


import copy
import os
from typing import Union

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


__a	 =      logging.get_logger(__name__)

__a	 =      {
    """google/pix2struct-textcaps-base""": (
        """https://huggingface.co/google/pix2struct-textcaps-base/resolve/main/config.json"""
    ),
}






class 	__lowercase					(	__snake_case	):
      UpperCamelCase										=							'''pix2struct_text_model'''
      UpperCamelCase										=							['''past_key_values''']
      UpperCamelCase										=							{
          '''hidden_size''': '''hidden_size''',
          '''num_attention_heads''': '''num_heads''',
          '''num_hidden_layers''': '''num_layers''',
      }





      def __init__(		self    :       Optional[Any]       ,							__lowerCamelCase    :       Optional[int]=5_0_2_4_4       ,							__lowerCamelCase    :       int=7_6_8       ,							__lowerCamelCase    :       Union[str, Any]=6_4       ,							__lowerCamelCase    :       Dict=2_0_4_8       ,							__lowerCamelCase    :       int=1_2       ,							__lowerCamelCase    :       Any=1_2       ,							__lowerCamelCase    :       Union[str, Any]=3_2       ,							__lowerCamelCase    :       Any=1_2_8       ,							__lowerCamelCase    :       Union[str, Any]=0.1       ,							__lowerCamelCase    :       str=1e-6       ,							__lowerCamelCase    :       int=1.0       ,							__lowerCamelCase    :       Optional[int]="gelu_new"       ,							__lowerCamelCase    :       int=0       ,							__lowerCamelCase    :       int=False       ,							__lowerCamelCase    :       Optional[Any]=0       ,							__lowerCamelCase    :       Dict=1       ,							__lowerCamelCase    :       List[Any]=False       ,							__lowerCamelCase    :       Optional[Any]=True       ,							**__lowerCamelCase    :       Dict       ,							)     -> int:






         """simple docstring"""







         UpperCAmelCase      					=  vocab_size
         UpperCAmelCase      					=  hidden_size
         UpperCAmelCase      					=  d_kv
         UpperCAmelCase      					=  d_ff
         UpperCAmelCase      					=  num_layers
         UpperCAmelCase      					=  num_heads
         UpperCAmelCase      					=  relative_attention_num_buckets
         UpperCAmelCase      					=  relative_attention_max_distance
         UpperCAmelCase      					=  dropout_rate
         UpperCAmelCase      					=  layer_norm_epsilon
         UpperCAmelCase      					=  initializer_factor
         UpperCAmelCase      					=  use_cache

         UpperCAmelCase      					=  eos_token_id
         UpperCAmelCase      					=  decoder_start_token_id

         # for backwards compatibility
         UpperCAmelCase      					=  dense_act_fn

         super().__init__(
             pad_token_id=__lowerCamelCase       ,							eos_token_id=__lowerCamelCase       ,							decoder_start_token_id=__lowerCamelCase       ,							tie_word_embeddings=__lowerCamelCase       ,							is_decoder=__lowerCamelCase       ,							**__lowerCamelCase       ,							)





      @classmethod
      def 							_lowercase					(		cls    :       List[Any]       ,							__lowerCamelCase    :       Union[str, os.PathLike]       ,							**__lowerCamelCase    :       Any							)     -> "PretrainedConfig":






         """simple docstring"""







         cls._set_token_in_kwargs(__lowerCamelCase							)

         UpperCAmelCase					,	UpperCAmelCase      					=  cls.get_config_dict(__lowerCamelCase       ,							**__lowerCamelCase							)

         # get the text config dict if we are loading from Pix2StructConfig
         if config_dict.get("""model_type"""							) == "pix2struct":
            UpperCAmelCase      					=  config_dict["""text_config"""]

         if "model_type" in config_dict and hasattr(cls       ,							"""model_type"""							) and config_dict["model_type"] != cls.model_type:
            logger.warning(
                F"""You are using a model of type {config_dict['model_type']} to instantiate a model of type """
                F"""{cls.model_type}. This is not supported for all configurations of models and can yield errors."""							)

         return cls.from_dict(__lowerCamelCase       ,							**__lowerCamelCase							)






class 	__lowercase					(	__snake_case	):
      UpperCamelCase										=							'''pix2struct_vision_model'''





