
from __future__ import annotations



def 						lowercase_      (       A__ = 4		)							->							list[list[int]]:
    """simple docstring"""

    snake_case								= abs(A__		) or 4
    return [[1 + x + y * row_size for x in range(A__		)] for y in range(A__		)]



def 						lowercase_      (       A__		)							->							list[list[int]]:
    """simple docstring"""

    return reverse_row(transpose(A__		)		)
    # OR.. transpose(reverse_column(matrix))



def 						lowercase_      (       A__		)							->							list[list[int]]:
    """simple docstring"""

    return reverse_row(reverse_column(A__		)		)
    # OR.. reverse_column(reverse_row(matrix))



def 						lowercase_      (       A__		)							->							list[list[int]]:
    """simple docstring"""

    return reverse_column(transpose(A__		)		)
    # OR.. transpose(reverse_row(matrix))



def 						lowercase_      (       A__		)							->							list[list[int]]:
    """simple docstring"""

    snake_case								= [list(A__		) for x in zip(*A__		)]
    return matrix



def 						lowercase_      (       A__		)							->							list[list[int]]:
    """simple docstring"""

    snake_case								= matrix[::-1]
    return matrix



def 						lowercase_      (       A__		)							->							list[list[int]]:
    """simple docstring"""

    snake_case								= [x[::-1] for x in matrix]
    return matrix



def 						lowercase_      (       A__		)							->							None:
    """simple docstring"""

    for i in matrix:
        print(*A__		)


if __name__ == "__main__":
   _A   =			make_matrix()
   print("\norigin:\n")
   print_matrix(matrix)
   print("\nrotate 90 counterclockwise:\n")
   print_matrix(rotate_aa(matrix))

   _A   =			make_matrix()
   print("\norigin:\n")
   print_matrix(matrix)
   print("\nrotate 180:\n")
   print_matrix(rotate_aaa(matrix))

   _A   =			make_matrix()
   print("\norigin:\n")
   print_matrix(matrix)
   print("\nrotate 270 counterclockwise:\n")
   print_matrix(rotate_aaa(matrix))



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


_A   =			logging.get_logger(__name__)

_A   =			{
    "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		(  A_  ):
     UpperCAmelCase__    :							str									=		"realm"





     def __init__(self				:   Optional[int]    ,   _A				:   Optional[Any]=3_0_5_2_2    ,   _A				:   Tuple=7_6_8    ,   _A				:   List[str]=1_2_8    ,   _A				:   Optional[Any]=1_2    ,   _A				:   Dict=1_2    ,   _A				:   Tuple=8    ,   _A				:   Dict=3_0_7_2    ,   _A				:   Union[str, Any]="gelu_new"    ,   _A				:   Any=0.1    ,   _A				:   int=0.1    ,   _A				:   Union[str, Any]=5_1_2    ,   _A				:   List[str]=2    ,   _A				:   Any=0.02    ,   _A				:   int=1E-12    ,   _A				:   Tuple=2_5_6    ,   _A				:   Optional[Any]=1_0    ,   _A				:   Any=1E-3    ,   _A				:   int=5    ,   _A				:   int=3_2_0    ,   _A				:   Dict=1_3_3_5_3_7_1_8    ,   _A				:   Any=5_0_0_0    ,   _A				:   Union[str, Any]=1    ,   _A				:   Dict=0    ,   _A				:   int=2    ,   **_A				:   Union[str, Any]    ,   )						->						Optional[Any]:
         super().__init__(pad_token_id=_A    ,   bos_token_id=_A    ,   eos_token_id=_A    ,   **_A       )

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

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

         # Retrieval config
         snake_case								= num_block_records
         snake_case								= searcher_beam_size

