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eig(x[, out1, out2])

eig on the last two dimension and broadcast to the rest. 
Results in a vector with the  eigenvalues and a matrix with the eigenvectors. 

src/n/u/numpy-1.8.1/numpy/linalg/linalg.py   numpy(Download)
    signature = 'D->DD' if isComplexType(t) else 'd->DD'
    w, vt = _umath_linalg.eig(a, signature=signature, extobj=extobj)
    if not isComplexType(t) and all(w.imag == 0.0):