


'''simple docstring'''

import json
from typing import TYPE_CHECKING, List, Optional, Tuple

from tokenizers import pre_tokenizers

from ...tokenization_utils_base import AddedToken, BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_deberta import DebertaTokenizer


if TYPE_CHECKING:
 from transformers.pipelines.conversational import Conversation


lowerCamelCase							:       List[Any]  						=     logging.get_logger(__name__)

lowerCamelCase							:       Dict  						=     {'vocab_file': 'vocab.json', 'merges_file': 'merges.txt', 'tokenizer_file': 'tokenizer.json'}

lowerCamelCase							:       Optional[Any]  						=     {
    'vocab_file': {
        'microsoft/deberta-base': 'https://huggingface.co/microsoft/deberta-base/resolve/main/vocab.json',
        'microsoft/deberta-large': 'https://huggingface.co/microsoft/deberta-large/resolve/main/vocab.json',
        'microsoft/deberta-xlarge': 'https://huggingface.co/microsoft/deberta-xlarge/resolve/main/vocab.json',
        'microsoft/deberta-base-mnli': 'https://huggingface.co/microsoft/deberta-base-mnli/resolve/main/vocab.json',
        'microsoft/deberta-large-mnli': 'https://huggingface.co/microsoft/deberta-large-mnli/resolve/main/vocab.json',
        'microsoft/deberta-xlarge-mnli': (
            'https://huggingface.co/microsoft/deberta-xlarge-mnli/resolve/main/vocab.json'
        ),
    },
    'merges_file': {
        'microsoft/deberta-base': 'https://huggingface.co/microsoft/deberta-base/resolve/main/merges.txt',
        'microsoft/deberta-large': 'https://huggingface.co/microsoft/deberta-large/resolve/main/merges.txt',
        'microsoft/deberta-xlarge': 'https://huggingface.co/microsoft/deberta-xlarge/resolve/main/merges.txt',
        'microsoft/deberta-base-mnli': 'https://huggingface.co/microsoft/deberta-base-mnli/resolve/main/merges.txt',
        'microsoft/deberta-large-mnli': 'https://huggingface.co/microsoft/deberta-large-mnli/resolve/main/merges.txt',
        'microsoft/deberta-xlarge-mnli': (
            'https://huggingface.co/microsoft/deberta-xlarge-mnli/resolve/main/merges.txt'
        ),
    },
}

lowerCamelCase							:       List[Any]  						=     {
    'microsoft/deberta-base': 512,
    'microsoft/deberta-large': 512,
    'microsoft/deberta-xlarge': 512,
    'microsoft/deberta-base-mnli': 512,
    'microsoft/deberta-large-mnli': 512,
    'microsoft/deberta-xlarge-mnli': 512,
}

lowerCamelCase							:       Optional[int]  						=     {
    'microsoft/deberta-base': {'do_lower_case': False},
    'microsoft/deberta-large': {'do_lower_case': False},
}
class   __lowerCAmelCase						(lowercase_					):





      '''simple docstring'''






      lowerCAmelCase__ :					str   =							VOCAB_FILES_NAMES
      lowerCAmelCase__ :					Union[str, Any]   =							PRETRAINED_VOCAB_FILES_MAP
      lowerCAmelCase__ :					Dict   =							PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
      lowerCAmelCase__ :					Any   =							["""input_ids""", """attention_mask""", """token_type_ids"""]
      lowerCAmelCase__ :					Dict   =							DebertaTokenizer



      def __init__(self   :   Optional[int]       ,						UpperCamelCase   :   Any=None       ,						UpperCamelCase   :   Tuple=None       ,						UpperCamelCase   :   List[Any]=None       ,						UpperCamelCase   :   Union[str, Any]="replace"       ,						UpperCamelCase   :   Optional[Any]="[CLS]"       ,						UpperCamelCase   :   List[str]="[SEP]"       ,						UpperCamelCase   :   Dict="[SEP]"       ,						UpperCamelCase   :   int="[CLS]"       ,						UpperCamelCase   :   Optional[int]="[UNK]"       ,						UpperCamelCase   :   Tuple="[PAD]"       ,						UpperCamelCase   :   List[Any]="[MASK]"       ,						UpperCamelCase   :   str=False       ,						**UpperCamelCase   :   Optional[int]       ,						):

             '''simple docstring'''







             super().__init__(
                 UpperCamelCase       ,						UpperCamelCase       ,						tokenizer_file=UpperCamelCase       ,						errors=UpperCamelCase       ,						bos_token=UpperCamelCase       ,						eos_token=UpperCamelCase       ,						unk_token=UpperCamelCase       ,						sep_token=UpperCamelCase       ,						cls_token=UpperCamelCase       ,						pad_token=UpperCamelCase       ,						mask_token=UpperCamelCase       ,						add_prefix_space=UpperCamelCase       ,						**UpperCamelCase       ,						)
             lowercase__				      =			kwargs.pop('''add_bos_token'''       ,						UpperCamelCase			)

             lowercase__				      =			json.loads(self.backend_tokenizer.pre_tokenizer.__getstate__()			)
             if pre_tok_state.get('''add_prefix_space'''       ,						UpperCamelCase			) != add_prefix_space:
                    lowercase__				      =			getattr(UpperCamelCase       ,						pre_tok_state.pop('''type'''			)			)
                    lowercase__				      =			add_prefix_space
                    lowercase__				      =			pre_tok_class(**UpperCamelCase			)

             lowercase__				      =			add_prefix_space



      @property
      def 				UpperCamelCase__		(self   :   Union[str, Any]			):

