, 3), strides, padding='SAME'),
      tl.BatchNorm(momentum=bn_momentum, mode=mode),
      tl.Relu(),
      tl.Conv(channels, (3, 3), padding='SAME'),
  ]
def WideResnetBlock ( channels , strides = ( 1 , 1 ) , bn_momentum = 0.9 , mode = 'train' ) : return [ tl . BatchNorm ( momentum = bn_momentum , mode = mode ) , tl . Relu ( ) , tl . Conv ( channels , ( 3 , 3 ) , strides , padding = 'SAME' ) , tl . BatchNorm ( momentum = bn_momentum , mode = mode ) , tl . Relu ( ) , tl . Conv ( channels , ( 3 , 3 ) , padding = 'SAME' ) , ]