




import json
import os
from typing import Dict, List, Optional, Tuple

from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging


lowerCamelCase       :	Optional[int]									=     logging.get_logger(__name__)


lowerCamelCase       :	Optional[int]									=     {
    "vocab_file": "vocab.json",
    "tokenizer_config_file": "tokenizer_config.json",
    "merges_file": "merges.txt",
}

lowerCamelCase       :	str									=     {
    "vocab_file": {
        "facebook/s2t-wav2vec2-large-en-de": (
            "https://huggingface.co/facebook/s2t-wav2vec2-large-en-de/resolve/main/vocab.json"
        ),
    },
    "tokenizer_config_file": {
        "facebook/s2t-wav2vec2-large-en-de": (
            "https://huggingface.co/facebook/s2t-wav2vec2-large-en-de/resolve/main/tokenizer_config.json"
        ),
    },
    "merges_file": {
        "facebook/s2t-wav2vec2-large-en-de": (
            "https://huggingface.co/facebook/s2t-wav2vec2-large-en-de/resolve/main/merges.txt"
        ),
    },
}

lowerCamelCase       :	List[Any]									=     "</w>"
lowerCamelCase       :	Union[str, Any]									=     "@@ "

def     _SCREAMING_SNAKE_CASE    (							lowercase			: Union[str, Any]  ):


      '''simple docstring'''



      lowerCamelCase_	  =					set()
      lowerCamelCase_	  =					word[0]
      for char in word[1:]:
            pairs.add((prev_char, char)  )
            lowerCamelCase_	  =					char
      return pairs


# Speech2Text2 has no max input length
lowerCamelCase       :	Tuple									=     {"facebook/s2t-wav2vec2-large-en-de": 1_024}







class 						A(		UpperCamelCase     ):



 '''simple docstring'''


 UpperCamelCase		     =		VOCAB_FILES_NAMES
 UpperCamelCase		     =		PRETRAINED_VOCAB_FILES_MAP
 UpperCamelCase		     =		PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
 UpperCamelCase		     =		['''input_ids''', '''attention_mask''']

 def __init__(       self      :						List[Any]		,							A_      :						Union[str, Any]		,							A_      :						List[Any]="<s>"		,							A_      :						Union[str, Any]="<pad>"		,							A_      :						str="</s>"		,							A_      :						Optional[int]="<unk>"		,							A_      :						Optional[int]=False		,							A_      :						Any=None		,							**A_      :						Tuple		,							)     ->			int:

       """simple docstring"""






       super().__init__(
           unk_token=A_		,							bos_token=A_		,							eos_token=A_		,							pad_token=A_		,							do_lower_case=A_		,							**A_		,							)

       lowerCamelCase_	  =					do_lower_case

       with open(A_		,							encoding='utf-8'						) as vocab_handle:
             lowerCamelCase_	  =					json.load(A_						)
       lowerCamelCase_	  =					{v: k for k, v in self.encoder.items()}

       if merges_file is None:
             logger.info(f"""No merges files provided. {self.__class__.__name__} can only be used for decoding."""						)

             lowerCamelCase_	  =					None
             lowerCamelCase_	  =					None
       else:
             with open(A_		,							encoding='utf-8'						) as merges_handle:
                   lowerCamelCase_	  =					merges_handle.read().split('\n'						)[:-1]

             lowerCamelCase_	  =					[tuple(merge.split()[:2]						) for merge in merges]
             lowerCamelCase_	  =					dict(zip(A_		,							range(len(A_						)						)						)						)
             lowerCamelCase_	  =					{}

 @property
 def        a__				(       self      :						Dict						)     ->			int:

       """simple docstring"""






       return len(self.decoder						)

 def        a__				(       self      :						Optional[Any]						)     ->			Dict:

       """simple docstring"""






       return dict(self.encoder		,							**self.added_tokens_encoder						)

 def        a__				(       self      :						Union[str, Any]		,							A_      :						List[Any]						)     ->			Tuple:

