code: def test_load_from_remote_uri(
      model_path, basic_model, mock_s3_bucket
  ):
      mlflow.sentence_transformers.save_model(
          model=basic_model, path=model_path
      )
      artifact_root = f"s3://{mock_s3_bucket}"
      artifact_path = "model"
      artifact_repo = S3ArtifactRepository(artifact_root)
      artifact_repo.log_artifacts(
          model_path, artifact_path=artifact_path
      )
      model_uri = os.path.join(artifact_root, artifact_path)
      loaded = mlflow.sentence_transformers.load_model(
          model_uri=str(model_uri)
      )
  
      encoding = loaded.encode(
          "I can see why these are useful when you do distance calculations on them!"
      )
  
      assert len(encoding) == 384
  
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 8 for calling a global function with example usage: test_load_from_remote_uri(model_path, basic_model, mock_s3_bucket) without return types