





'''simple docstring'''






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


A__							:  Dict    =logging.get_logger(__name__)

A__							:  Tuple    ={
    '''alibaba-damo/mgp-str-base''': '''https://huggingface.co/alibaba-damo/mgp-str-base/resolve/main/config.json''',
}




class 					UpperCAmelCase	(     snake_case_  ):
      _lowercase:     Any			=  '''mgp-str'''




      def __init__(     self     :					Any     ,     __snake_case     :					Tuple=[32, 1_28]     ,     __snake_case     :					List[Any]=4     ,     __snake_case     :					int=3     ,     __snake_case     :					int=27     ,     __snake_case     :					Union[str, Any]=38     ,     __snake_case     :					Dict=5_02_57     ,     __snake_case     :					Optional[Any]=3_05_22     ,     __snake_case     :					Optional[Any]=7_68     ,     __snake_case     :					Optional[int]=12     ,     __snake_case     :					int=12     ,     __snake_case     :					List[Any]=4.0     ,     __snake_case     :					Dict=True     ,     __snake_case     :					str=False     ,     __snake_case     :					List[str]=1E-5     ,     __snake_case     :					str=0.0     ,     __snake_case     :					Any=0.0     ,     __snake_case     :					List[str]=0.0     ,     __snake_case     :					Any=False     ,     __snake_case     :					List[str]=0.02     ,     **__snake_case     :					Dict     ,     )							-> Dict:
            super().__init__(**__snake_case    )

            _lowerCAmelCase					=				image_size
            _lowerCAmelCase					=				patch_size
            _lowerCAmelCase					=				num_channels
            _lowerCAmelCase					=				max_token_length
            _lowerCAmelCase					=				num_character_labels
            _lowerCAmelCase					=				num_bpe_labels
            _lowerCAmelCase					=				num_wordpiece_labels
            _lowerCAmelCase					=				hidden_size
            _lowerCAmelCase					=				num_hidden_layers
            _lowerCAmelCase					=				num_attention_heads
            _lowerCAmelCase					=				mlp_ratio
            _lowerCAmelCase					=				distilled
            _lowerCAmelCase					=				layer_norm_eps
            _lowerCAmelCase					=				drop_rate
            _lowerCAmelCase					=				qkv_bias
            _lowerCAmelCase					=				attn_drop_rate
            _lowerCAmelCase					=				drop_path_rate
            _lowerCAmelCase					=				output_aa_attentions
            _lowerCAmelCase					=				initializer_range













'''simple docstring'''






from __future__ import annotations

import numpy as np
def   UpperCamelCase__ (						lowerCAmelCase    ):





      """simple docstring"""


      _lowerCAmelCase	,				_lowerCAmelCase					=				np.shape(lowerCAmelCase    )
      if rows != columns:
            _lowerCAmelCase					=				(
                """'table' has to be of square shaped array but got a """
                f"{rows}x{columns} array:\n{table}"
            )
            raise ValueError(lowerCAmelCase    )

      _lowerCAmelCase					=				np.zeros((rows, columns)    )
      _lowerCAmelCase					=				np.zeros((rows, columns)    )
      for i in range(lowerCAmelCase    ):
            for j in range(lowerCAmelCase    ):
                  _lowerCAmelCase					=				sum(lower[i][k] * upper[k][j] for k in range(lowerCAmelCase    )    )
                  if upper[j][j] == 0:
                        raise ArithmeticError("""No LU decomposition exists"""    )
                  _lowerCAmelCase					=				(table[i][j] - total) / upper[j][j]
            _lowerCAmelCase					=				1
            for j in range(lowerCAmelCase				,      lowerCAmelCase    ):
                  _lowerCAmelCase					=				sum(lower[i][k] * upper[k][j] for k in range(lowerCAmelCase    )    )
                  _lowerCAmelCase					=				table[i][j] - total
      return lower, upper


if __name__ == "__main__":
      import doctest

      doctest.testmod()






