code: def quantization_pass(tfssa):
      """
      Delete activation quantization ops and repair TF graph:
          If the FakeQuant op is not connected to constant inputs (which means that the op performs activation
          quantization) then delete that FakeQuant op and repair the graph.
      Edit weight quantization ops:
          If the FakeQuant op is connected to constant inputs then add its attributes to its output op so that parameters
          min, max, narrow_range, num_bits are available (in addition to weights) to downstream ops for denoting and
          supporting weight quantization.
      """
      for v in tfssa.functions.values():
          quantization_pass_impl(v)
  
label_desc: Use image node_id 3 for calling a global function with example usage: quantization_pass(tfssa) without return types