code: def _docs_statistics():
      _docs.set_doc(
          chainerx.amax,
          """amax(a, axis=None, keepdims=False)
  Returns the maximum of an array or the maximum along an axis.
  
  Note:
      When at least one element is NaN, the corresponding max value will be NaN.
  
  Args:
      a (~chainerx.ndarray): Array to take the maximum.
      axis (None or int or tuple of ints): Along which axis to take the maximum.
          The flattened array is used by default.
          If this is a tuple of ints, the maximum is selected over multiple
          axes, instead of a single axis or all the axes.
      keepdims (bool): If ``True``, the axis is remained as an axis of size one.
  
  Returns:
      :class:`~chainerx.ndarray`: The maximum of ``a``, along the axis if
      specified.
  
  Note:
      During backpropagation, this function propagates the gradient of the
      output array to the input array ``a``.
  
  .. seealso:: :func:`numpy.amax`
  """,
      )
  
      _docs.set_doc(
          chainerx.amin,
          """amin(a, axis=None, keepdims=False)
  Returns the minimum of an array or the minimum along an axis.
  
  Note:
      When at least one element is NaN, the corresponding min value will be NaN.
  
  Args:
      a (~chainerx.ndarray): Array to take the minimum.
      axis (None or int or tuple of ints): Along which axis to take the minimum.
          The flattened array is used by default.
          If this is a tuple of ints, the minimum is selected over multiple
          axes, instead of a single axis or all the axes.
      keepdims (bool): If ``True``, the axis is remained as an axis of size one.
  
  Returns:
      :class:`~chainerx.ndarray`: The minimum of ``a``, along the axis if
      specified.
  
  Note:
      During backpropagation, this function propagates the gradient of the
      output array to the input array ``a``.
  
  .. seealso:: :func:`numpy.amin`
  """,
      )
  
      _docs.set_doc(
          chainerx.mean,
          """mean(a, axis=None, keepdims=False)
  Compute the arithmetic mean along the specified axis.
  
  Returns the average of the array elements. The average is taken over the
  flattened array by default, otherwise over the specified axis.
  
  Args:
      a (~chainerx.ndarray): Array to take the mean of.
      axis (None or int or tuple of ints): Along which axis or axes to compute
      the mean. The flattened array is used by default.
      keepdims (bool): If this is set to True, the axes which are reduced are
      left in the result as dimensions with size one. With this option,
      the result will broadcast correctly against the input array.
  
  Returns:
      :class:`~chainerx.ndarray`: The mean of ``a``, along the axis or axes if
      specified.
  
  .. seealso:: :func:`numpy.mean`
  """,
      )
  
      _docs.set_doc(
          chainerx.var,
          """var(a, axis=None, keepdims=False)
  Compute the arithmetic var along the specified axis.
  
  Returns the var of the array elements. The var is taken over the flattened
  array by default, otherwise over the specified axis.
  
  Args:
      a (~chainerx.ndarray): Array to take the var of.
      axis (None or int or tuple of ints): Along which axis or axes to compute
      the var. The flattened array is used by default.
      keepdims (bool): If this is set to True, the axes which are reduced are
      left in the result as dimensions with size one. With this option,
      the result will broadcast correctly against the input array.
  
  Returns:
      :class:`~chainerx.ndarray`: The var of ``a``, along the axis or axes if
      specified.
  
  .. seealso:: :func:`numpy.var`
  """,
      )
  
file_path: chainer/chainerx/_docs/routines.py
imports: import chainerx
  from chainerx import _docs
label_desc: Use image node_id 11 for calling a global function with example usage: _docs_statistics() without return types