code: def get_conv_outsize(size, k, s, p, cover_all=False, d=1):
      """Calculates output size of convolution.
  
      This function takes the size of input feature map, kernel, stride, and
      pooling of one particular dimension, then calculates the output feature
      map size of that dimension.
  
      .. seealso:: :func:`~chainer.utils.get_deconv_outsize`
  
      Args:
          size (int): The size of input feature map. It usually is the length of
              a side of feature map.
          k (int): The size of convolution kernel.
          s (int): The size of stride.
          p (int): The size of padding.
          cover_all (bool): Use ``cover_all`` option or not.
          d (int): The size of dilation.
  
      Returns:
          int: The expected output size of the convolution operation.
  
      """
      dk = k + (k - 1) * (d - 1)
      if cover_all:
          return (size + p * 2 - dk + s - 1) // s + 1
      else:
          return (size + p * 2 - dk) // s + 1
  
file_path: chainer/chainer/utils/conv.py
imports: import numpy
  import six
  from chainer.backends import cuda
label_desc: Use image node_id 1 for calling a global function with example usage: get_conv_outsize(size, k, s, p, cover_all, d) and returns: unknown, unknown