code: def from_pb(
      cls,
      pb: generate_pb2.Batch,
      tokenizer: PreTrainedTokenizerBase,
      dtype: torch.dtype,
      device: torch.device,
  ) -> "CausalLMBatch":
      batch = super().from_pb(
          pb=pb, tokenizer=tokenizer, dtype=dtype, device=device
      )
      batch.keys_head_dim_last = False
      return batch
  
file_path: text-generation-inference/server/text_generation_server/models/bloom.py
imports: import torch
  import torch.distributed
  from typing import Optional, Type
  from transformers import AutoTokenizer, AutoConfig, PreTrainedTokenizerBase
  from text_generation_server.models.custom_modeling.bloom_modeling import BloomForCausalLM
  from text_generation_server.models import CausalLM
  from text_generation_server.models.causal_lm import CausalLMBatch
  from text_generation_server.pb import generate_pb2
  from text_generation_server.utils import initialize_torch_distributed, weight_files, Weights
label_desc: Use image node_id 1 for calling the BloomCausalLMBatch obj's underlying member method code with example usage: obj.from_pb(cls, pb, tokenizer, dtype, device) and returns: batch