'''simple docstring'''





import inspect
import os
import unittest

import torch

import accelerate
from accelerate import debug_launcher
from accelerate.test_utils import (
    execute_subprocess_async,
    require_cpu,
    require_huggingface_suite,
    require_multi_gpu,
    require_single_gpu,
)
from accelerate.utils import patch_environment




@require_huggingface_suite
class  __magic_name__  (		unittest.TestCase    ):





   """simple docstring"""




   def   lowerCAmelCase						(	self					:  Dict							):



    """simple docstring"""



    _UpperCamelCase:     List[Any]							= inspect.getfile(accelerate.test_utils							)
    _UpperCamelCase:     Optional[int]							= os.path.sep.join(
        mod_file.split(os.path.sep							)[:-1] + ['''scripts''', '''external_deps''', '''test_metrics.py''']							)

    from accelerate.test_utils.scripts.external_deps import test_metrics  # noqa: F401

    _UpperCamelCase:     List[str]							= test_metrics



   @require_cpu
   def   lowerCAmelCase						(	self					:  Union[str, Any]							):



    """simple docstring"""



    debug_launcher(self.test_metrics.main		,  num_processes=1							)



   @require_cpu
   def   lowerCAmelCase						(	self					:  Tuple							):



    """simple docstring"""



    debug_launcher(self.test_metrics.main							)



   @require_single_gpu
   def   lowerCAmelCase						(	self					:  Any							):



    """simple docstring"""



    self.test_metrics.main()



   @require_multi_gpu
   def   lowerCAmelCase						(	self					:  Any							):



    """simple docstring"""



    print(f"""Found {torch.cuda.device_count()} devices."""							)
    _UpperCamelCase:     str							= ['''torchrun''', f"""--nproc_per_node={torch.cuda.device_count()}""", self.test_file_path]
    with patch_environment(omp_num_threads=1							):
     execute_subprocess_async(_lowercase		,  env=os.environ.copy()							)
# 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 ..models.auto import AutoModelForSeqaSeqLM, AutoTokenizer
from .base import PipelineTool




class  __magic_name__  (		__a    ):





   """simple docstring"""




   lowerCAmelCase      :    Optional[Any]  			=   '''philschmid/bart-large-cnn-samsum'''
   lowerCAmelCase      :    Any  			=   (
       '''This is a tool that summarizes an English text. It takes an input `text` containing the text to summarize, '''
       '''and returns a summary of the text.'''
   )
   lowerCAmelCase      :    Any  			=   '''summarizer'''
   lowerCAmelCase      :    Tuple  			=   AutoTokenizer
   lowerCAmelCase      :    Optional[Any]  			=   AutoModelForSeqaSeqLM

   lowerCAmelCase      :    Union[str, Any]  			=   ['''text''']
   lowerCAmelCase      :    Dict  			=   ['''text''']



   def   lowerCAmelCase						(	self					:  str		,  _lowercase					:  Union[str, Any]							):



    """simple docstring"""



    return self.pre_processor(_lowercase		,  return_tensors='''pt'''		,  truncation=_lowercase							)



   def   lowerCAmelCase						(	self					:  List[Any]		,  _lowercase					:  Optional[Any]							):



    """simple docstring"""



    return self.model.generate(**_lowercase							)[0]



   def   lowerCAmelCase						(	self					:  int		,  _lowercase					:  List[str]							):



    """simple docstring"""



    return self.pre_processor.decode(_lowercase		,  skip_special_tokens=_lowercase		,  clean_up_tokenization_spaces=_lowercase							)