from ...configuration_utils import PretrainedConfig
from ...utils import logging


A   :     Dict       =				logging.get_logger(__name__)

A   :     int       =				{
    "google/realm-cc-news-pretrained-embedder": (
        "https://huggingface.co/google/realm-cc-news-pretrained-embedder/resolve/main/config.json"
    ),
    "google/realm-cc-news-pretrained-encoder": (
        "https://huggingface.co/google/realm-cc-news-pretrained-encoder/resolve/main/config.json"
    ),
    "google/realm-cc-news-pretrained-scorer": (
        "https://huggingface.co/google/realm-cc-news-pretrained-scorer/resolve/main/config.json"
    ),
    "google/realm-cc-news-pretrained-openqa": (
        "https://huggingface.co/google/realm-cc-news-pretrained-openqa/aresolve/main/config.json"
    ),
    "google/realm-orqa-nq-openqa": "https://huggingface.co/google/realm-orqa-nq-openqa/resolve/main/config.json",
    "google/realm-orqa-nq-reader": "https://huggingface.co/google/realm-orqa-nq-reader/resolve/main/config.json",
    "google/realm-orqa-wq-openqa": "https://huggingface.co/google/realm-orqa-wq-openqa/resolve/main/config.json",
    "google/realm-orqa-wq-reader": "https://huggingface.co/google/realm-orqa-wq-reader/resolve/main/config.json",
    # See all REALM models at https://huggingface.co/models?filter=realm
}


class      lowerCamelCase    (SCREAMING_SNAKE_CASE__    ):
  """simple docstring"""







  lowerCamelCase__   =  '''realm'''







  def __init__(							self       :				int     ,   __magic_name__       :				int=30_522     ,   __magic_name__       :				Optional[int]=768     ,   __magic_name__       :				Dict=128     ,   __magic_name__       :				int=12     ,   __magic_name__       :				Optional[Any]=12     ,   __magic_name__       :				Optional[Any]=8     ,   __magic_name__       :				str=3_072     ,   __magic_name__       :				Union[str, Any]="gelu_new"     ,   __magic_name__       :				int=0.1     ,   __magic_name__       :				List[Any]=0.1     ,   __magic_name__       :				str=512     ,   __magic_name__       :				str=2     ,   __magic_name__       :				Tuple=0.02     ,   __magic_name__       :				Optional[int]=1e-12     ,   __magic_name__       :				List[Any]=256     ,   __magic_name__       :				Any=10     ,   __magic_name__       :				Optional[Any]=1e-3     ,   __magic_name__       :				str=5     ,   __magic_name__       :				List[str]=320     ,   __magic_name__       :				Optional[int]=13_353_718     ,   __magic_name__       :				Dict=5_000     ,   __magic_name__       :				Optional[int]=1     ,   __magic_name__       :				Union[str, Any]=0     ,   __magic_name__       :				Tuple=2     ,   **__magic_name__       :				Dict     ,   )     ->		Union[str, Any]:
        super().__init__(pad_token_id=__magic_name__     ,   bos_token_id=__magic_name__     ,   eos_token_id=__magic_name__     ,   **__magic_name__      )

        # Common config
        SCREAMING_SNAKE_CASE_      =     vocab_size
        SCREAMING_SNAKE_CASE_      =     max_position_embeddings
        SCREAMING_SNAKE_CASE_      =     hidden_size
        SCREAMING_SNAKE_CASE_      =     retriever_proj_size
        SCREAMING_SNAKE_CASE_      =     num_hidden_layers
        SCREAMING_SNAKE_CASE_      =     num_attention_heads
        SCREAMING_SNAKE_CASE_      =     num_candidates
        SCREAMING_SNAKE_CASE_      =     intermediate_size
        SCREAMING_SNAKE_CASE_      =     hidden_act
        SCREAMING_SNAKE_CASE_      =     hidden_dropout_prob
        SCREAMING_SNAKE_CASE_      =     attention_probs_dropout_prob
        SCREAMING_SNAKE_CASE_      =     initializer_range
        SCREAMING_SNAKE_CASE_      =     type_vocab_size
        SCREAMING_SNAKE_CASE_      =     layer_norm_eps

        # Reader config
        SCREAMING_SNAKE_CASE_      =     span_hidden_size
        SCREAMING_SNAKE_CASE_      =     max_span_width
        SCREAMING_SNAKE_CASE_      =     reader_layer_norm_eps
        SCREAMING_SNAKE_CASE_      =     reader_beam_size
        SCREAMING_SNAKE_CASE_      =     reader_seq_len

        # Retrieval config
        SCREAMING_SNAKE_CASE_      =     num_block_records
        SCREAMING_SNAKE_CASE_      =     searcher_beam_size



import math
from datetime import datetime, timedelta


def    a__       (						__UpperCamelCase ):
      SCREAMING_SNAKE_CASE_      =     year % 1_9
      SCREAMING_SNAKE_CASE_      =     year % 4
      SCREAMING_SNAKE_CASE_      =     year % 7
      SCREAMING_SNAKE_CASE_      =     math.floor(year / 1_0_0 )
      SCREAMING_SNAKE_CASE_      =     math.floor((1_3 + 8 * leap_day_inhibits) / 2_5 )
      SCREAMING_SNAKE_CASE_      =     leap_day_inhibits / 4
      SCREAMING_SNAKE_CASE_      =     (
          1_5 - lunar_orbit_correction + leap_day_inhibits - leap_day_reinstall_number
      ) % 3_0
      SCREAMING_SNAKE_CASE_      =     (4 + leap_day_inhibits - leap_day_reinstall_number) % 7

      # days to be added to March 21
      SCREAMING_SNAKE_CASE_      =     (1_9 * metonic_cycle + secular_moon_shift) % 3_0

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

      if days_to_add == 2_9 and days_from_phm_to_sunday == 6:
            return datetime(__UpperCamelCase   ,					4   ,					1_9 )
      elif days_to_add == 2_8 and days_from_phm_to_sunday == 6:
            return datetime(__UpperCamelCase   ,					4   ,					1_8 )
      else:
            return datetime(__UpperCamelCase   ,					3   ,					2_2 ) + timedelta(
                days=int(days_to_add + days_from_phm_to_sunday ) )


if __name__ == "__main__":
      for year in (19_94, 20_00, 20_10, 20_21, 20_23):
            A   :     Dict       =				"will be" if year > datetime.now().year else "was"
            print(f"Easter in {year} {tense} {gauss_easter(year)}")


