def _find_all_hints_in_graph_def(session):
    'Look at the current default graph and return a list of LiteFuncCall objs.\n\n  Args:\n    session: A TensorFlow session that contains the graph to convert.\n  Returns:\n    a list of `LifeFuncCall` objects in the form\n\n  '
    func_calls = _collections.defaultdict(_LiteFuncCall)
    seen_ops = set()
    for op in session.graph.get_operations():
        for operand in _itertools.chain(op.inputs, op.outputs):
            if (operand in seen_ops):
                continue
            seen_ops.add(operand)
            attr = operand.op.node_def.attr
            uuid = attr[OpHint.FUNCTION_UUID_ATTR].s
            if (OpHint.FUNCTION_UUID_ATTR not in attr):
                continue
            call_def = func_calls[uuid]
            call_def.uuid = uuid
            if (OpHint.FUNCTION_UUID_ATTR in attr):
                call_def.function_name = attr[OpHint.FUNCTION_NAME_ATTR].s
                if (OpHint.FUNCTION_INPUT_INDEX_ATTR in attr):
                    call_def.inputs[attr[OpHint.FUNCTION_INPUT_INDEX_ATTR].i] = operand
                if (OpHint.FUNCTION_OUTPUT_INDEX_ATTR in attr):
                    call_def.outputs[attr[OpHint.FUNCTION_OUTPUT_INDEX_ATTR].i] = operand
            for a in attr:
                if a.startswith('_tflite_attr_'):
                    call_def.params[a.replace('_tflite_attr_,', '')] = attr[a].tensor
    return func_calls
Look at the current default graph and return a list of LiteFuncCall objs.

Args:
  session: A TensorFlow session that contains the graph to convert.
Returns:
  a list of `LifeFuncCall` objects in the form
def _find_all_hints_in_graph_def(session):
    'Look at the current default graph and return a list of LiteFuncCall objs.\n\n  Args:\n    session: A TensorFlow session that contains the graph to convert.\n  Returns:\n    a list of `LifeFuncCall` objects in the form\n\n  '
    func_calls = _collections.defaultdict(_LiteFuncCall)
    seen_ops = set()
    for op in session.graph.get_operations():
        for operand in _itertools.chain(op.inputs, op.outputs):
            if (operand in seen_ops):
                continue
            seen_ops.add(operand)
            attr = operand.op.node_def.attr
            uuid = attr[OpHint.FUNCTION_UUID_ATTR].s
            if (OpHint.FUNCTION_UUID_ATTR not in attr):
                continue
            call_def = func_calls[uuid]
            call_def.uuid = uuid
            if (OpHint.FUNCTION_UUID_ATTR in attr):
                call_def.function_name = attr[OpHint.FUNCTION_NAME_ATTR].s
                if (OpHint.FUNCTION_INPUT_INDEX_ATTR in attr):
                    call_def.inputs[attr[OpHint.FUNCTION_INPUT_INDEX_ATTR].i] = operand
                if (OpHint.FUNCTION_OUTPUT_INDEX_ATTR in attr):
                    call_def.outputs[attr[OpHint.FUNCTION_OUTPUT_INDEX_ATTR].i] = operand
            for a in attr:
                if a.startswith('_tflite_attr_'):
                    call_def.params[a.replace('_tflite_attr_,', )] = attr[a].tensor
    return func_calls