       """simple docstring"""






       lowerCamelCase_	  =					tuple(token[:-1]						) + (token[-1] + BPE_TOKEN_MERGES,)
       if token in self.cache:
             return self.cache[token]
       lowerCamelCase_	  =					get_pairs(A_						)

       if not pairs:
             return token

       while True:
             lowerCamelCase_	  =					min(A_		,							key=lambda A_						: self.bpe_ranks.get(A_		,							float('inf'						)						)						)
             if bigram not in self.bpe_ranks:
                   break
             lowerCamelCase_  ,       lowerCamelCase_	  =					bigram
             lowerCamelCase_	  =					[]
             lowerCamelCase_	  =					0
             while i < len(A_						):
                   try:
                         lowerCamelCase_	  =					word.index(A_		,							A_						)
                   except ValueError:
                         new_word.extend(word[i:]						)
                         break
                   else:
                         new_word.extend(word[i:j]						)
                         lowerCamelCase_	  =					j

                   if word[i] == first and i < len(A_						) - 1 and word[i + 1] == second:
                         new_word.append(first + second						)
                         i += 2
                   else:
                         new_word.append(word[i]						)
                         i += 1
             lowerCamelCase_	  =					tuple(A_						)
             lowerCamelCase_	  =					new_word
             if len(A_						) == 1:
                   break
             else:
                   lowerCamelCase_	  =					get_pairs(A_						)
       lowerCamelCase_	  =					' '.join(A_						)
       if word == "\n  " + BPE_TOKEN_MERGES:
             lowerCamelCase_	  =					'\n' + BPE_TOKEN_MERGES

       if word.endswith(A_						):
             lowerCamelCase_	  =					word.replace(A_		,							''						)

       lowerCamelCase_	  =					word.replace(' '		,							A_						)
       lowerCamelCase_	  =					word
       return word

 def        a__				(       self      :						Dict		,							A_      :						Any						)     ->			Optional[int]:

       """simple docstring"""






       if self.bpe_ranks is None:
             raise ValueError(
                 'This tokenizer was instantiated without a `merges.txt` file, so'
                 ' that it can only be used for decoding, not for encoding.'
                 'Make sure to provide `merges.txt` file at instantiation to enable '
                 'encoding.'						)

       if self.do_lower_case:
             lowerCamelCase_	  =					text.lower()

       lowerCamelCase_	  =					text.split()

       lowerCamelCase_	  =					[]
       for token in text:
             if token:
                   split_tokens.extend(list(self.bpe(A_						).split(' '						)						)						)

       return split_tokens

 def        a__				(       self      :						List[Any]		,							A_      :						str						)     ->			int:

       """simple docstring"""






       return self.encoder.get(A_		,							self.encoder.get(self.unk_token						)						)

 def        a__				(       self      :						Tuple		,							A_      :						int						)     ->			str:

       """simple docstring"""






       lowerCamelCase_	  =					self.decoder.get(A_		,							self.unk_token						)
       return result

 def        a__				(       self      :						Tuple		,							A_      :						List[str]						)     ->			str:

       """simple docstring"""






       lowerCamelCase_	  =					' '.join(A_						)

       # make sure @@ tokens are concatenated
       lowerCamelCase_	  =					''.join(string.split(A_						)						)

       return string





 def        a__				(       self      :						List[Any]		,							A_      :						str		,							A_      :						Optional[str] = None						)     ->			Tuple[str]:

       """simple docstring"""






       if not os.path.isdir(A_						):
             logger.error(f"""Vocabulary path ({save_directory}) should be a directory"""						)
             return
       lowerCamelCase_	  =					os.path.join(
           A_		,							(filename_prefix + '-' if filename_prefix else '') + VOCAB_FILES_NAMES['vocab_file']						)
       lowerCamelCase_	  =					os.path.join(
           A_		,							(filename_prefix + '-' if filename_prefix else '') + VOCAB_FILES_NAMES['merges_file']						)

       with open(A_		,							'w'		,							encoding='utf-8'						) as f:
             f.write(json.dumps(self.encoder		,							indent=2		,							sort_keys=A_		,							ensure_ascii=A_						) + '\n'						)

       lowerCamelCase_	  =					0
       if self.bpe_ranks is None:
             return (vocab_file,)

       with open(A_		,							'w'		,							encoding='utf-8'						) as writer:
             for bpe_tokens, token_index in sorted(self.bpe_ranks.items()		,							key=lambda A_						: kv[1]						):
                   if index != token_index:
                         logger.warning(
                             f"""Saving vocabulary to {merges_file}: BPE merge indices are not consecutive."""
                             ' Please check that the tokenizer is not corrupted!'						)
                         lowerCamelCase_	  =					token_index
                   writer.write(' '.join(A_						) + '\n'						)
                   index += 1

