

import copy
import os

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






class 	UpperCAmelCase__		:






  """simple docstring"""


  def __init__(							self						:		Optional[int] )		->							Union[str, Any]:
       SCREAMING_SNAKE_CASE__   =   ''
       SCREAMING_SNAKE_CASE__   =   ''
       SCREAMING_SNAKE_CASE__   =   []
       SCREAMING_SNAKE_CASE__   =   0
       SCREAMING_SNAKE_CASE__   =   256
       SCREAMING_SNAKE_CASE__   =   0
       SCREAMING_SNAKE_CASE__   =   0
       SCREAMING_SNAKE_CASE__   =   0
       SCREAMING_SNAKE_CASE__   =   0






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






  def 				lowercase_		(							self						:		List[Any] )		->							Tuple:
       plt.hist(self.img.ravel()     ,       256     ,       [0, 256] )







  def 				lowercase_		(							self						:		List[str] )		->							List[str]:
       cva.imshow('''Output-Image'''     ,       self.img )
       cva.imshow('''Input-Image'''     ,       self.original_image )
       cva.waitKey(5000 )
       cva.destroyAllWindows()


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





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


_SCREAMING_SNAKE_CASE					:  Any             =      logging.get_logger(__name__)

_SCREAMING_SNAKE_CASE					:  int             =      {
    '''edbeeching/decision-transformer-gym-hopper-medium''': (
        '''https://huggingface.co/edbeeching/decision-transformer-gym-hopper-medium/resolve/main/config.json'''
    ),
    # See all DecisionTransformer models at https://huggingface.co/models?filter=decision_transformer
}






class 	UpperCAmelCase__		(	A__	):






  """simple docstring"""


  a									= "decision_transformer"
  a									= ["past_key_values"]
  a									= {
      "max_position_embeddings": "n_positions",
      "num_attention_heads": "n_head",
      "num_hidden_layers": "n_layer",
  }






  def __init__(							self						:		Tuple     ,       __lowerCamelCase						:		Any=17     ,       __lowerCamelCase						:		Any=4     ,       __lowerCamelCase						:		List[Any]=128     ,       __lowerCamelCase						:		Union[str, Any]=4096     ,       __lowerCamelCase						:		Optional[Any]=True     ,       __lowerCamelCase						:		Any=1     ,       __lowerCamelCase						:		List[Any]=1024     ,       __lowerCamelCase						:		Any=3     ,       __lowerCamelCase						:		Dict=1     ,       __lowerCamelCase						:		List[Any]=None     ,       __lowerCamelCase						:		str="relu"     ,       __lowerCamelCase						:		Dict=0.1     ,       __lowerCamelCase						:		int=0.1     ,       __lowerCamelCase						:		List[str]=0.1     ,       __lowerCamelCase						:		str=1e-5     ,       __lowerCamelCase						:		Optional[Any]=0.02     ,       __lowerCamelCase						:		int=True     ,       __lowerCamelCase						:		Tuple=True     ,       __lowerCamelCase						:		Optional[int]=5_0256     ,       __lowerCamelCase						:		Tuple=5_0256     ,       __lowerCamelCase						:		int=False     ,       __lowerCamelCase						:		Optional[int]=False     ,       **__lowerCamelCase						:		Tuple     ,       )		->							Optional[Any]:
       SCREAMING_SNAKE_CASE__   =   state_dim
       SCREAMING_SNAKE_CASE__   =   act_dim
       SCREAMING_SNAKE_CASE__   =   hidden_size
       SCREAMING_SNAKE_CASE__   =   max_ep_len
       SCREAMING_SNAKE_CASE__   =   action_tanh
       SCREAMING_SNAKE_CASE__   =   vocab_size
       SCREAMING_SNAKE_CASE__   =   n_positions
       SCREAMING_SNAKE_CASE__   =   n_layer
       SCREAMING_SNAKE_CASE__   =   n_head
       SCREAMING_SNAKE_CASE__   =   n_inner
       SCREAMING_SNAKE_CASE__   =   activation_function
       SCREAMING_SNAKE_CASE__   =   resid_pdrop
       SCREAMING_SNAKE_CASE__   =   embd_pdrop
       SCREAMING_SNAKE_CASE__   =   attn_pdrop
       SCREAMING_SNAKE_CASE__   =   layer_norm_epsilon
       SCREAMING_SNAKE_CASE__   =   initializer_range
       SCREAMING_SNAKE_CASE__   =   scale_attn_weights
       SCREAMING_SNAKE_CASE__   =   use_cache
       SCREAMING_SNAKE_CASE__   =   scale_attn_by_inverse_layer_idx
       SCREAMING_SNAKE_CASE__   =   reorder_and_upcast_attn

       SCREAMING_SNAKE_CASE__   =   bos_token_id
       SCREAMING_SNAKE_CASE__   =   eos_token_id

       super().__init__(bos_token_id=__lowerCamelCase     ,       eos_token_id=__lowerCamelCase     ,       **__lowerCamelCase )


