class_docstr: Inference model implementation for ragged batching for Llama-2 models.
class_docstr_tok: ["Inference","model","implementation","for","ragged","batching","for","Llama-2","models","."]
code: def positional_embedding_type(self) -> PositionalEmbeddingType:
      return PositionalEmbeddingType.rotate_half
  
imports: from typing import Iterable, Optional, Tuple
  import torch
  import deepspeed.comm
  from ...allocator import empty_from
  from ...inference_utils import ActivationType, DtypeEnum
  from ..None import *
  from ...modules.configs import *
  from ...modules.interfaces import *
  from ...ragged import RaggedBatchWrapper
  from .containers import PhiNonTransformerContainer, PhiTransformerContainer
label_desc: Use image node_id 12 for calling the PhiInferenceModel obj's underlying member method code with example usage: obj.positional_embedding_type() and returns: PositionalEmbeddingType