

import copy
import os
from typing import Union

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


A_		:      Tuple					    = logging.get_logger(__name__)

A_		:      str					    = {
    'microsoft/git-base': 'https://huggingface.co/microsoft/git-base/resolve/main/config.json',
}
class        A_ (   __snake_case    ):


    '''simple docstring'''






    a__  				=							"git_vision_model"


    def __init__(self  ,   lowercase__=768  ,   lowercase__=3_072  ,   lowercase__=12  ,   lowercase__=12  ,   lowercase__=3  ,   lowercase__=224  ,   lowercase__=16  ,   lowercase__="quick_gelu"  ,   lowercase__=1E-5  ,   lowercase__=0.0  ,   lowercase__=0.02  ,   **lowercase__  ,   )  ->   Union[str, Any]:
        super().__init__(**__lowerCamelCase	)

        __UpperCAmelCase					       =      hidden_size
        __UpperCAmelCase					       =      intermediate_size
        __UpperCAmelCase					       =      num_hidden_layers
        __UpperCAmelCase					       =      num_attention_heads
        __UpperCAmelCase					       =      num_channels
        __UpperCAmelCase					       =      patch_size
        __UpperCAmelCase					       =      image_size
        __UpperCAmelCase					       =      initializer_range
        __UpperCAmelCase					       =      attention_dropout
        __UpperCAmelCase					       =      layer_norm_eps
        __UpperCAmelCase					       =      hidden_act






    @classmethod
    def   lowerCAmelCase_    (cls  ,   lowercase__  ,   **lowercase__	)  ->   "PretrainedConfig":
        cls._set_token_in_kwargs(__lowerCamelCase	)

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

        # get the vision config dict if we are loading from GITConfig
        if config_dict.get('''model_type'''	) == "git":
            __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        A_ (   __snake_case    ):


    '''simple docstring'''






    a__  				=							"git"


    def __init__(self  ,   lowercase__=None  ,   lowercase__=30_522  ,   lowercase__=768  ,   lowercase__=6  ,   lowercase__=12  ,   lowercase__=3_072  ,   lowercase__="gelu"  ,   lowercase__=0.1  ,   lowercase__=0.1  ,   lowercase__=1_024  ,   lowercase__=0.02  ,   lowercase__=1E-12  ,   lowercase__=0  ,   lowercase__="absolute"  ,   lowercase__=True  ,   lowercase__=False  ,   lowercase__=101  ,   lowercase__=102  ,   lowercase__=None  ,   **lowercase__  ,   )  ->   Optional[int]:
        super().__init__(bos_token_id=__lowerCamelCase  ,   eos_token_id=__lowerCamelCase  ,   pad_token_id=__lowerCamelCase  ,   **__lowerCamelCase	)

        if vision_config is None:
            __UpperCAmelCase					       =      {}
            logger.info('''vision_config is None. initializing the GitVisionConfig with default values.'''	)

        __UpperCAmelCase					       =      GitVisionConfig(**__lowerCamelCase	)
        __UpperCAmelCase					       =      vocab_size
        __UpperCAmelCase					       =      hidden_size
        __UpperCAmelCase					       =      num_hidden_layers
        __UpperCAmelCase					       =      num_attention_heads
        __UpperCAmelCase					       =      hidden_act
        __UpperCAmelCase					       =      intermediate_size
        __UpperCAmelCase					       =      hidden_dropout_prob
        __UpperCAmelCase					       =      attention_probs_dropout_prob
        __UpperCAmelCase					       =      max_position_embeddings
        __UpperCAmelCase					       =      initializer_range
        __UpperCAmelCase					       =      layer_norm_eps
        __UpperCAmelCase					       =      position_embedding_type
        __UpperCAmelCase					       =      use_cache
        __UpperCAmelCase					       =      tie_word_embeddings
        __UpperCAmelCase					       =      num_image_with_embedding

        __UpperCAmelCase					       =      bos_token_id
        __UpperCAmelCase					       =      eos_token_id






    def   lowerCAmelCase_    (self	)  ->   Dict:
        __UpperCAmelCase					       =      copy.deepcopy(self.__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()



