code: def test_dependency_mapping():
      pip_requirements = (
          mlflow.sentence_transformers.get_default_pip_requirements()
      )
  
      expected_requirements = {
          "sentence-transformers",
          "torch",
          "transformers",
      }
      assert {
          package.split("=")[0] for package in pip_requirements
      }.intersection(expected_requirements) == expected_requirements
  
      conda_requirements = (
          mlflow.sentence_transformers.get_default_conda_env()
      )
      pip_in_conda = {
          package.split("=")[0]
          for package in conda_requirements["dependencies"][2]["pip"]
      }
      expected_conda = {"mlflow"}
      expected_conda.update(expected_requirements)
      assert pip_in_conda.intersection(expected_conda) == expected_conda
  
imports: import json
  import os
  from unittest import mock
  import numpy
  import pandas
  import pytest
  import yaml
  from pyspark.sql import SparkSession
  from pyspark.sql.types import ArrayType, DoubleType
  from sentence_transformers import SentenceTransformer
  import mlflow
  import mlflow.pyfunc.scoring_server
  import mlflow.sentence_transformers
  from mlflow import pyfunc
  from mlflow.exceptions import MlflowException
  from mlflow.models import Model, infer_signature
  from mlflow.models.utils import _read_example
  from mlflow.store.artifact.s3_artifact_repo import S3ArtifactRepository
  from mlflow.utils.environment import _mlflow_conda_env
  from tests.helper_functions import _assert_pip_requirements, _compare_logged_code_paths, _mlflow_major_version_string, assert_register_model_called_with_local_model_path, pyfunc_serve_and_score_model
label_desc: Use image node_id 5 for calling a global function with example usage: test_dependency_mapping() without return types