code: def fixture_pair_classification_pipeline(
      unload_registry: bool, tmp_path: Path
  ):
      from transformers.pipelines import PIPELINE_REGISTRY
  
      from .models.transformers import PairClassificationPipeline
  
      PIPELINE_REGISTRY.register_pipeline(
          TASK_NAME,
          pipeline_class=PairClassificationPipeline,
          pt_model=AutoModelForSequenceClassification,
      )
  
      config = transformers.BertConfig(
          vocab_size=99,
          hidden_size=32,
          num_hidden_layer=5,
          num_attention_heads=4,
          intermediate_size=37,
      )
      model = transformers.BertForSequenceClassification(config).eval()
      vocab_tokens = [
          "[UNK]",
          "[CLS]",
          "[SEP]",
          "[PAD]",
          "[MASK]",
          "I",
          "love",
          "hate",
          "you",
      ]
  
      vocab_file = tmp_path / "vocab.txt"
      with vocab_file.open("w", encoding="utf-8") as vocab_writer:
          vocab_writer.write("".join([x + "\n" for x in vocab_tokens]))
      classifier = pipeline(
          TASK_NAME,
          model=model,
          tokenizer=transformers.BertTokenizer(vocab_file.__fspath__()),
      )
      yield classifier
      if unload_registry:
          del PIPELINE_REGISTRY.supported_tasks[TASK_NAME]
  
imports: from __future__ import annotations
  import logging
  import os
  import typing
  import pytest
  import transformers
  from transformers.models.auto.modeling_auto import AutoModelForAudioClassification
  from transformers.models.auto.modeling_auto import AutoModelForCausalLM
  from transformers.models.auto.modeling_auto import AutoModelForSequenceClassification
  from transformers.pipelines import check_task
  from transformers.pipelines import pipeline
  from transformers.pipelines.audio_classification import AudioClassificationPipeline
  from transformers.trainer_utils import set_seed
  import bentoml
  from bentoml.exceptions import BentoMLException
  from bentoml.transformers import ModelOptions
label_desc: Use image node_id 10 for calling a global function with example usage: fixture_pair_classification_pipeline(unload_registry, tmp_path) without return types