"""simple docstring"""







import argparse
import importlib
from pathlib import Path


# Test all the extensions added in the setup
_a     :     Any= [
    'kernels/rwkv/wkv_cuda.cu',
    'kernels/rwkv/wkv_op.cpp',
    'kernels/deformable_detr/ms_deform_attn.h',
    'kernels/deformable_detr/cuda/ms_deform_im2col_cuda.cuh',
    'models/graphormer/algos_graphormer.pyx',
]
def   __UpperCAmelCase				(    UpperCAmelCase_    :				Union[str, Any]  )							->			Union[str, Any]:

	'''simple docstring'''





	for file in FILES_TO_FIND:
		if not (transformers_path / file).exists():
			return False
	return True


if __name__ == "__main__":
	_a     :     Dict= argparse.ArgumentParser()
	parser.add_argument("--check_lib", action="store_true", help="Whether to check the build or the actual package.")
	_a     :     List[str]= parser.parse_args()
	if args.check_lib:
		_a     :     Tuple= importlib.import_module("transformers")
		_a     :     Tuple= Path(transformers_module.__file__).parent
	else:
		_a     :     str= Path.cwd() / 'build/lib/transformers'
	if not test_custom_files_are_present(transformers_path):
		raise ValueError("The built release does not contain the custom files. Fix this before going further!")







"""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[Any]    							= logging.getLogger()

def lowercase_  (   _snake_case   ,_snake_case						):
							SCREAMING_SNAKE_CASE__						:       Union[str, Any]           =   """\n""".join(_snake_case						)
							Path(_snake_case						).open("""w"""						).writelines(_snake_case						)


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

UpperCAmelCase__      :    int    							= logging.StreamHandler(sys.stdout)
logger.addHandler(stream_handler)
logging.disable(logging.CRITICAL)  # remove noisy download output from tracebacks



class 	lowerCAmelCase_						(a__  ):


				"""simple docstring"""



				def 	__magic_name__    (self   ,       SCREAMING_SNAKE_CASE__    )					->		str:



											"""simple docstring"""




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

											SCREAMING_SNAKE_CASE__						:       Any           =   str(Path(self.get_auto_remove_tmp_dir()    ) / """scores.json"""    )
											SCREAMING_SNAKE_CASE__						:       Union[str, Any]           =   """translation_en_to_de""" if model == T5_TINY else """summarization"""
											SCREAMING_SNAKE_CASE__						:       Optional[Any]           =   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(SCREAMING_SNAKE_CASE__   ,       """argv"""   ,       SCREAMING_SNAKE_CASE__    ):
																		run_generate()
																		assert Path(SCREAMING_SNAKE_CASE__    ).exists()
																		# os.remove(Path(output_file_name))



				def 	__magic_name__    (self    )					->		Dict:



											"""simple docstring"""




											self.run_eval_tester(SCREAMING_SNAKE_CASE__    )



				@parameterized.expand([BART_TINY, MBART_TINY]    )
				@slow
				def 	__magic_name__    (self   ,       SCREAMING_SNAKE_CASE__    )					->		Dict:



											"""simple docstring"""




											self.run_eval_tester(SCREAMING_SNAKE_CASE__    )



				@parameterized.expand([T5_TINY, MBART_TINY]    )
				@slow
				def 	__magic_name__    (self   ,       SCREAMING_SNAKE_CASE__    )					->		Dict:



											"""simple docstring"""




											SCREAMING_SNAKE_CASE__						:       List[Any]           =   Path(self.get_auto_remove_tmp_dir()    ) / """utest_input.source"""
											SCREAMING_SNAKE_CASE__						:       int           =   input_file_name.parent / """utest_output.txt"""
											assert not output_file_name.exists()

											SCREAMING_SNAKE_CASE__						:       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!""",
											    ],
											}

											SCREAMING_SNAKE_CASE__						:       List[str]           =   Path(self.get_auto_remove_tmp_dir()    )
											SCREAMING_SNAKE_CASE__						:       Tuple           =   str(tmp_dir / """scores.json"""    )
											SCREAMING_SNAKE_CASE__						:       Tuple           =   str(tmp_dir / """val.target"""    )
											_dump_articles(SCREAMING_SNAKE_CASE__   ,       text["""en"""]    )
											_dump_articles(SCREAMING_SNAKE_CASE__   ,       text["""de"""]    )
											SCREAMING_SNAKE_CASE__						:       str           =   """translation_en_to_de""" if model == T5_TINY else """summarization"""
											SCREAMING_SNAKE_CASE__						:       List[Any]           =   F'''
            run_eval_search.py
            {model}
            {str(SCREAMING_SNAKE_CASE__    )}
            {str(SCREAMING_SNAKE_CASE__    )}
            --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(SCREAMING_SNAKE_CASE__   ,       """argv"""   ,       SCREAMING_SNAKE_CASE__    ):
																		with CaptureStdout() as cs:
																									run_search()
																		SCREAMING_SNAKE_CASE__						:       Optional[Any]           =   [""" num_beams | length_penalty""", model, """Best score args"""]
																		SCREAMING_SNAKE_CASE__						:       Any           =   ["""Info"""]
																		if "translation" in task:
																									expected_strings.append("""bleu"""    )
																		else:
																									expected_strings.extend(SCREAMING_SNAKE_CASE__    )
																		for w in expected_strings:
																									assert w in cs.out
																		for w in un_expected_strings:
																									assert w not in cs.out
																		assert Path(SCREAMING_SNAKE_CASE__    ).exists()
																		os.remove(Path(SCREAMING_SNAKE_CASE__    )    )




