





'''simple docstring'''

import logging
import os
import sys
from pathlib import Path
from unittest.mock import patch

from parameterized import parameterized
from run_eval import run_generate
from run_eval_search import run_search

from transformers.testing_utils import CaptureStdout, TestCasePlus, slow
from utils import ROUGE_KEYS


logging.basicConfig(level=logging.DEBUG)
UpperCAmelCase					:		List[str]		=							logging.getLogger()




def    _a    (							lowerCAmelCase_			,      lowerCAmelCase_	):





      """simple docstring"""



      _snake_case		:	Union[str, Any]					     =     '''\n'''.join(lowerCAmelCase_	)
      Path(lowerCAmelCase_	).open('''w'''	).writelines(lowerCAmelCase_	)


UpperCAmelCase					:		Union[str, Any]		=							'patrickvonplaten/t5-tiny-random'
UpperCAmelCase					:		Optional[int]		=							'sshleifer/bart-tiny-random'
UpperCAmelCase					:		List[Any]		=							'sshleifer/tiny-mbart'

UpperCAmelCase					:		List[str]		=							logging.StreamHandler(sys.stdout)
logger.addHandler(stream_handler)
logging.disable(logging.CRITICAL)  # remove noisy download output from tracebacks





class lowerCamelCase						(a__					):







  def 				UpperCAmelCase_				(		self     ,     lowercase__		)		->						List[Any]:






        """simple docstring"""





        _snake_case		:	Tuple					     =     Path(self.get_auto_remove_tmp_dir()		) / '''utest_input.source'''
        _snake_case		:	Union[str, Any]					     =     input_file_name.parent / '''utest_output.txt'''
        assert not output_file_name.exists()
        _snake_case		:	Any					     =     [''' New York (CNN)When Liana Barrientos was 23 years old, she got married in Westchester County.''']
        _dump_articles(lowercase__     ,     lowercase__		)

        _snake_case		:	Union[str, Any]					     =     str(Path(self.get_auto_remove_tmp_dir()		) / '''scores.json'''		)
        _snake_case		:	Optional[Any]					     =     '''translation_en_to_de''' if model == T5_TINY else '''summarization'''
        _snake_case		:	Optional[int]					     =     F'''
            run_eval_search.py
            {model}
            {input_file_name}
            {output_file_name}
            --score_path {score_path}
            --task {task}
            --num_beams 2
            --length_penalty 2.0
            '''.split()

        with patch.object(lowercase__     ,     '''argv'''     ,     lowercase__		):
              run_generate()
              assert Path(lowercase__		).exists()
              # os.remove(Path(output_file_name))







  def 				UpperCAmelCase_				(		self		)		->						Optional[int]:






        """simple docstring"""





        self.run_eval_tester(lowercase__		)







  @parameterized.expand([BART_TINY, MBART_TINY]		)
  @slow
  def 				UpperCAmelCase_				(		self     ,     lowercase__		)		->						Any:






        """simple docstring"""





        self.run_eval_tester(lowercase__		)







  @parameterized.expand([T5_TINY, MBART_TINY]		)
  @slow
  def 				UpperCAmelCase_				(		self     ,     lowercase__		)		->						Union[str, Any]:






        """simple docstring"""





        _snake_case		:	Dict					     =     Path(self.get_auto_remove_tmp_dir()		) / '''utest_input.source'''
        _snake_case		:	Dict					     =     input_file_name.parent / '''utest_output.txt'''
        assert not output_file_name.exists()

        _snake_case		:	List[Any]					     =     {
            '''en''': ['''Machine learning is great, isn\'t it?''', '''I like to eat bananas''', '''Tomorrow is another great day!'''],
            '''de''': [
                '''Maschinelles Lernen ist großartig, oder?''',
                '''Ich esse gerne Bananen''',
                '''Morgen ist wieder ein toller Tag!''',
            ],
        }

        _snake_case		:	Tuple					     =     Path(self.get_auto_remove_tmp_dir()		)
        _snake_case		:	List[Any]					     =     str(tmp_dir / '''scores.json'''		)
        _snake_case		:	Tuple					     =     str(tmp_dir / '''val.target'''		)
        _dump_articles(lowercase__     ,     text['''en''']		)
        _dump_articles(lowercase__     ,     text['''de''']		)
        _snake_case		:	List[Any]					     =     '''translation_en_to_de''' if model == T5_TINY else '''summarization'''
        _snake_case		:	Dict					     =     F'''
            run_eval_search.py
            {model}
            {str(lowercase__		)}
            {str(lowercase__		)}
            --score_path {score_path}
            --reference_path {reference_path}
            --task {task}
            '''.split()
        testargs.extend(['''--search''', '''num_beams=1:2 length_penalty=0.9:1.0''']		)

        with patch.object(lowercase__     ,     '''argv'''     ,     lowercase__		):
              with CaptureStdout() as cs:
                    run_search()
              _snake_case		:	List[str]					     =     [''' num_beams | length_penalty''', model, '''Best score args''']
              _snake_case		:	str					     =     ['''Info''']
              if "translation" in task:
                    expected_strings.append('''bleu'''		)
              else:
                    expected_strings.extend(lowercase__		)
              for w in expected_strings:
                    assert w in cs.out
              for w in un_expected_strings:
                    assert w not in cs.out
              assert Path(lowercase__		).exists()
              os.remove(Path(lowercase__		)		)









'''simple docstring'''

# Copyright 2023 The HuggingFace 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


UpperCAmelCase					:		Dict		=							{'configuration_timm_backbone': ['TimmBackboneConfig']}


try:
   if not is_torch_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   UpperCAmelCase					:		Union[str, Any]		=							['TimmBackbone']


if TYPE_CHECKING:
   from .configuration_timm_backbone import TimmBackboneConfig

   try:
      if not is_torch_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .modeling_timm_backbone import TimmBackbone

else:
   import sys

   UpperCAmelCase					:		Dict		=							_LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)


