code: def __init__(self, context):
      self.tokenizer = BertTokenizer.from_pretrained(
          "bert-base-uncased"
      )
      self.model = BertModel.from_pretrained(
          "bert-base-uncased", output_hidden_states=True
      )
  
      self.device = context.device
  
      self.model = context.prepare_model_for_inference(self.model)
  
      self.output = []
  
      self.context = context
      self.last_index = 0
      self.rank = self.context.get_distributed_rank()
  
      self.output_dir = "/tmp/data/bert_scidocs_embeddings"
      os.makedirs(self.output_dir, exist_ok=True)
  
file_path: determined/examples/features/torch_batch_process_embeddings/bert_embedding_generation.py
imports: import logging
  import os
  import pathlib
  import shutil
  import chromadb
  import torch
  from datasets import load_dataset
  from transformers import BertModel, BertTokenizer
  from determined.pytorch import experimental
label_desc: Use image node_id 1 to create a new EmbeddingProcessor object from inherited base classes: experimental with example: obj = EmbeddingProcessor(context)