



'''simple docstring'''






from __future__ import annotations

from typing import Dict

from ...configuration_utils import PretrainedConfig


A_							: int						 =	{
    '''susnato/ernie-m-base_pytorch''': '''https://huggingface.co/susnato/ernie-m-base_pytorch/blob/main/config.json''',
    '''susnato/ernie-m-large_pytorch''': '''https://huggingface.co/susnato/ernie-m-large_pytorch/blob/main/config.json''',
}



class 							lowercase       (  lowerCAmelCase__				):


 """simple docstring"""


 UpperCAmelCase							=  """ernie_m"""
 UpperCAmelCase							=  {"dropout": "classifier_dropout", "num_classes": "num_labels"}







 def __init__(							self  ,a_ = 250_002  ,a_ = 768  ,a_ = 12  ,a_ = 12  ,a_ = 3_072  ,a_ = "gelu"  ,a_ = 0.1  ,a_ = 0.1  ,a_ = 514  ,a_ = 0.02  ,a_ = 1  ,a_ = 1E-0_5  ,a_=None  ,a_=False  ,a_=0.0  ,**a_  ,)		->   Any:
        super().__init__(pad_token_id=lowercase_  ,**lowercase_							)
        _UpperCAmelCase  :						str			     = vocab_size
        _UpperCAmelCase  :						Tuple			     = hidden_size
        _UpperCAmelCase  :						Any			     = num_hidden_layers
        _UpperCAmelCase  :						List[Any]			     = num_attention_heads
        _UpperCAmelCase  :						List[str]			     = intermediate_size
        _UpperCAmelCase  :						int			     = hidden_act
        _UpperCAmelCase  :						str			     = hidden_dropout_prob
        _UpperCAmelCase  :						Tuple			     = attention_probs_dropout_prob
        _UpperCAmelCase  :						List[str]			     = max_position_embeddings
        _UpperCAmelCase  :						Union[str, Any]			     = initializer_range
        _UpperCAmelCase  :						Any			     = layer_norm_eps
        _UpperCAmelCase  :						int			     = classifier_dropout
        _UpperCAmelCase  :						List[str]			     = is_decoder
        _UpperCAmelCase  :						Dict			     = act_dropout








"""simple docstring"""

import copy
import os

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




class        _UpperCAmelCase       :

 def __init__(     self		:       List[Any]				):
     snake_case_ :     List[str]				=	''''''
     snake_case_ :     Tuple				=	''''''
     snake_case_ :     int				=	[]
     snake_case_ :     Optional[int]				=	0
     snake_case_ :     Optional[Any]				=	256
     snake_case_ :     Tuple				=	0
     snake_case_ :     Tuple				=	0
     snake_case_ :     Optional[Any]				=	0
     snake_case_ :     Any				=	0

 def 						_snake_case					(     self		:       Optional[Any]  ,     lowercase_		:       List[Any]				):
     snake_case_ :     List[Any]				=	cva.imread(lowercase_  ,     0				)
     snake_case_ :     Tuple				=	copy.deepcopy(self.img				)
     snake_case_,	snake_case_,	snake_case_ :     List[Any]				=	plt.hist(self.img.ravel()  ,     256  ,     [0, 256]  ,     label='''x'''				)
     snake_case_ :     str				=	np.sum(lowercase_				)
     for i in range(len(lowercase_				)				):
         snake_case_ :     Optional[Any]				=	x[i] / self.k
         self.sk += prk
         snake_case_ :     Any				=	(self.L - 1) * self.sk
         if self.rem != 0:
             snake_case_ :     Dict				=	int(last % last				)
         snake_case_ :     Union[str, Any]				=	int(last + 1 if self.rem >= 0.5 else last				)
         self.last_list.append(lowercase_				)
         snake_case_ :     int				=	int(np.ma.count(self.img				) / self.img[1].size				)
         snake_case_ :     Tuple				=	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_ :     List[str]				=	self.last_list[num]
     cva.imwrite('''output_data/output.jpg'''  ,     self.img				)

 def 						_snake_case					(     self		:       Tuple				):
     plt.hist(self.img.ravel()  ,     256  ,     [0, 256]				)






 def 						_snake_case					(     self		:       int				):
     cva.imshow('''Output-Image'''  ,     self.img				)
     cva.imshow('''Input-Image'''  ,     self.original_image				)
     cva.waitKey(5000				)
     cva.destroyAllWindows()


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





