code: def _generate(self, model, tokenizer, prompt):
      local_rank = int(os.getenv("LOCAL_RANK", "0"))
      tokens = tokenizer.batch_encode_plus(
          prompt, return_tensors="pt", padding=True
      )
      for t in tokens:
          if torch.is_tensor(tokens[t]):
              tokens[t] = tokens[t].to(
                  f"{get_accelerator().device_name()}:{local_rank}"
              )
      output = model.generate(**tokens, do_sample=False, max_length=100)
      outputs = tokenizer.batch_decode(output, skip_special_tokens=True)
      return outputs
  
file_path: DeepSpeed/tests/unit/hybrid_engine/test_he_all.py
imports: import os
  import torch
  import pytest
  import deepspeed
  from deepspeed.ops.op_builder import OpBuilder
  from unit.common import DistributedTest
  from deepspeed.accelerator import get_accelerator
  from transformers import AutoConfig, AutoTokenizer, AutoModelForCausalLM
  from deepspeed.ops.op_builder import InferenceBuilder
label_desc: Use image node_id 1 for calling the TestHybridEngineTextGen obj's underlying member method code with example usage: obj._generate(model, tokenizer, prompt) and returns: outputs