How to use the pydra.engine.helpers.create_checksum function in pydra

"""
        self.state.prepare_states(self.inputs)
        self.state.prepare_inputs()
        if state_index is not None:
            inputs_copy = deepcopy(self.inputs)
            for key, ind in self.state.inputs_ind[state_index].items():
                setattr(
                    inputs_copy,
                    key.split(".")[1],
                    getattr(inputs_copy, key.split(".")[1])[ind],
                )
            input_hash = inputs_copy.hash
            if is_workflow(self):
                con_hash = hash_function(self._connections)
                hash_list = [input_hash, con_hash]
                checksum_ind = create_checksum(
                    self.__class__.__name__, self._checksum_wf(input_hash)
                )
            else:
                checksum_ind = create_checksum(self.__class__.__name__, input_hash)
            return checksum_ind
        else:
            checksum_list = []
            for ind in range(len(self.state.inputs_ind)):
                checksum_list.append(self.checksum_states(state_index=ind))
            return checksum_list

inputs_copy = deepcopy(self.inputs)
            for key, ind in self.state.inputs_ind[state_index].items():
                setattr(
                    inputs_copy,
                    key.split(".")[1],
                    getattr(inputs_copy, key.split(".")[1])[ind],
                )
            input_hash = inputs_copy.hash
            if is_workflow(self):
                con_hash = hash_function(self._connections)
                hash_list = [input_hash, con_hash]
                checksum_ind = create_checksum(
                    self.__class__.__name__, self._checksum_wf(input_hash)
                )
            else:
                checksum_ind = create_checksum(self.__class__.__name__, input_hash)
            return checksum_ind
        else:
            checksum_list = []
            for ind in range(len(self.state.inputs_ind)):
                checksum_list.append(self.checksum_states(state_index=ind))
            return checksum_list

inputs_copy = deepcopy(self.inputs)
            for key, ind in self.state.inputs_ind[state_index].items():
                setattr(
                    inputs_copy,
                    key.split(".")[1],
                    getattr(inputs_copy, key.split(".")[1])[ind],
                )
            input_hash = inputs_copy.hash
            if is_workflow(self):
                con_hash = hash_function(self._connections)
                hash_list = [input_hash, con_hash]
                checksum_ind = create_checksum(
                    self.__class__.__name__, self._checksum_wf(input_hash)
                )
            else:
                checksum_ind = create_checksum(self.__class__.__name__, input_hash)
            return checksum_ind
        else:
            checksum_list = []
            for ind in range(len(self.state.inputs_ind)):
                checksum_list.append(self.checksum_states(state_index=ind))
            return checksum_list

"""
        self.state.prepare_states(self.inputs)
        self.state.prepare_inputs()
        if state_index is not None:
            inputs_copy = deepcopy(self.inputs)
            for key, ind in self.state.inputs_ind[state_index].items():
                setattr(
                    inputs_copy,
                    key.split(".")[1],
                    getattr(inputs_copy, key.split(".")[1])[ind],
                )
            input_hash = inputs_copy.hash
            if is_workflow(self):
                con_hash = hash_function(self._connections)
                hash_list = [input_hash, con_hash]
                checksum_ind = create_checksum(
                    self.__class__.__name__, self._checksum_wf(input_hash)
                )
            else:
                checksum_ind = create_checksum(self.__class__.__name__, input_hash)
            return checksum_ind
        else:
            checksum_list = []
            for ind in range(len(self.state.inputs_ind)):
                checksum_list.append(self.checksum_states(state_index=ind))
            return checksum_list

def checksum(self):
        """ Calculates the unique checksum of the task.
            Used to create specific directory name for task that are run;
            and to create nodes checksums needed for graph checkums
            (before the tasks have inputs etc.)
        """
        input_hash = self.inputs.hash
        if self.state is None:
            self._checksum = create_checksum(self.__class__.__name__, input_hash)
        else:
            splitter_hash = hash_function(self.state.splitter)
            self._checksum = create_checksum(
                self.__class__.__name__, hash_function([input_hash, splitter_hash])
            )
        return self._checksum

def checksum(self):
        """ Calculates the unique checksum of the task.
            Used to create specific directory name for task that are run;
            and to create nodes checksums needed for graph checkums
            (before the tasks have inputs etc.)
        """
        # if checksum is called before run the _graph_checksums is not ready
        if is_workflow(self) and self.inputs._graph_checksums is attr.NOTHING:
            self.inputs._graph_checksums = [nd.checksum for nd in self.graph_sorted]

        input_hash = self.inputs.hash
        if not self.state:
            self._checksum = create_checksum(
                self.__class__.__name__, self._checksum_wf(input_hash)
            )
        else:
            self._checksum = create_checksum(
                self.__class__.__name__,
                self._checksum_wf(input_hash, with_splitter=True),
            )
        return self._checksum

def checksum(self):
        """ Calculates the unique checksum of the task.
            Used to create specific directory name for task that are run;
            and to create nodes checksums needed for graph checkums
            (before the tasks have inputs etc.)
        """
        # if checksum is called before run the _graph_checksums is not ready
        if is_workflow(self) and self.inputs._graph_checksums is attr.NOTHING:
            self.inputs._graph_checksums = [nd.checksum for nd in self.graph_sorted]

        input_hash = self.inputs.hash
        if not self.state:
            self._checksum = create_checksum(
                self.__class__.__name__, self._checksum_wf(input_hash)
            )
        else:
            self._checksum = create_checksum(
                self.__class__.__name__,
                self._checksum_wf(input_hash, with_splitter=True),
            )
        return self._checksum