code: def add(x1, x2):
      if (
          isfloat_tensor(x1)
          and isfloat_tensor(x2)
          and isccontiguous(x1)
          and isccontiguous(x2)
      ):
          if x1.shape == x2.shape and x1.size > omp_threshold:
              y = np.empty_like(x1)
              _x1 = ffi.cast("float *", ffi.from_buffer(x1))
              _x2 = ffi.cast("float *", ffi.from_buffer(x2))
              _y = ffi.cast("float *", ffi.from_buffer(y))
              NervanaObject.be.mathlib.cmath_add(_x1, _x2, x1.size, _y)
              return y
          elif (
              istensor2d(x1)
              and istensor1d(x2)
              and x1.shape[0] == x2.shape[0]
              and x1.size > omp_threshold
          ):
              y = np.empty_like(x1)
              _x1 = ffi.cast("float *", ffi.from_buffer(x1))
              _x2 = ffi.cast("float *", ffi.from_buffer(x2))
              _y = ffi.cast("float *", ffi.from_buffer(y))
              NervanaObject.be.mathlib.cmath_addmv(
                  _x1, _x2, x1.shape[0], x1.shape[1], _y
              )
              return y
          elif (
              istensor1d(x1)
              and istensor2d(x2)
              and x1.shape[0] == x2.shape[0]
              and x2.size > omp_threshold
          ):
              y = np.empty_like(x2)
              _x1 = ffi.cast("float *", ffi.from_buffer(x1))
              _x2 = ffi.cast("float *", ffi.from_buffer(x2))
              _y = ffi.cast("float *", ffi.from_buffer(y))
              NervanaObject.be.mathlib.cmath_addmv(
                  _x2, _x1, x2.shape[0], x2.shape[1], _y
              )
              return y
          else:
              return np.add(x1, x2)
      else:
          return np.add(x1, x2)
  
imports: import sys
  import numpy
  from cffi import FFI
  from neon import NervanaObject
  from neon.transforms import Rectlinclip
label_desc: Use image node_id 16 for calling a global function with example usage: add(x1, x2) and returns: np, y, y, y, np