code: def act_and_mul(in_deltas, hs, activation):
      if iscontiguous(in_deltas._tensor) and iscontiguous(hs._tensor):
          if isinstance(activation, Rectlinclip) and (
              activation.slope == 0
          ):
              _in_deltas = ffi.cast(
                  "float *", ffi.from_buffer(in_deltas._tensor)
              )
              _hs = ffi.cast("float *", ffi.from_buffer(hs._tensor))
              NervanaObject.be.mathlib.cmath_act_and_mul(
                  _in_deltas, _hs, in_deltas.size, activation.xcut
              )
              return True
          else:
              return False
      else:
          return False
  
imports: import sys
  import numpy
  from cffi import FFI
  from neon import NervanaObject
  from neon.transforms import Rectlinclip
label_desc: Use image node_id 27 for calling a global function with example usage: act_and_mul(in_deltas, hs, activation) and returns: False, True, False