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

def _collect_outputs(self):
        output_klass = make_klass(self.output_spec)
        output = output_klass(**{f.name: None for f in attr.fields(output_klass)})
        # collecting outputs from tasks
        output_wf = {}
        for name, val in self._connections:
            if not isinstance(val, LazyField):
                raise ValueError("all connections must be lazy")
            output_wf[name] = val.get_value(self)
        return attr.evolve(output, **output_wf)

def _collect_outputs(self):
        run_output = self.output_
        self.output_spec = output_from_inputfields(self.output_spec, self.inputs)
        output_klass = make_klass(self.output_spec)
        output = output_klass(**{f.name: None for f in attr.fields(output_klass)})
        other_output = output.collect_additional_outputs(
            self.input_spec, self.inputs, self.output_dir
        )
        return attr.evolve(output, **run_output, **other_output)

def _collect_outputs(self):
        error = False
        output_klass = make_klass(self.output_spec)
        output = output_klass(**{f.name: None for f in attr.fields(output_klass)})
        # collecting outputs from tasks
        output_wf = {}
        for name, val in self._connections:
            if not isinstance(val, LazyField):
                raise ValueError("all connections must be lazy")
            try:
                val_out = val.get_value(self)
                output_wf[name] = val_out
            except ValueError:
                output_wf[name] = None
                # checking if the tasks has predecessors that raises error
                if isinstance(getattr(self, val.name)._errored, list):
                    raise ValueError(
                        f"Tasks {getattr(self, val.name)._errored} raised an error"
                    )

def _collect_outputs(self):
        run_output = self.output_
        self.output_spec = output_from_inputfields(self.output_spec, self.inputs)
        output_klass = make_klass(self.output_spec)
        output = output_klass(**{f.name: None for f in attr.fields(output_klass)})
        other_output = output.collect_additional_outputs(
            self.input_spec, self.inputs, self.output_dir
        )
        return attr.evolve(output, **run_output, **other_output)

def __setstate__(self, state):
        state["input_spec"] = cp.loads(state["input_spec"])
        state["output_spec"] = cp.loads(state["output_spec"])
        state["inputs"] = make_klass(state["input_spec"])(**state["inputs"])
        self.__dict__.update(state)

def output_names(self):
        """Get the names of the parameters generated by the task."""
        output_spec_names = [f.name for f in attr.fields(make_klass(self.output_spec))]
        from_input_spec_names = output_names_from_inputfields(self.inputs)
        return output_spec_names + from_input_spec_names

Set particular inputs to this node.
        messenger_args :
            TODO
        messengers :
            TODO

        """
        from .. import check_latest_version

        if TaskBase._etelemetry_version_data is None:
            TaskBase._etelemetry_version_data = check_latest_version()

        self.name = name
        if not self.input_spec:
            raise Exception("No input_spec in class: %s" % self.__class__.__name__)
        klass = make_klass(self.input_spec)
        # todo should be used to input_check in spec??
        self.inputs = klass(
            **{
                (f.name[1:] if f.name.startswith("_") else f.name): f.default
                for f in attr.fields(klass)
            }
        )
        self.input_names = [
            field.name
            for field in attr.fields(klass)
            if field.name not in ["_func", "_graph_checksums"]
        ]
        # dictionary to save the connections with lazy fields
        self.inp_lf = {}
        self.state = None
        self._output = {}