class_docstr: Parameter with list dependency.
  
  NOTE: This uses the tuple workaround for the `ParametrizedList` class
  as described in the docstring of `ParametrizedList`.
class_docstr_tok: ["Parameter","with","list","dependency",".","NOTE",":","This","uses","the","tuple","workaround","for","the","`","ParametrizedList","`","class","as","described","in","the","docstring","of","`","ParametrizedList","`","."]
code: def finalize(self) -> torch.Tensor:
      return self.inference_model.transform(
          torch.cat(tuple(self.params))
      )
  
file_path: DeepSpeed/tests/unit/inference/v2/model_implementations/parameters/utils.py
imports: import torch
  from deepspeed.accelerator import get_accelerator
  from deepspeed.inference.v2.allocator import on_device
  from deepspeed.inference.v2.inference_parameter import InferenceParameter
  from deepspeed.inference.v2.model_implementations.parameter_base import ParameterBase, ParametrizedList
label_desc: Use image node_id 1 for calling the ListParam obj's underlying member method code with example usage: obj.finalize() and returns: self