


'''simple docstring'''
import unittest

from transformers import (
    MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING,
    TF_MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING,
    TextaTextGenerationPipeline,
    pipeline,
)
from transformers.testing_utils import is_pipeline_test, require_tf, require_torch
from transformers.utils import is_torch_available

from .test_pipelines_common import ANY


if is_torch_available():
		import torch
@is_pipeline_test
class    lowercase	(							unittest.TestCase					):

		"""simple docstring"""

		_a     =				MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING
		_a     =				TF_MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING




		def     lowerCAmelCase__				(		self    ,   UpperCamelCase_    ,   UpperCamelCase_    ,   UpperCamelCase_							):

							'''simple docstring'''


							UpperCamelCase__   :Union[str, Any]												= TextaTextGenerationPipeline(model=UpperCamelCase_    ,   tokenizer=UpperCamelCase_							)
							return generator, ["Something to write", "Something else"]




		def     lowerCAmelCase__				(		self    ,   UpperCamelCase_    ,   UpperCamelCase_							):

							'''simple docstring'''


							UpperCamelCase__   :int												= generator('''Something there'''							)
							self.assertEqual(UpperCamelCase_    ,   [{'''generated_text''': ANY(UpperCamelCase_							)}]							)
							# These are encoder decoder, they don't just append to incoming string
							self.assertFalse(outputs[0]['''generated_text'''].startswith('''Something there'''							)							)

							UpperCamelCase__   :Dict												= generator(['''This is great !''', '''Something else''']    ,   num_return_sequences=2    ,   do_sample=UpperCamelCase_							)
							self.assertEqual(
							    UpperCamelCase_    ,   [
							        [{'''generated_text''': ANY(UpperCamelCase_							)}, {'''generated_text''': ANY(UpperCamelCase_							)}],
							        [{'''generated_text''': ANY(UpperCamelCase_							)}, {'''generated_text''': ANY(UpperCamelCase_							)}],
							    ]    ,   )

							UpperCamelCase__   :List[str]												= generator(
							    ['''This is great !''', '''Something else''']    ,   num_return_sequences=2    ,   batch_size=2    ,   do_sample=UpperCamelCase_							)
							self.assertEqual(
							    UpperCamelCase_    ,   [
							        [{'''generated_text''': ANY(UpperCamelCase_							)}, {'''generated_text''': ANY(UpperCamelCase_							)}],
							        [{'''generated_text''': ANY(UpperCamelCase_							)}, {'''generated_text''': ANY(UpperCamelCase_							)}],
							    ]    ,   )

							with self.assertRaises(UpperCamelCase_							):
												generator(4							)




		@require_torch
		def     lowerCAmelCase__				(		self							):

							'''simple docstring'''


							UpperCamelCase__   :str												= pipeline('''text2text-generation'''    ,   model='''patrickvonplaten/t5-tiny-random'''    ,   framework='''pt'''							)
							# do_sample=False necessary for reproducibility
							UpperCamelCase__   :Optional[Any]												= generator('''Something there'''    ,   do_sample=UpperCamelCase_							)
							self.assertEqual(UpperCamelCase_    ,   [{'''generated_text''': ''''''}]							)

							UpperCamelCase__   :Union[str, Any]												= 3
							UpperCamelCase__   :List[str]												= generator(
							    '''Something there'''    ,   num_return_sequences=UpperCamelCase_    ,   num_beams=UpperCamelCase_    ,   )
							UpperCamelCase__   :Any												= [
							    {'''generated_text''': '''Beide Beide Beide Beide Beide Beide Beide Beide Beide'''},
							    {'''generated_text''': '''Beide Beide Beide Beide Beide Beide Beide Beide'''},
							    {'''generated_text''': ''''''},
							]
							self.assertEqual(UpperCamelCase_    ,   UpperCamelCase_							)

							UpperCamelCase__   :List[str]												= generator('''This is a test'''    ,   do_sample=UpperCamelCase_    ,   num_return_sequences=2    ,   return_tensors=UpperCamelCase_							)
							self.assertEqual(
							    UpperCamelCase_    ,   [
							        {'''generated_token_ids''': ANY(torch.Tensor							)},
							        {'''generated_token_ids''': ANY(torch.Tensor							)},
							    ]    ,   )
							UpperCamelCase__   :Dict												= generator.model.config.eos_token_id
							UpperCamelCase__   :Any												= '''<pad>'''
							UpperCamelCase__   :Tuple												= generator(
							    ['''This is a test''', '''This is a second test''']    ,   do_sample=UpperCamelCase_    ,   num_return_sequences=2    ,   batch_size=2    ,   return_tensors=UpperCamelCase_    ,   )
							self.assertEqual(
							    UpperCamelCase_    ,   [
							        [
							            {'''generated_token_ids''': ANY(torch.Tensor							)},
							            {'''generated_token_ids''': ANY(torch.Tensor							)},
							        ],
							        [
							            {'''generated_token_ids''': ANY(torch.Tensor							)},
							            {'''generated_token_ids''': ANY(torch.Tensor							)},
							        ],
							    ]    ,   )




		@require_tf
		def     lowerCAmelCase__				(		self							):

							'''simple docstring'''


							UpperCamelCase__   :int												= pipeline('''text2text-generation'''    ,   model='''patrickvonplaten/t5-tiny-random'''    ,   framework='''tf'''							)
							# do_sample=False necessary for reproducibility
							UpperCamelCase__   :Dict												= generator('''Something there'''    ,   do_sample=UpperCamelCase_							)
							self.assertEqual(UpperCamelCase_    ,   [{'''generated_text''': ''''''}]							)



'''simple docstring'''
from datetime import datetime as dt
import os

from github import Github


__snake_case							      =     [
    '''good first issue''',
    '''good second issue''',
    '''good difficult issue''',
    '''feature request''',
    '''new model''',
    '''wip''',
]


def 			a      (			)  ->	List[str]:



					'''simple docstring'''






					UpperCamelCase__   :List[str]												= Github(os.environ['''GITHUB_TOKEN''']   )
					UpperCamelCase__   :Tuple												= g.get_repo('''huggingface/transformers'''   )
					UpperCamelCase__   :Union[str, Any]												= repo.get_issues(state='''open'''   )

					for issue in open_issues:
										UpperCamelCase__   :List[Any]												= sorted([comment for comment in issue.get_comments()] ,					key=lambda __a   : i.created_at ,					reverse=__a   )
										UpperCamelCase__   :List[Any]												= comments[0] if len(__a   ) > 0 else None
										if (
										    last_comment is not None
										    and last_comment.user.login == "github-actions[bot]"
										    and (dt.utcnow() - issue.updated_at).days > 7
										    and (dt.utcnow() - issue.created_at).days >= 30
										    and not any(label.name.lower() in LABELS_TO_EXEMPT for label in issue.get_labels()   )
										):
															# print(f"Would close issue {issue.number} since it has been 7 days of inactivity since bot mention.")
															issue.edit(state='''closed'''   )
										elif (
										    (dt.utcnow() - issue.updated_at).days > 23
										    and (dt.utcnow() - issue.created_at).days >= 30
										    and not any(label.name.lower() in LABELS_TO_EXEMPT for label in issue.get_labels()   )
										):
															# print(f"Would add stale comment to {issue.number}")
															issue.create_comment(
															    '''This issue has been automatically marked as stale because it has not had '''
															    '''recent activity. If you think this still needs to be addressed '''
															    '''please comment on this thread.\n\nPlease note that issues that do not follow the '''
															    '''[contributing guidelines](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md) '''
															    '''are likely to be ignored.'''   )


if __name__ == "__main__":
		main()