      def __init__(		self    :       str       ,							__lowerCamelCase    :       Any=7_6_8       ,							__lowerCamelCase    :       Dict=7_6_8       ,							__lowerCamelCase    :       List[Any]=2_0_4_8       ,							__lowerCamelCase    :       List[Any]=6_4       ,							__lowerCamelCase    :       Union[str, Any]=1_2       ,							__lowerCamelCase    :       Optional[int]=1_2       ,							__lowerCamelCase    :       Tuple="gelu_new"       ,							__lowerCamelCase    :       Tuple=1e-6       ,							__lowerCamelCase    :       Any=0.0       ,							__lowerCamelCase    :       List[Any]=0.0       ,							__lowerCamelCase    :       int=1e-1_0       ,							__lowerCamelCase    :       Union[str, Any]=1.0       ,							__lowerCamelCase    :       Any=4_0_9_6       ,							__lowerCamelCase    :       Dict=3_2       ,							__lowerCamelCase    :       Any=1_2_8       ,							**__lowerCamelCase    :       Optional[int]       ,							)     -> Optional[Any]:






         """simple docstring"""







         super().__init__(**__lowerCamelCase							)

         UpperCAmelCase      					=  hidden_size
         UpperCAmelCase      					=  patch_embed_hidden_size
         UpperCAmelCase      					=  d_ff
         UpperCAmelCase      					=  dropout_rate
         UpperCAmelCase      					=  num_hidden_layers
         UpperCAmelCase      					=  num_attention_heads
         UpperCAmelCase      					=  initializer_range
         UpperCAmelCase      					=  initializer_factor
         UpperCAmelCase      					=  attention_dropout
         UpperCAmelCase      					=  layer_norm_eps
         UpperCAmelCase      					=  dense_act_fn
         UpperCAmelCase      					=  seq_len
         UpperCAmelCase      					=  relative_attention_num_buckets
         UpperCAmelCase      					=  relative_attention_max_distance
         UpperCAmelCase      					=  d_kv





      @classmethod
      def 							_lowercase					(		cls    :       Any       ,							__lowerCamelCase    :       Union[str, os.PathLike]       ,							**__lowerCamelCase    :       int							)     -> "PretrainedConfig":






         """simple docstring"""







         cls._set_token_in_kwargs(__lowerCamelCase							)

         UpperCAmelCase					,	UpperCAmelCase      					=  cls.get_config_dict(__lowerCamelCase       ,							**__lowerCamelCase							)

         # get the vision config dict if we are loading from Pix2StructConfig
         if config_dict.get("""model_type"""							) == "pix2struct":
            UpperCAmelCase      					=  config_dict["""vision_config"""]

         if "model_type" in config_dict and hasattr(cls       ,							"""model_type"""							) and config_dict["model_type"] != cls.model_type:
            logger.warning(
                F"""You are using a model of type {config_dict['model_type']} to instantiate a model of type """
                F"""{cls.model_type}. This is not supported for all configurations of models and can yield errors."""							)

         return cls.from_dict(__lowerCamelCase       ,							**__lowerCamelCase							)






class 	__lowercase					(	__snake_case	):
      UpperCamelCase										=							'''pix2struct'''
      UpperCamelCase										=							True





      def __init__(		self    :       str       ,							__lowerCamelCase    :       str=None       ,							__lowerCamelCase    :       Dict=None       ,							__lowerCamelCase    :       Optional[Any]=1.0       ,							__lowerCamelCase    :       str=0.02       ,							__lowerCamelCase    :       Any=False       ,							__lowerCamelCase    :       Tuple=False       ,							__lowerCamelCase    :       str=True       ,							**__lowerCamelCase    :       Dict       ,							)     -> Optional[Any]:






         """simple docstring"""







         super().__init__(tie_word_embeddings=__lowerCamelCase       ,							is_encoder_decoder=__lowerCamelCase       ,							**__lowerCamelCase							)

         if text_config is None:
            UpperCAmelCase      					=  {}
            logger.info("""text_config is None. Initializing the Pix2StructTextConfig with default values."""							)

         if vision_config is None:
            UpperCAmelCase      					=  {}
            logger.info("""vision_config is None. Initializing the Pix2StructVisionConfig with default values."""							)

         UpperCAmelCase      					=  PixaStructTextConfig(**__lowerCamelCase							)
         UpperCAmelCase      					=  PixaStructVisionConfig(**__lowerCamelCase							)

         UpperCAmelCase      					=  self.text_config.decoder_start_token_id
         UpperCAmelCase      					=  self.text_config.pad_token_id
         UpperCAmelCase      					=  self.text_config.eos_token_id

         UpperCAmelCase      					=  initializer_factor
         UpperCAmelCase      					=  initializer_range