             '''simple docstring'''







             if self._mask_token is None:
                    if self.verbose:
                           logger.error('''Using mask_token, but it is not set yet.'''			)
                    return None
             return str(self._mask_token			)



      @mask_token.setter
      def 				UpperCamelCase__		(self   :   int       ,						UpperCamelCase   :   Union[str, Any]			):

             '''simple docstring'''







             lowercase__				      =			AddedToken(UpperCamelCase       ,						lstrip=UpperCamelCase       ,						rstrip=UpperCamelCase			) if isinstance(UpperCamelCase       ,						UpperCamelCase			) else value
             lowercase__				      =			value



      def 				UpperCamelCase__		(self   :   Optional[Any]       ,						UpperCamelCase   :   List[int]       ,						UpperCamelCase   :   Optional[List[int]] = None			):

             '''simple docstring'''







             if token_ids_a is None:
                    return [self.cls_token_id] + token_ids_a + [self.sep_token_id]
             lowercase__				      =			[self.cls_token_id]
             lowercase__				      =			[self.sep_token_id]
             return cls + token_ids_a + sep + token_ids_a + sep



      def 				UpperCamelCase__		(self   :   Tuple       ,						UpperCamelCase   :   List[int]       ,						UpperCamelCase   :   Optional[List[int]] = None			):

             '''simple docstring'''







             lowercase__				      =			[self.sep_token_id]
             lowercase__				      =			[self.cls_token_id]

             if token_ids_a is None:
                    return len(cls + token_ids_a + sep			) * [0]
             return len(cls + token_ids_a + sep			) * [0] + len(token_ids_a + sep			) * [1]



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

             '''simple docstring'''







             lowercase__				      =			kwargs.get('''is_split_into_words'''       ,						UpperCamelCase			)
             assert self.add_prefix_space or not is_split_into_words, (
                 f"You need to instantiate {self.__class__.__name__} with add_prefix_space=True "
                 "to use it with pretokenized inputs."
             )

             return super()._batch_encode_plus(*UpperCamelCase       ,						**UpperCamelCase			)



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

             '''simple docstring'''







             lowercase__				      =			kwargs.get('''is_split_into_words'''       ,						UpperCamelCase			)

             assert self.add_prefix_space or not is_split_into_words, (
                 f"You need to instantiate {self.__class__.__name__} with add_prefix_space=True "
                 "to use it with pretokenized inputs."
             )

             return super()._encode_plus(*UpperCamelCase       ,						**UpperCamelCase			)



      def 				UpperCamelCase__		(self   :   Union[str, Any]       ,						UpperCamelCase   :   str       ,						UpperCamelCase   :   Optional[str] = None			):

             '''simple docstring'''







             lowercase__				      =			self._tokenizer.model.save(UpperCamelCase       ,						name=UpperCamelCase			)
             return tuple(UpperCamelCase			)






      def 				UpperCamelCase__		(self   :   Optional[int]       ,						UpperCamelCase   :   "Conversation"			):

             '''simple docstring'''







             lowercase__				      =			[]
             for is_user, text in conversation.iter_texts():
                    input_ids.extend(self.encode(UpperCamelCase       ,						add_special_tokens=UpperCamelCase			) + [self.eos_token_id]			)

             if len(UpperCamelCase			) > self.model_max_length:
                    lowercase__				      =			input_ids[-self.model_max_length :]
             return input_ids








'''simple docstring'''

import math
import os

import cva
import numpy as np

lowerCamelCase							:       Optional[Any]  						=     2_5_5.0

def _SCREAMING_SNAKE_CASE				(A  ,			A	)	->	float:






       """simple docstring"""







       lowercase__				      =			np.mean((original - contrast) ** 2	)
       if mse == 0:
              return 100

       return 20 * math.logaa(PIXEL_MAX / math.sqrt(A	)	)

def _SCREAMING_SNAKE_CASE				()	->	None:






       """simple docstring"""







       lowercase__				      =			os.path.dirname(os.path.realpath(A	)	)
       # Loading images (original image and compressed image)
       lowercase__				      =			cva.imread(os.path.join(A  ,			'''image_data/original_image.png'''	)	)
       lowercase__				      =			cva.imread(os.path.join(A  ,			'''image_data/compressed_image.png'''	)  ,			1	)

       lowercase__				      =			cva.imread(os.path.join(A  ,			'''image_data/PSNR-example-base.png'''	)	)
       lowercase__				      =			cva.imread(
           os.path.join(A  ,			'''image_data/PSNR-example-comp-10.jpg'''	)  ,			1	)

       # Value expected: 29.73dB
       print('''-- First Test --'''	)
       print(f"PSNR value is {peak_signal_to_noise_ratio(A  ,			A	)} dB"	)

       # # Value expected: 31.53dB (Wikipedia Example)
       print('''\n-- Second Test --'''	)
       print(f"PSNR value is {peak_signal_to_noise_ratio(A  ,			A	)} dB"	)


if __name__ == "__main__":
 main()




