




"""simple docstring"""







import argparse
from pathlib import Path

from transformers import AutoConfig, AutoTokenizer, RagConfig, RagSequenceForGeneration, RagTokenForGeneration





def 				lowercase       (snake_case__ :			Any   ,							snake_case__ :			Optional[int]   ,							snake_case__ :			List[str]   ,							snake_case__ :			Optional[Any]   ,							snake_case__ :			Union[str, Any] = None   ,							snake_case__ :			str = None   ,							snake_case__ :			Optional[int] = None   ,							)  ->	List[Any]:


				'''simple docstring'''






				if config_name_or_path is None:
								lowerCAmelCase						=					"""facebook/rag-token-base""" if model_type == """rag_token""" else """facebook/rag-sequence-base"""

				if generator_tokenizer_name_or_path is None:
								lowerCAmelCase						=					generator_name_or_path

				if question_encoder_tokenizer_name_or_path is None:
								lowerCAmelCase						=					question_encoder_name_or_path

				lowerCAmelCase						=					RagTokenForGeneration if model_type == """rag_token""" else RagSequenceForGeneration

				# Save model.
				lowerCAmelCase						=					RagConfig.from_pretrained(__lowercase			)
				lowerCAmelCase						=					AutoConfig.from_pretrained(__lowercase			)
				lowerCAmelCase						=					AutoConfig.from_pretrained(__lowercase			)

				lowerCAmelCase						=					gen_config
				lowerCAmelCase						=					question_encoder_config

				lowerCAmelCase						=					model_class.from_pretrained_question_encoder_generator(
				    __lowercase   ,							__lowercase   ,							config=__lowercase			)
				rag_model.save_pretrained(__lowercase			)

				# Sanity check.
				model_class.from_pretrained(__lowercase			)

				# Save tokenizers.
				lowerCAmelCase						=					AutoTokenizer.from_pretrained(__lowercase			)
				gen_tokenizer.save_pretrained(dest_dir / """generator_tokenizer/"""			)
				lowerCAmelCase						=					AutoTokenizer.from_pretrained(__lowercase			)
				question_encoder_tokenizer.save_pretrained(dest_dir / """question_encoder_tokenizer/"""			)


if __name__ == "__main__":
		a  =				argparse.ArgumentParser()
		parser.add_argument(
		    '--model_type',
		    choices=['rag_sequence', 'rag_token'],
		    required=True,
		    type=str,
		    help='RAG model type: rag_sequence, rag_token',
		)
		parser.add_argument('--dest', type=str, required=True, help='Path to the output checkpoint directory.')
		parser.add_argument('--generator_name_or_path', type=str, required=True, help='Generator model identifier')
		parser.add_argument(
		    '--question_encoder_name_or_path', type=str, required=True, help='Question encoder model identifier'
		)

		parser.add_argument(
		    '--generator_tokenizer_name_or_path',
		    type=str,
		    help='Generator tokenizer identifier, if not specified, resolves to ``generator_name_or_path``',
		)
		parser.add_argument(
		    '--question_encoder_tokenizer_name_or_path',
		    type=str,
		    help='Question encoder tokenizer identifier, if not specified, resolves to ``question_encoder_name_or_path``',
		)
		parser.add_argument(
		    '--config_name_or_path',
		    type=str,
		    help=(
		        'Identifier of the model config to use, if not provided, resolves to a base config for a given'
		        ' ``model_type``'
		    ),
		)

		a  =				parser.parse_args()

		a  =				Path(args.dest)
		dest_dir.mkdir(exist_ok=True)

		consolidate(
		    args.model_type,
		    args.generator_name_or_path,
		    args.question_encoder_name_or_path,
		    dest_dir,
		    args.config_name_or_path,
		    args.generator_tokenizer_name_or_path,
		    args.question_encoder_tokenizer_name_or_path,
		)













import math
from datetime import datetime, timedelta






def      _snake_case     (__lowercase):
   UpperCamelCase_						=  year % 19
   UpperCamelCase_						=  year % 4
   UpperCamelCase_						=  year % 7
   UpperCamelCase_						=  math.floor(year / 100)
   UpperCamelCase_						=  math.floor((13 + 8 * leap_day_inhibits) / 25)
   UpperCamelCase_						=  leap_day_inhibits / 4
   UpperCamelCase_						=  (
       15 - lunar_orbit_correction + leap_day_inhibits - leap_day_reinstall_number
   ) % 30
   UpperCamelCase_						=  (4 + leap_day_inhibits - leap_day_reinstall_number) % 7

   # days to be added to March 21
   UpperCamelCase_						=  (19 * metonic_cycle + secular_moon_shift) % 30

   # PHM -> Paschal Full Moon
   UpperCamelCase_						=  (
       2 * julian_leap_year
       + 4 * non_leap_year
       + 6 * days_to_add
       + century_starting_point
   ) % 7

   if days_to_add == 29 and days_from_phm_to_sunday == 6:
      return datetime(__lowercase     ,   4     ,   19)
   elif days_to_add == 28 and days_from_phm_to_sunday == 6:
      return datetime(__lowercase     ,   4     ,   18)
   else:
      return datetime(__lowercase     ,   3     ,   22) + timedelta(
          days=int(days_to_add + days_from_phm_to_sunday))


if __name__ == "__main__":
 for year in (1_9_9_4, 2_0_0_0, 2_0_1_0, 2_0_2_1, 2_0_2_3):
  snake_case__   :						Dict													=   """will be""" if year > datetime.now().year else """was"""
  print(f'Easter in {year} {tense} {gauss_easter(year)}')





