


"""simple docstring"""






def    A_ ( _lowerCAmelCase  :       list[list[int]]							):






     """simple docstring"""

     _a     						=					[list(_A							) for row in matrix]
     if matrix and isinstance(_A,  _A							):
          if isinstance(matrix[0],  _A							):
               _a     						=					0
               for row in matrix:
                    if prev_len == 0:
                         _a     						=					len(_A							)
                         _a     						=					True
                    else:
                         _a     						=					prev_len == len(_A							)
          else:
               _a     						=					True
     else:
          _a     						=					False

     return result
def    A_ ( _lowerCAmelCase  :       list[list[int]]							):






     """simple docstring"""

     if check_matrix(_A							) and len(_A							) > 0:
          _a     						=					[list(_A							) for row in a]
          _a     						=					len(_A							)
          if isinstance(a[0],  _A							):
               _a     						=					len(a[0]							)
          else:
               for dat in a:
                    print(_A							)
               return

          # horizotal printing increasing
          for i in range(0,  _A							):
               print(a[0][i]							)
          # vertical printing down
          for i in range(1,  _A							):
               print(a[i][mat_col - 1]							)
          # horizotal printing decreasing
          if mat_row > 1:
               for i in range(mat_col - 2,  -1,  -1							):
                    print(a[mat_row - 1][i]							)
        # vertical printing up
          for i in range(mat_row - 2,  0,  -1							):
               print(a[i][0]							)
          _a     						=					[row[1 : mat_col - 1] for row in a[1 : mat_row - 1]]
          if len(_A							) > 0:
               spiral_print_clockwise(_A							)
          else:
               return
     else:
          print('''Not a valid matrix'''							)
          return
def    A_ ( _lowerCAmelCase  :       list[list]							):






     """simple docstring"""

     if matrix:
          return list(matrix.pop(0							)							) + spiral_traversal(list(zip(*_A							)							)[::-1]							)
     else:
          return []


# driver code
if __name__ == "__main__":
   import doctest

   doctest.testmod()

   __snake_case												=							[[1, 2, 3, 4], [5, 6, 7, 8], [9, 10, 11, 12]]
   spiral_print_clockwise(a)


from collections import OrderedDict
from typing import Mapping

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


__A	:   List[Any]	=					logging.get_logger(__name__)

__A	:   Tuple	=					{
    'google/electra-small-generator': 'https://huggingface.co/google/electra-small-generator/resolve/main/config.json',
    'google/electra-base-generator': 'https://huggingface.co/google/electra-base-generator/resolve/main/config.json',
    'google/electra-large-generator': 'https://huggingface.co/google/electra-large-generator/resolve/main/config.json',
    'google/electra-small-discriminator': (
        'https://huggingface.co/google/electra-small-discriminator/resolve/main/config.json'
    ),
    'google/electra-base-discriminator': (
        'https://huggingface.co/google/electra-base-discriminator/resolve/main/config.json'
    ),
    'google/electra-large-discriminator': (
        'https://huggingface.co/google/electra-large-discriminator/resolve/main/config.json'
    ),
}


class 			_SCREAMING_SNAKE_CASE      (  lowerCAmelCase__):
						_UpperCamelCase:Tuple	=		"electra"







						def __init__(			self     ,						_SCREAMING_SNAKE_CASE=3_0522     ,						_SCREAMING_SNAKE_CASE=128     ,						_SCREAMING_SNAKE_CASE=256     ,						_SCREAMING_SNAKE_CASE=12     ,						_SCREAMING_SNAKE_CASE=4     ,						_SCREAMING_SNAKE_CASE=1024     ,						_SCREAMING_SNAKE_CASE="gelu"     ,						_SCREAMING_SNAKE_CASE=0.1     ,						_SCREAMING_SNAKE_CASE=0.1     ,						_SCREAMING_SNAKE_CASE=512     ,						_SCREAMING_SNAKE_CASE=2     ,						_SCREAMING_SNAKE_CASE=0.0_2     ,						_SCREAMING_SNAKE_CASE=1E-12     ,						_SCREAMING_SNAKE_CASE="first"     ,						_SCREAMING_SNAKE_CASE=True     ,						_SCREAMING_SNAKE_CASE="gelu"     ,						_SCREAMING_SNAKE_CASE=0.1     ,						_SCREAMING_SNAKE_CASE=0     ,						_SCREAMING_SNAKE_CASE="absolute"     ,						_SCREAMING_SNAKE_CASE=True     ,						_SCREAMING_SNAKE_CASE=None     ,						**_SCREAMING_SNAKE_CASE     ,						)->							Optional[int]:
													super().__init__(pad_token_id=_SCREAMING_SNAKE_CASE     ,						**_SCREAMING_SNAKE_CASE							)

													lowerCamelCase_								=vocab_size
													lowerCamelCase_								=embedding_size
													lowerCamelCase_								=hidden_size
													lowerCamelCase_								=num_hidden_layers
													lowerCamelCase_								=num_attention_heads
													lowerCamelCase_								=intermediate_size
													lowerCamelCase_								=hidden_act
													lowerCamelCase_								=hidden_dropout_prob
													lowerCamelCase_								=attention_probs_dropout_prob
													lowerCamelCase_								=max_position_embeddings
													lowerCamelCase_								=type_vocab_size
													lowerCamelCase_								=initializer_range
													lowerCamelCase_								=layer_norm_eps

													lowerCamelCase_								=summary_type
													lowerCamelCase_								=summary_use_proj
													lowerCamelCase_								=summary_activation
													lowerCamelCase_								=summary_last_dropout
													lowerCamelCase_								=position_embedding_type
													lowerCamelCase_								=use_cache
													lowerCamelCase_								=classifier_dropout


class 			_SCREAMING_SNAKE_CASE      (  lowerCAmelCase__):







						@property
						def        _snake_case				(			self							)->							Mapping[str, Mapping[int, str]]:
													if self.task == "multiple-choice":
																				lowerCamelCase_								={0: """batch""", 1: """choice""", 2: """sequence"""}
													else:
																				lowerCamelCase_								={0: """batch""", 1: """sequence"""}
													return OrderedDict(
													    [
													        ("""input_ids""", dynamic_axis),
													        ("""attention_mask""", dynamic_axis),
													        ("""token_type_ids""", dynamic_axis),
													    ]							)
