
import copy
import os

import cva
import numpy as np
from matplotlib import pyplot as plt






class   UpperCAmelCase		:



   def __init__(self		:					List[str] )		->	Any:


          '''simple docstring'''


          snake_case       :   Tuple							=      ""
          snake_case       :   str							=      ""
          snake_case       :   Dict							=      []
          snake_case       :   str							=      0
          snake_case       :   Tuple							=      2_56
          snake_case       :   Optional[Any]							=      0
          snake_case       :   Union[str, Any]							=      0
          snake_case       :   Any							=      0
          snake_case       :   Union[str, Any]							=      0



   def 				_SCREAMING_SNAKE_CASE   (self		:					List[Any]    ,						snake_case__		:					Tuple )		->	List[Any]:


          '''simple docstring'''


          snake_case       :   Optional[Any]							=      cva.imread(snake_case__    ,						0 )
          snake_case       :   Union[str, Any]							=      copy.deepcopy(self.img )
          snake_case				,					snake_case				,					snake_case       :   Tuple							=      plt.hist(self.img.ravel()    ,						2_56    ,						[0, 2_56]    ,						label="x" )
          snake_case       :   Any							=      np.sum(snake_case__ )
          for i in range(len(snake_case__ ) ):
                 snake_case       :   Union[str, Any]							=      x[i] / self.k
                 self.sk += prk
                 snake_case       :   Optional[Any]							=      (self.L - 1) * self.sk
                 if self.rem != 0:
                        snake_case       :   List[str]							=      int(last % last )
                 snake_case       :   List[str]							=      int(last + 1 if self.rem >= 0.5 else last )
                 self.last_list.append(snake_case__ )
                 snake_case       :   int							=      int(np.ma.count(self.img ) / self.img[1].size )
                 snake_case       :   Optional[int]							=      self.img[1].size
          for i in range(self.number_of_cols ):
                 for j in range(self.number_of_rows ):
                        snake_case       :   Union[str, Any]							=      self.img[j][i]
                        if num != self.last_list[num]:
                               snake_case       :   Dict							=      self.last_list[num]
          cva.imwrite("output_data/output.jpg"    ,						self.img )



   def 				_SCREAMING_SNAKE_CASE   (self		:					List[Any] )		->	List[Any]:


          '''simple docstring'''


          plt.hist(self.img.ravel()    ,						2_56    ,						[0, 2_56] )



   def 				_SCREAMING_SNAKE_CASE   (self		:					str )		->	int:


          '''simple docstring'''


          cva.imshow("Output-Image"    ,						self.img )
          cva.imshow("Input-Image"    ,						self.original_image )
          cva.waitKey(50_00 )
          cva.destroyAllWindows()


if __name__ == "__main__":
   __lowerCamelCase							=       os.path.join(os.path.basename(__file__), """image_data/input.jpg""")
   __lowerCamelCase							=       ConstantStretch()
   stretcher.stretch(file_path)
   stretcher.plot_histogram()
   stretcher.show_image()







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


__lowerCamelCase							=       logging.get_logger(__name__)

__lowerCamelCase							=       {
    # See all MEGATRON_BERT models at https://huggingface.co/models?filter=bert
}






class   UpperCAmelCase		(						A_ ):
   A__					:		List[str]						     =     "megatron-bert"



   def __init__(self		:					Optional[int]    ,						snake_case__		:					List[str]=2_90_56    ,						snake_case__		:					List[Any]=10_24    ,						snake_case__		:					str=24    ,						snake_case__		:					Tuple=16    ,						snake_case__		:					Union[str, Any]=40_96    ,						snake_case__		:					str="gelu"    ,						snake_case__		:					str=0.1    ,						snake_case__		:					Optional[int]=0.1    ,						snake_case__		:					Tuple=5_12    ,						snake_case__		:					Union[str, Any]=2    ,						snake_case__		:					Dict=0.02    ,						snake_case__		:					List[Any]=1e-12    ,						snake_case__		:					int=0    ,						snake_case__		:					Tuple="absolute"    ,						snake_case__		:					Any=True    ,						**snake_case__		:					Union[str, Any]    ,						)		->	Optional[Any]:


          '''simple docstring'''


          super().__init__(pad_token_id=snake_case__    ,						**snake_case__ )

          snake_case       :   Tuple							=      vocab_size
          snake_case       :   str							=      hidden_size
          snake_case       :   str							=      num_hidden_layers
          snake_case       :   str							=      num_attention_heads
          snake_case       :   Optional[int]							=      hidden_act
          snake_case       :   int							=      intermediate_size
          snake_case       :   List[str]							=      hidden_dropout_prob
          snake_case       :   Union[str, Any]							=      attention_probs_dropout_prob
          snake_case       :   Dict							=      max_position_embeddings
          snake_case       :   List[str]							=      type_vocab_size
          snake_case       :   List[str]							=      initializer_range
          snake_case       :   Tuple							=      layer_norm_eps
          snake_case       :   int							=      position_embedding_type
          snake_case       :   str							=      use_cache





