code: def _generate(self, *inputs, **kwargs):
      # Reset KV-cache at the beginning of generate
      if hasattr(self.module, "reset_cache"):
          self.module.reset_cache()
      num_beams = 1
      if "generation_config" in kwargs:
          gen_config = kwargs["generation_config"]
          num_beams = getattr(gen_config, "num_beams", 1)
      if "num_beams" in kwargs:
          num_beams = kwargs["num_beams"]
  
      if num_beams > 1:
          raise NotImplementedError(
              "DeepSpeed does not support `num_beams` > 1, if this is important to you please "
              "add your request to: https://github.com/microsoft/DeepSpeed/issues/2506"
          )
  
      if ("input_ids" in kwargs) and (kwargs["input_ids"].dim() == 2):
          for input_tensor in kwargs["input_ids"]:
              tensor_length = input_tensor.shape[-1]
              if tensor_length > self._config.max_out_tokens:
                  raise RuntimeError(
                      f"Input with size {tensor_length} exceeds maximum length of {self._config.max_out_tokens}. Please increase `max_tokens` in the DeepSpeed Inference Config."
                  )
  
      return self.module.generate(*inputs, **kwargs)
  
imports: import torch
  import time
  import os
  from deepspeed import comm
  from deepspeed.utils.logging import log_dist
  from torch.nn.modules import Module
  from packaging import version
  from deepspeed.runtime.checkpoint_engine.torch_checkpoint_engine import TorchCheckpointEngine
  from deepspeed.utils.timer import SynchronizedWallClockTimer
  from ..runtime.state_dict_factory import SDLoaderFactory
  from ..runtime.weight_quantizer import WeightQuantization
  from ..module_inject import replace_transformer_layer, generic_injection
  from ..comm.comm import init_distributed
  from ..pipe import PipelineModule
  from ..moe.utils import has_moe_layers
  from ..module_inject import LinearAllreduce, LinearLayer, Normalize, ReplaceWithTensorSlicing
  from deepspeed.accelerator import get_accelerator
  from ..module_inject.policy import TransformerPolicy
  from ..module_inject.auto_tp import AutoTP
  from ..module_inject.replace_policy import generic_policies
  from ..module_inject.auto_tp_model_utils import build_bloom_alibi_tensor, build_mpt_atten_bias_tensor, build_mpt_alibi_tensor, get_alibi_mask
  from ..ops.transformer.inference.ds_attention import DeepSpeedSelfAttention
  from ..model_implementations.transformers.ds_transformer import DeepSpeedTransformerInference
  from torch import nn
label_desc: Use image node_id 27 for calling the InferenceEngine obj's underlying member method code with example usage: obj._generate() and returns: self