class_docstr: Implementation of a model for inference composable with ragged batching.
class_docstr_tok: ["Implementation","of","a","model","for","inference","composable","with","ragged","batching","."]
docstr: The flattened parameter buffer.
docstr_tok: ["The","flattened","parameter","buffer","."]
code: def flattened_params(self) -> Optional[torch.Tensor]:
      """
      The flattened parameter buffer.
      """
      return self._flattened_param_buffer
  
imports: from abc import ABC, abstractmethod
  from typing import Iterable, Optional, Tuple, Type
  import torch
  import deepspeed.comm
  from ..ragged import DSStateManager, RaggedBatchWrapper
  from ..ragged.manager_configs import KVCacheConfig
  from ..ragged import DSSequenceDescriptor
  from ..model_implementations.layer_container_base import LayerContainer
  from ..config_v2 import RaggedInferenceEngineConfig
  from .flat_model_helpers import ModelMetadata
label_desc: Use image node_id 9 for calling the DSInferenceModelBase obj's underlying member method code with example usage: obj.flattened_params() and returns: self