



'''simple docstring'''




from typing import Mapping

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxSeqaSeqConfigWithPast
from ...utils import logging


a     :    List[str] 						=					logging.get_logger(__name__)

a     :    List[str] 						=					{
    """t5-small""": """https://huggingface.co/t5-small/resolve/main/config.json""",
    """t5-base""": """https://huggingface.co/t5-base/resolve/main/config.json""",
    """t5-large""": """https://huggingface.co/t5-large/resolve/main/config.json""",
    """t5-3b""": """https://huggingface.co/t5-3b/resolve/main/config.json""",
    """t5-11b""": """https://huggingface.co/t5-11b/resolve/main/config.json""",
}

class     UpperCamelCase_				(							_a    ):
	lowercase    =				"""t5"""
	lowercase    =				["""past_key_values"""]
	lowercase    =				{"""hidden_size""": """d_model""", """num_attention_heads""": """num_heads""", """num_hidden_layers""": """num_layers"""}





	def __init__(						self	,	A=32128	,	A=512	,	A=64	,	A=2048	,	A=6	,	A=None	,	A=8	,	A=32	,	A=128	,	A=0.1	,	A=1e-6	,	A=1.0	,	A="relu"	,	A=True	,	A=True	,	A=0	,	A=1	,	**A	,	)    ->    List[str]:
								UpperCAmelCase  :	Optional[int]							  =	vocab_size
								UpperCAmelCase  :	str							  =	d_model
								UpperCAmelCase  :	Optional[Any]							  =	d_kv
								UpperCAmelCase  :	List[Any]							  =	d_ff
								UpperCAmelCase  :	List[str]							  =	num_layers
								UpperCAmelCase  :	Optional[int]							  =	(
								    num_decoder_layers if num_decoder_layers is not None else self.num_layers
								)  # default = symmetry
								UpperCAmelCase  :	str							  =	num_heads
								UpperCAmelCase  :	Union[str, Any]							  =	relative_attention_num_buckets
								UpperCAmelCase  :	str							  =	relative_attention_max_distance
								UpperCAmelCase  :	Union[str, Any]							  =	dropout_rate
								UpperCAmelCase  :	List[Any]							  =	layer_norm_epsilon
								UpperCAmelCase  :	Tuple							  =	initializer_factor
								UpperCAmelCase  :	List[Any]							  =	feed_forward_proj
								UpperCAmelCase  :	Tuple							  =	use_cache

								UpperCAmelCase  :	Dict							  =	self.feed_forward_proj.split("""-"""					)
								UpperCAmelCase  :	int							  =	act_info[-1]
								UpperCAmelCase  :	int							  =	act_info[0] == """gated"""

								if len(snake_case_					) > 1 and act_info[0] != "gated" or len(snake_case_					) > 2:
															raise ValueError(
															    f'''`feed_forward_proj`: {feed_forward_proj} is not a valid activation function of the dense layer.'''
															    """Please make sure `feed_forward_proj` is of the format `gated-{ACT_FN}` or `{ACT_FN}`, e.g. """
															    """\'gated-gelu\' or \'relu\'"""					)

								# for backwards compatibility
								if feed_forward_proj == "gated-gelu":
															UpperCAmelCase  :	int							  =	"""gelu_new"""

								super().__init__(
								    pad_token_id=snake_case_	,	eos_token_id=snake_case_	,	is_encoder_decoder=snake_case_	,	**snake_case_	,	)




class     UpperCamelCase_				(							_a    ):





	@property
	def 				_lowercase(						self					)    ->    Mapping[str, Mapping[int, str]]:
								UpperCAmelCase  :	Any							  =	{
								    """input_ids""": {0: """batch""", 1: """encoder_sequence"""},
								    """attention_mask""": {0: """batch""", 1: """encoder_sequence"""},
								}
								if self.use_past:
															UpperCAmelCase  :	Optional[int]							  =	"""past_encoder_sequence + sequence"""
															UpperCAmelCase  :	int							  =	{0: """batch"""}
															UpperCAmelCase  :	Tuple							  =	{0: """batch""", 1: """past_decoder_sequence + sequence"""}
								else:
															UpperCAmelCase  :	List[Any]							  =	{0: """batch""", 1: """decoder_sequence"""}
															UpperCAmelCase  :	str							  =	{0: """batch""", 1: """decoder_sequence"""}

								if self.use_past:
															self.fill_with_past_key_values_(snake_case_	,	direction="""inputs"""					)

								return common_inputs






	@property
	def 				_lowercase(						self					)    ->    int:
								return 13






'''simple docstring'''




from datetime import datetime as dt
import os

from github import Github


a     :    int      						=					[
    """good first issue""",
    """good second issue""",
    """good difficult issue""",
    """feature request""",
    """new model""",
    """wip""",
]



def    __lowerCamelCase						(      )   ->    Dict:
							UpperCAmelCase  :	str							  =	Github(os.environ["""GITHUB_TOKEN"""]	)
							UpperCAmelCase  :	Dict							  =	g.get_repo("""huggingface/transformers"""	)
							UpperCAmelCase  :	int							  =	repo.get_issues(state="""open"""	)

							for issue in open_issues:
														UpperCAmelCase  :	Optional[int]							  =	sorted([comment for comment in issue.get_comments()]			,       key=lambda _lowercase	: i.created_at			,       reverse=_lowercase	)
														UpperCAmelCase  :	Any							  =	comments[0] if len(_lowercase	) > 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 >= 3_0
														    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 > 2_3
														    and (dt.utcnow() - issue.created_at).days >= 3_0
														    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()

