code: def log_softmax(x, axis=1):
      """Channel-wise log-softmax function.
  
      This function computes its logarithm of softmax along the second axis.
      Let :math:`c = (c_1, c_2, \\dots, c_D)` be the slice of ``x`` along with
      the second axis. For each slice :math:`c`, it computes the logarithm of
      the function :math:`f(c)` defined as
  
      .. math::
          f(c) = {\\exp(c) \\over \\sum_{d} \\exp(c_d)}.
  
      This method is theoretically equivalent to ``log(softmax(x))`` but is more
      stable.
  
      .. note::
          ``log(softmax(x))`` may cause underflow when ``x`` is too small,
          because ``softmax(x)`` may returns ``0``.
          ``log_softmax`` method is more stable.
  
      Args:
          x (:class:`~chainer.Variable` or :ref:`ndarray`):
              Input variable.
              A :math:`n`-dimensional (:math:`n \\geq 2`) float array.
          axis (int): The axis along which the softmax is to be computed.
  
      Returns:
          ~chainer.Variable: Output variable.
          A :math:`n`-dimensional (:math:`n \\geq 2`) float array, which is the
          same shape with x.
  
      .. seealso:: :func:`~chainer.functions.softmax`
  
      .. admonition:: Example
  
          >>> x = np.array([[0, 1, 2], [0, 2, 4]], np.float32)
          >>> x
          array([[0., 1., 2.],
                 [0., 2., 4.]], dtype=float32)
          >>> F.log_softmax(x).array
          array([[-2.407606  , -1.4076059 , -0.4076059 ],
                 [-4.1429315 , -2.1429315 , -0.14293146]], dtype=float32)
          >>> np.allclose(F.log_softmax(x).data, F.log(F.softmax(x)).data)
          True
  
      """
      return LogSoftmax(axis=axis).apply((x,))[0]
  
imports: import chainer
  from chainer import backend
  from chainer.backends import cuda
  from chainer import function_node
  import chainer.functions
  from chainer.utils import type_check
  import chainerx
label_desc: Use image node_id 3 for calling a global function with example usage: log_softmax(x, axis) and returns: LogSoftmax