code: def constant_propagation(tfssa):
      # we are going to rely on the TensorFlow graph to perform constant
      # propagation. For each graph, we construct a new graph comprising
      # only a subset of nodes that are constant nodes.
  
      for f in tfssa.functions.values():
          const_nodes_info = _get_const_nodes(f)
          _constant_propagation(f, *const_nodes_info)
  
file_path: coremltools/coremltools/converters/mil/frontend/tensorflow/tf_graph_pass/constant_propagation.py
imports: import gc
  from distutils.version import StrictVersion
  import tensorflow
  from coremltools import _logger
  from coremltools._deps import _get_version
  from coremltools.converters.mil.mil import types
  from coremltools.converters.mil.mil.types.type_mapping import numpy_val_to_builtin_val
  from ..basic_graph_ops import const_determined_nodes
label_desc: Use image node_id 3 for calling a global function with example usage: constant_propagation(tfssa) without return types