         UpperCAmelCase      					=  self.initializer_range
         UpperCAmelCase      					=  self.initializer_range

         UpperCAmelCase      					=  is_vqa





      @classmethod
      def 							_lowercase					(		cls    :       List[Any]       ,							__lowerCamelCase    :       PixaStructTextConfig       ,							__lowerCamelCase    :       PixaStructVisionConfig       ,							**__lowerCamelCase    :       Dict							)     -> Union[str, Any]:






         """simple docstring"""







         return cls(text_config=text_config.to_dict()       ,							vision_config=vision_config.to_dict()       ,							**__lowerCamelCase							)





      def 							_lowercase					(		self    :       List[str]							)     -> Optional[int]:






         """simple docstring"""







         UpperCAmelCase      					=  copy.deepcopy(self.__dict__							)
         UpperCAmelCase      					=  self.text_config.to_dict()
         UpperCAmelCase      					=  self.vision_config.to_dict()
         UpperCAmelCase      					=  self.__class__.model_type
         return output







def 	_UpperCamelCase					(    )    ->list[list[int]]:
   return [list(range(1_0_0_0 - i	,    -1_0_0_0 - i	,    -1 ) ) for i in range(1_0_0_0 )]


__a	 =      generate_large_matrix()
__a	 =      (
    [[4, 3, 2, -1], [3, 2, 1, -1], [1, 1, -1, -2], [-1, -1, -2, -3]],
    [[3, 2], [1, 0]],
    [[7, 7, 6]],
    [[7, 7, 6], [-1, -2, -3]],
    grid,
)
def 	_UpperCamelCase					(    lowerCAmelCase_ )    ->None:
   assert all(row == sorted(lowerCAmelCase_	,    reverse=lowerCAmelCase_ ) for row in grid )
   assert all(list(lowerCAmelCase_ ) == sorted(lowerCAmelCase_	,    reverse=lowerCAmelCase_ ) for col in zip(*lowerCAmelCase_ ) )
def 	_UpperCamelCase					(    lowerCAmelCase_ )    ->int:
   UpperCAmelCase      					=  0
   UpperCAmelCase      					=  len(lowerCAmelCase_ ) - 1

   # Edge cases such as no values or all numbers are negative.
   if not array or array[0] < 0:
      return 0

   while right + 1 > left:
      UpperCAmelCase      					=  (left + right) // 2
      UpperCAmelCase      					=  array[mid]

      # Num must be negative and the index must be greater than or equal to 0.
      if num < 0 and array[mid - 1] >= 0:
         return mid

      if num >= 0:
         UpperCAmelCase      					=  mid + 1
      else:
         UpperCAmelCase      					=  mid - 1
    # No negative numbers so return the last index of the array + 1 which is the length.
   return len(lowerCAmelCase_ )
def 	_UpperCamelCase					(    lowerCAmelCase_ )    ->int:
   UpperCAmelCase      					=  0
   UpperCAmelCase      					=  len(grid[0] )

   for i in range(len(lowerCAmelCase_ ) ):
      UpperCAmelCase      					=  find_negative_index(grid[i][:bound] )
      total += bound
   return (len(lowerCAmelCase_ ) * len(grid[0] )) - total
def 	_UpperCamelCase					(    lowerCAmelCase_ )    ->int:
   return len([number for row in grid for number in row if number < 0] )
def 	_UpperCamelCase					(    lowerCAmelCase_ )    ->int:
   UpperCAmelCase      					=  0
   for row in grid:
      for i, number in enumerate(lowerCAmelCase_ ):
         if number < 0:
            total += len(lowerCAmelCase_ ) - i
            break
   return total
def 	_UpperCamelCase					(    )    ->None:
   from timeit import timeit

   print("""Running benchmarks""" )
   UpperCAmelCase      					=  (
       """from __main__ import count_negatives_binary_search, """
       """count_negatives_brute_force, count_negatives_brute_force_with_break, grid"""
   )
   for func in (
       "count_negatives_binary_search",  # took 0.7727 seconds
       "count_negatives_brute_force_with_break",  # took 4.6505 seconds
       "count_negatives_brute_force",  # took 12.8160 seconds
   ):
      UpperCAmelCase      					=  timeit(F"""{func}(grid=grid)"""	,    setup=lowerCAmelCase_	,    number=5_0_0 )
      print(F"""{func}() took {time:0.4f} seconds""" )


if __name__ == "__main__":
 import doctest

 doctest.testmod()
 benchmark()



