class_docstr: Dimensioning properties
docstr: See ``DSInferenceModelBase.prepare_batch`` for documentation.
  
  This method assumes an autoregressive dense attention pattern. Override this method
  if this does not match the model's attention pattern.
docstr_tok: ["See","``","DSInferenceModelBase.prepare_batch","``","for","documentation",".","This","method","assumes","an","autoregressive","dense","attention","pattern",".","Override","this","method","if","this","does","not","match","the","model","'s","attention","pattern","."]
code: def prepare_batch(self, wrapped_batch: RaggedBatchWrapper) -> None:
      """
      See ``DSInferenceModelBase.prepare_batch`` for documentation.
  
      This method assumes an autoregressive dense attention pattern. Override this method
      if this does not match the model's attention pattern.
      """
      self.attn.build_atoms(wrapped_batch)
  
imports: from abc import abstractmethod
  from typing import Optional
  import torch
  from deepspeed.accelerator import get_accelerator
  from ..config_v2 import RaggedInferenceEngineConfig
  from ..inference_utils import ActivationType, ceil_div, is_gated
  from ..model_implementations import *
  from ..model_implementations.sharding import *
  from ..modules.configs import DSEmbeddingsConfig, DSLinearConfig, DSMoEConfig, DSNormConfig, DSSelfAttentionConfig, DSUnembedConfig, NormTypeEnum, PositionalEmbeddingType, RotateHalfConfig
  from ..modules import heuristics
  from ..ragged import DSSequenceDescriptor, KVCacheConfig, RaggedBatchWrapper
  from .inference_model_base import DSInferenceModelBase, DSModelImplementationConfig, MPType
  from ..inference_parameter import InferenceParameter
label_desc: Use image node_id 28 for calling the DSTransformerModelBase obj's underlying member method code with example usage: obj.prepare_batch(wrapped_batch) without return types