code: 
  
  '''simple docstring'''
  
  
  
  
  
  # Copyright 2023 The HuggingFace Inc. team. All rights reserved.
  #
  # Licensed under the Apache License, Version 2.0 (the "License");
  # you may not use this file except in compliance with the License.
  # You may obtain a copy of the License at
  #
  #     http://www.apache.org/licenses/LICENSE-2.0
  #
  # Unless required by applicable law or agreed to in writing, software
  # distributed under the License is distributed on an "AS IS" BASIS,
  # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
  # See the License for the specific language governing permissions and
  # limitations under the License.
  from typing import TYPE_CHECKING
  
  from ..utils import (
      OptionalDependencyNotAvailable,
      _LazyModule,
      is_torch_available,
  )
  
  
  snake_case_    						=				{
      '''agents''': ['''Agent''', '''AzureOpenAiAgent''', '''HfAgent''', '''LocalAgent''', '''OpenAiAgent'''],
      '''base''': ['''PipelineTool''', '''RemoteTool''', '''Tool''', '''launch_gradio_demo''', '''load_tool'''],
  }
  
  try:
         if not is_torch_available():
                raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
         pass
  else:
         snake_case_    						=				['''DocumentQuestionAnsweringTool''']
         snake_case_    						=				['''ImageCaptioningTool''']
         snake_case_    						=				['''ImageQuestionAnsweringTool''']
         snake_case_    						=				['''ImageSegmentationTool''']
         snake_case_    						=				['''SpeechToTextTool''']
         snake_case_    						=				['''TextClassificationTool''']
         snake_case_    						=				['''TextQuestionAnsweringTool''']
         snake_case_    						=				['''TextSummarizationTool''']
         snake_case_    						=				['''TextToSpeechTool''']
         snake_case_    						=				['''TranslationTool''']
  
  if TYPE_CHECKING:
         from .agents import Agent, AzureOpenAiAgent, HfAgent, LocalAgent, OpenAiAgent
         from .base import PipelineTool, RemoteTool, Tool, launch_gradio_demo, load_tool
  
         try:
                if not is_torch_available():
                       raise OptionalDependencyNotAvailable()
         except OptionalDependencyNotAvailable:
                pass
         else:
                from .document_question_answering import DocumentQuestionAnsweringTool
                from .image_captioning import ImageCaptioningTool
                from .image_question_answering import ImageQuestionAnsweringTool
                from .image_segmentation import ImageSegmentationTool
                from .speech_to_text import SpeechToTextTool
                from .text_classification import TextClassificationTool
                from .text_question_answering import TextQuestionAnsweringTool
                from .text_summarization import TextSummarizationTool
                from .text_to_speech import TextToSpeechTool
                from .translation import TranslationTool
  else:
         import sys
  
         snake_case_    						=				_LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)
  
  
style_context: 
  
  # as due to their complexity multi-gpu tests could impact other tests, and to aid debug we have those in a separate module.
  
  import os
  import sys
  
  from transformers.testing_utils import TestCasePlus, execute_subprocess_async, get_gpu_count, require_torch_gpu, slow
  
  from .utils import load_json
  
  
  class    SCREAMING_SNAKE_CASE__      (__snake_case  ):
  
  
  
  
  
      @classmethod
      def    snake_case_       (   cls):
           return cls
  
  
  
  
  
      @slow
      @require_torch_gpu
      def    snake_case_       (   self):
           lowercase__					:     List[Any]   = self.get_auto_remove_tmp_dir()
           lowercase__					:     List[str]   = f"""
              --model_name Helsinki-NLP/opus-mt-en-ro
              --save_dir {output_dir}
              --data_dir {self.test_file_dir_str}/test_data/wmt_en_ro
              --num_beams 2
              --task translation
          """.split()
  
           # we want this test to run even if there is only one GPU, but if there are more we use them all
           lowercase__					:     int   = get_gpu_count()
           lowercase__					:     Tuple   = f"""
              -m torch.distributed.launch
              --nproc_per_node={n_gpu}
              {self.test_file_dir}/run_distributed_eval.py
          """.split()
           lowercase__					:     Optional[Any]   = [sys.executable] + distributed_args + args
           execute_subprocess_async(a		,     env=self.get_env())
  
           lowercase__					:     str   = os.path.join(a		,     'test_bleu.json')
           lowercase__					:     List[str]   = load_json(a)
           # print(metrics)
           self.assertGreaterEqual(metrics['bleu']		,     25)
  
  