code: def test(
      self,
      model_w_task,
      query,
      inf_kwargs,
      assert_fn,
  ):
      model, task = model_w_task
      dtype = torch.float16
      if dtype not in get_accelerator().supported_dtypes():
          pytest.skip(
              f"Acceleraor {get_accelerator().device_name()} does not support {dtype}."
          )
  
      local_rank = int(os.getenv("LOCAL_RANK", "0"))
  
      pipe = pipeline(
          task,
          model=model,
          model_kwargs={"low_cpu_mem_usage": True},
          device=local_rank,
          framework="pt",
      )
      bs_output = pipe(query, **inf_kwargs)
      pipe.model = deepspeed.init_inference(
          pipe.model,
          mp_size=self.world_size,
          dtype=dtype,
          replace_method="auto",
          replace_with_kernel_inject=True,
      )
  
      ds_output = pipe(query, **inf_kwargs)
  
      assert assert_fn(bs_output, ds_output)
  
imports: import os
  import time
  import torch
  import pytest
  import itertools
  import deepspeed
  from deepspeed.git_version_info import torch_info
  from unit.common import DistributedTest
  from packaging import version
  from deepspeed.ops.op_builder import OpBuilder
  from transformers import pipeline, AutoTokenizer
  from transformers.models.t5.modeling_t5 import T5Block
  from transformers.models.roberta.modeling_roberta import RobertaLayer
  from huggingface_hub import HfApi
  from deepspeed.model_implementations import DeepSpeedTransformerInference
  from torch import nn
  from deepspeed.accelerator import get_accelerator
  from deepspeed.ops.op_builder import InferenceBuilder
label_desc: Use image node_id 1 for calling the TestLowCpuMemUsage obj's underlying member method code with example usage: obj.test(model_w_task, query, inf_kwargs, assert_fn) without return types