
"""simple docstring"""


import os
from datetime import datetime as dt

from github import Github


A_    							=					[
    """good first issue""",
    """feature request""",
    """wip""",
]






def  lowercase						(	):
			lowerCamelCase_					=  Github(os.environ['''GITHUB_TOKEN''']						)
			lowerCamelCase_					=  g.get_repo('''huggingface/accelerate'''						)
			lowerCamelCase_					=  repo.get_issues(state='''open'''						)

			for issue in open_issues:
						lowerCamelCase_					=  sorted([comment for comment in issue.get_comments()]	,key=lambda lowerCAmelCase__						: i.created_at	,reverse=lowerCAmelCase__						)
						lowerCamelCase_					=  comments[0] if len(lowerCAmelCase__						) > 0 else None
						lowerCamelCase_					=  dt.utcnow()
						lowerCamelCase_					=  (current_time - issue.updated_at).days
						lowerCamelCase_					=  (current_time - issue.created_at).days
						if (
						    last_comment is not None
						    and last_comment.user.login == "github-actions[bot]"
						    and days_since_updated > 7
						    and days_since_creation >= 30
						    and not any(label.name.lower() in LABELS_TO_EXEMPT for label in issue.get_labels()						)
						):
									# Close issue since it has been 7 days of inactivity since bot mention.
									issue.edit(state='''closed'''						)
						elif (
						    days_since_updated > 23
						    and days_since_creation >= 30
						    and not any(label.name.lower() in LABELS_TO_EXEMPT for label in issue.get_labels()						)
						):
									# Add stale comment
									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/accelerate/blob/main/CONTRIBUTING.md) '''
									    '''are likely to be ignored.'''						)


if __name__ == "__main__":
						main()





"""simple docstring"""


import unittest

from transformers import is_flax_available
from transformers.testing_utils import require_flax, require_sentencepiece, require_tokenizers, require_torch, slow


if is_flax_available():
						import optax
						from flax.training.common_utils import onehot

						from transformers import AutoTokenizer, FlaxMTaForConditionalGeneration
						from transformers.models.ta.modeling_flax_ta import shift_tokens_right




@require_torch
@require_sentencepiece
@require_tokenizers
@require_flax
class  __lowerCamelCase  ( unittest.TestCase			):




				@slow
				def        UpperCAmelCase__						(				self   ):
							lowerCamelCase_					=  FlaxMTaForConditionalGeneration.from_pretrained('''google/mt5-small'''   )
							lowerCamelCase_					=  AutoTokenizer.from_pretrained('''google/mt5-small'''   )

							lowerCamelCase_					=  tokenizer('''Hello there'''							,						return_tensors='''np'''   ).input_ids
							lowerCamelCase_					=  tokenizer('''Hi I am'''							,						return_tensors='''np'''   ).input_ids

							lowerCamelCase_					=  shift_tokens_right(UpperCAmelCase							,						model.config.pad_token_id							,						model.config.decoder_start_token_id   )

							lowerCamelCase_					=  model(UpperCAmelCase							,						decoder_input_ids=UpperCAmelCase   ).logits
							lowerCamelCase_					=  optax.softmax_cross_entropy(UpperCAmelCase							,						onehot(UpperCAmelCase							,						logits.shape[-1]   )   ).mean()

							lowerCamelCase_					=  -(labels.shape[-1] * loss.item())

							lowerCamelCase_					=  -8_4.9_1_2_7
							self.assertTrue(abs(mtf_score - EXPECTED_SCORE   ) < 1e-4   )



