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inv(x[, out])

compute the inverse of the last two dimensions and broadcast to the rest. 
Results in the inverse matrices. 
    "(m,m)->(m,m)" 

src/n/u/numpy-1.8.1/numpy/linalg/linalg.py   numpy(Download)
    signature = 'D->D' if isComplexType(t) else 'd->d'
    extobj = get_linalg_error_extobj(_raise_linalgerror_singular)
    ainv = _umath_linalg.inv(a, signature=signature, extobj=extobj)
    return wrap(ainv.astype(result_t))