code: def accuracy(y, t, ignore_label=None):
      """Computes multiclass classification accuracy of the minibatch.
  
      Args:
          y (:class:`~chainer.Variable` or :ref:`ndarray`):
              Array whose (i, j, k, ...)-th element indicates the score of
              the class j at the (i, k, ...)-th sample.
              The prediction label :math:`\\hat t` is calculated by the formula
              :math:`\\hat t(i, k, ...) = \\operatorname{\\mathrm{argmax}}_j \
  y(i, j, k, ...)`.
          t (:class:`~chainer.Variable` or :ref:`ndarray`):
              Array of ground truth labels.
          ignore_label (int or None): Skip calculating accuracy
              if the true label is ``ignore_label``.
  
      Returns:
          ~chainer.Variable: A variable holding a scalar array of the accuracy.
  
      .. note:: This function is non-differentiable.
  
      .. admonition:: Example
  
          We show the most common case, when ``y`` is the two dimensional array.
  
          >>> y = np.array([[0.1, 0.7, 0.2], # prediction label is 1
          ...               [8.0, 1.0, 2.0], # prediction label is 0
          ...               [-8.0, 1.0, 2.0], # prediction label is 2
          ...               [-8.0, -1.0, -2.0]]) # prediction label is 1
          >>> t = np.array([1, 0, 2, 1], np.int32)
          >>> F.accuracy(y, t).array \
  # 100% accuracy because all samples are correct
          array(1.)
          >>> t = np.array([1, 0, 0, 0], np.int32)
          >>> F.accuracy(y, t).array \
  # 50% accuracy because 1st and 2nd samples are correct.
          array(0.5)
          >>> F.accuracy(y, t, ignore_label=0).array \
  # 100% accuracy because of ignoring the 2nd, 3rd and 4th samples.
          array(1.)
  
      """
      (acc,) = Accuracy(ignore_label=ignore_label).apply((y, t))
      return acc
  
file_path: chainer/chainer/functions/evaluation/accuracy.py
imports: import numpy
  import six
  from chainer.backends import cuda
  from chainer import function_node
  from chainer.utils import type_check
  import chainerx
label_desc: Use image node_id 1 for calling a global function with example usage: accuracy(y, t, ignore_label) and returns: acc