class_docstr: Convolution2D --> Activation
  
  This is a chain that does two-dimensional convolution
  and applies an activation.
  
  The arguments are the same as those of
  :class:`chainer.links.Convolution2D`
  except for :obj:`activ`.
  
  Example:
  
      There are several ways to initialize a :class:`Conv2DActiv`.
  
      1. Give the first three arguments explicitly:
  
          >>> l = Conv2DActiv(5, 10, 3)
  
      2. Omit :obj:`in_channels` or fill it with :obj:`None`:
  
          In these ways, attributes are initialized at runtime based on
          the channel size of the input.
  
          >>> l = Conv2DActiv(10, 3)
          >>> l = Conv2DActiv(None, 10, 3)
  
  Args:
      in_channels (int or None): Number of channels of input arrays.
          If :obj:`None`, parameter initialization will be deferred until the
          first forward data pass at which time the size will be determined.
      out_channels (int): Number of channels of output arrays.
      ksize (int or tuple of ints): Size of filters (a.k.a. kernels).
          :obj:`ksize=k` and :obj:`ksize=(k, k)` are equivalent.
      stride (int or tuple of ints): Stride of filter applications.
          :obj:`stride=s` and :obj:`stride=(s, s)` are equivalent.
      pad (int or tuple of ints): Spatial padding width for input arrays.
          :obj:`pad=p` and :obj:`pad=(p, p)` are equivalent.
      dilate (int or tuple of ints): Dilation factor of filter applications.
          :obj:`dilate=d` and :obj:`dilate=(d, d)` are equivalent.
      nobias (bool): If :obj:`True`,
          then this link does not use the bias term.
      initialW (callable): Initial weight value. If :obj:`None`, the default
          initializer is used.
          May also be a callable that takes :obj:`numpy.ndarray` or
          :obj:`cupy.ndarray` and edits its value.
      initial_bias (callable): Initial bias value. If :obj:`None`, the bias
          is set to 0.
          May also be a callable that takes :obj:`numpy.ndarray` or
          :obj:`cupy.ndarray` and edits its value.
      activ (callable): An activation function. The default value is
          :func:`chainer.functions.relu`. If this is :obj:`None`,
          no activation is applied (i.e. the activation is the identity
          function).
code: def __init__(
      self,
      in_channels,
      out_channels,
      ksize=None,
      stride=1,
      pad=0,
      dilate=1,
      nobias=False,
      initialW=None,
      initial_bias=None,
      activ=relu,
  ):
      if ksize is None:
          out_channels, ksize, in_channels = (
              in_channels,
              out_channels,
              None,
          )
  
      self.activ = activ
      super(Conv2DActiv, self).__init__()
      with self.init_scope():
          if dilate > 1:
              self.conv = DilatedConvolution2D(
                  in_channels,
                  out_channels,
                  ksize,
                  stride,
                  pad,
                  dilate,
                  nobias,
                  initialW,
                  initial_bias,
              )
          else:
              self.conv = Convolution2D(
                  in_channels,
                  out_channels,
                  ksize,
                  stride,
                  pad,
                  nobias,
                  initialW,
                  initial_bias,
              )
  
file_path: chainercv/chainercv/links/connection/conv_2d_activ.py
imports: import chainer
  from chainer.functions import relu
  from chainer.links import Convolution2D
  from chainer.links import DilatedConvolution2D
label_desc: Use image node_id 1 to create a new Conv2DActiv object from inherited base classes: chainer with example: obj = Conv2DActiv(in_channels, out_channels, ksize, stride, pad, dilate, nobias, initialW, initial_bias, activ)