


'''simple docstring'''

import copy
import os

import cva
import numpy as np
from matplotlib import pyplot as plt
class   __lowerCAmelCase						:





      '''simple docstring'''






      def __init__(self    :    Union[str, Any] ):

             '''simple docstring'''







             lowercase__      			= ''''''
             lowercase__      			= ''''''
             lowercase__      			= []
             lowercase__      			= 0
             lowercase__      			= 256
             lowercase__      			= 0
             lowercase__      			= 0
             lowercase__      			= 0
             lowercase__      			= 0



      def       UpperCamelCase__		(self    :    Union[str, Any]   ,						UpperCamelCase    :    int ):

             '''simple docstring'''







             lowercase__      			= cva.imread(UpperCamelCase   ,						0 )
             lowercase__      			= copy.deepcopy(self.img )
             lowercase__			,lowercase__			,lowercase__      			= plt.hist(self.img.ravel()   ,						256   ,						[0, 256]   ,						label='''x''' )
             lowercase__      			= np.sum(UpperCamelCase )
             for i in range(len(UpperCamelCase ) ):
                    lowercase__      			= x[i] / self.k
                    self.sk += prk
                    lowercase__      			= (self.L - 1) * self.sk
                    if self.rem != 0:
                           lowercase__      			= int(last % last )
                    lowercase__      			= int(last + 1 if self.rem >= 0.5 else last )
                    self.last_list.append(UpperCamelCase )
                    lowercase__      			= int(np.ma.count(self.img ) / self.img[1].size )
                    lowercase__      			= self.img[1].size
             for i in range(self.number_of_cols ):
                    for j in range(self.number_of_rows ):
                           lowercase__      			= self.img[j][i]
                           if num != self.last_list[num]:
                                  lowercase__      			= self.last_list[num]
             cva.imwrite('''output_data/output.jpg'''   ,						self.img )



      def       UpperCamelCase__		(self    :    int ):

             '''simple docstring'''







             plt.hist(self.img.ravel()   ,						256   ,						[0, 256] )






      def       UpperCamelCase__		(self    :    Tuple ):

             '''simple docstring'''







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


if __name__ == "__main__":
 lowerCamelCase							:   Union[str, Any]  						=	os.path.join(os.path.basename(__file__), 'image_data/input.jpg')
 lowerCamelCase							:   int  						=	ConstantStretch()
 stretcher.stretch(file_path)
 stretcher.plot_histogram()
 stretcher.show_image()








'''simple docstring'''

import warnings

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


lowerCamelCase							:   str  						=	logging.get_logger(__name__)

lowerCamelCase							:   int  						=	{
    'RUCAIBox/mvp': 'https://huggingface.co/RUCAIBox/mvp/resolve/main/config.json',
}
class   __lowerCAmelCase						(lowercase_     ):





      '''simple docstring'''






      lowerCAmelCase__					:     Union[str, Any]  					=							"""mvp"""
      lowerCAmelCase__					:     Optional[Any]  					=							["""past_key_values"""]
      lowerCAmelCase__					:     List[str]  					=							{"""num_attention_heads""": """encoder_attention_heads""", """hidden_size""": """d_model"""}



      def __init__(self    :    Any   ,						UpperCamelCase    :    Optional[int]=50267   ,						UpperCamelCase    :    Tuple=1024   ,						UpperCamelCase    :    int=12   ,						UpperCamelCase    :    Tuple=4096   ,						UpperCamelCase    :    Dict=16   ,						UpperCamelCase    :    int=12   ,						UpperCamelCase    :    Optional[int]=4096   ,						UpperCamelCase    :    Optional[int]=16   ,						UpperCamelCase    :    Tuple=0.0   ,						UpperCamelCase    :    Tuple=0.0   ,						UpperCamelCase    :    List[Any]="gelu"   ,						UpperCamelCase    :    Union[str, Any]=1024   ,						UpperCamelCase    :    Optional[Any]=0.1   ,						UpperCamelCase    :    str=0.0   ,						UpperCamelCase    :    str=0.0   ,						UpperCamelCase    :    Optional[Any]=0.02   ,						UpperCamelCase    :    List[str]=0.0   ,						UpperCamelCase    :    List[str]=False   ,						UpperCamelCase    :    Optional[int]=True   ,						UpperCamelCase    :    Any=1   ,						UpperCamelCase    :    int=0   ,						UpperCamelCase    :    int=2   ,						UpperCamelCase    :    Any=True   ,						UpperCamelCase    :    Optional[Any]=2   ,						UpperCamelCase    :    Optional[Any]=2   ,						UpperCamelCase    :    Tuple=False   ,						UpperCamelCase    :    int=100   ,						UpperCamelCase    :    Optional[Any]=800   ,						**UpperCamelCase    :    str   ,						):

             '''simple docstring'''







             lowercase__      			= vocab_size
             lowercase__      			= max_position_embeddings
             lowercase__      			= d_model
             lowercase__      			= encoder_ffn_dim
             lowercase__      			= encoder_layers
             lowercase__      			= encoder_attention_heads
             lowercase__      			= decoder_ffn_dim
             lowercase__      			= decoder_layers
             lowercase__      			= decoder_attention_heads
             lowercase__      			= dropout
             lowercase__      			= attention_dropout
             lowercase__      			= activation_dropout
             lowercase__      			= activation_function
             lowercase__      			= init_std
             lowercase__      			= encoder_layerdrop
             lowercase__      			= decoder_layerdrop
             lowercase__      			= classifier_dropout
             lowercase__      			= use_cache
             lowercase__      			= encoder_layers
             lowercase__      			= scale_embedding  # scale factor will be sqrt(d_model) if True
             lowercase__      			= use_prompt
             lowercase__      			= prompt_length
             lowercase__      			= prompt_mid_dim

             super().__init__(
                 pad_token_id=UpperCamelCase   ,						bos_token_id=UpperCamelCase   ,						eos_token_id=UpperCamelCase   ,						is_encoder_decoder=UpperCamelCase   ,						decoder_start_token_id=UpperCamelCase   ,						forced_eos_token_id=UpperCamelCase   ,						**UpperCamelCase   ,						)

             if self.forced_bos_token_id is None and kwargs.get('''force_bos_token_to_be_generated'''   ,						UpperCamelCase ):
                    lowercase__      			= self.bos_token_id
                    warnings.warn(
                        f"Please make sure the config includes `forced_bos_token_id={self.bos_token_id}` in future versions. "
                        '''The config can simply be saved and uploaded again to be fixed.''' )




