code: def inv(a):
      r"""
      Compute the (multiplicative) inverse of a matrix.
  
      Given a square matrix `a`, return the matrix `ainv` satisfying
      ``dot(a, ainv) = dot(ainv, a) = eye(a.shape[0])``.
  
      Parameters
      ----------
      a : (..., M, M) ndarray
          Matrix to be inverted.
  
      Returns
      -------
      ainv : (..., M, M) ndarray
          (Multiplicative) inverse of the matrix `a`.
  
      Raises
      ------
      MXNetError
          If `a` is not square or inversion fails.
  
      Examples
      --------
      >>> from mxnet import np
      >>> a = np.array([[1., 2.], [3., 4.]])
      array([[-2. ,  1. ],
             [ 1.5, -0.5]])
  
      Inverses of several matrices can be computed at once:
  
      >>> a = np.array([[[1., 2.], [3., 4.]], [[1, 3], [3, 5]]])
      >>> np.linalg.inv(a)
      array([[[-2.        ,  1.        ],
              [ 1.5       , -0.5       ]],
  
             [[-1.2500001 ,  0.75000006],
              [ 0.75000006, -0.25000003]]])
      """
      return _api_internal.inv(a)
  
file_path: mxnet/python/mxnet/ndarray/numpy/linalg.py
imports: import numpy
  from .None import _op
  from .None import _api_internal
label_desc: Use image node_id 8 for calling a global function with example usage: inv(a) and returns: _api_internal