       return (vocab_file, merges_file)









import numpy as np
from cva import COLOR_BGR2GRAY, cvtColor, imread
from numpy import array, uinta
from PIL import Image

from digital_image_processing import change_contrast as cc
from digital_image_processing import convert_to_negative as cn
from digital_image_processing import sepia as sp
from digital_image_processing.dithering import burkes as bs
from digital_image_processing.edge_detection import canny
from digital_image_processing.filters import convolve as conv
from digital_image_processing.filters import gaussian_filter as gg
from digital_image_processing.filters import local_binary_pattern as lbp
from digital_image_processing.filters import median_filter as med
from digital_image_processing.filters import sobel_filter as sob
from digital_image_processing.resize import resize as rs

lowerCamelCase       :	str									=     imread(r"digital_image_processing/image_data/lena_small.jpg")
lowerCamelCase       :	Optional[Any]									=     cvtColor(img, COLOR_BGR2GRAY)

def     _SCREAMING_SNAKE_CASE    (							):


      '''simple docstring'''



      lowerCamelCase_	  =					cn.convert_to_negative(lowercase  )
      # assert negative_img array for at least one True
      assert negative_img.any()

def     _SCREAMING_SNAKE_CASE    (							):


      '''simple docstring'''



      with Image.open('digital_image_processing/image_data/lena_small.jpg'  ) as img:
            # Work around assertion for response
            assert str(cc.change_contrast(lowercase			,							1_10  )  ).startswith(
                '<PIL.Image.Image image mode=RGB size=100x100 at'  )

def     _SCREAMING_SNAKE_CASE    (							):


      '''simple docstring'''



      lowerCamelCase_	  =					canny.gen_gaussian_kernel(9			,							sigma=1.4  )
      # Assert ambiguous array
      assert resp.all()

def     _SCREAMING_SNAKE_CASE    (							):


      '''simple docstring'''



      lowerCamelCase_	  =					imread('digital_image_processing/image_data/lena_small.jpg'			,							0  )
      # assert ambiguous array for all == True
      assert canny_img.all()
      lowerCamelCase_	  =					canny.canny(lowercase  )
      # assert canny array for at least one True
      assert canny_array.any()

def     _SCREAMING_SNAKE_CASE    (							):


      '''simple docstring'''



      assert gg.gaussian_filter(lowercase			,							5			,							sigma=0.9  ).all()

def     _SCREAMING_SNAKE_CASE    (							):


      '''simple docstring'''



      lowerCamelCase_	  =					array([[0.25, 0.5, 0.25], [0.5, -3, 0.5], [0.25, 0.5, 0.25]]  )
      lowerCamelCase_	  =					conv.img_convolve(lowercase			,							lowercase  ).astype(lowercase  )
      assert res.any()

def     _SCREAMING_SNAKE_CASE    (							):


      '''simple docstring'''



      assert med.median_filter(lowercase			,							3  ).any()

def     _SCREAMING_SNAKE_CASE    (							):


      '''simple docstring'''



      lowerCamelCase_  ,       lowerCamelCase_	  =					sob.sobel_filter(lowercase  )
      assert grad.any() and theta.any()

def     _SCREAMING_SNAKE_CASE    (							):


      '''simple docstring'''



      lowerCamelCase_	  =					sp.make_sepia(lowercase			,							20  )
      assert sepia.all()

def     _SCREAMING_SNAKE_CASE    (							lowercase			: str = "digital_image_processing/image_data/lena_small.jpg"  ):


      '''simple docstring'''



      lowerCamelCase_	  =					bs.Burkes(imread(lowercase			,							1  )			,							1_20  )
      burkes.process()
      assert burkes.output_img.any()

def     _SCREAMING_SNAKE_CASE    (							lowercase			: str = "digital_image_processing/image_data/lena_small.jpg"			,							):


      '''simple docstring'''



      lowerCamelCase_	  =					rs.NearestNeighbour(imread(lowercase			,							1  )			,							4_00			,							2_00  )
      nn.process()
      assert nn.output.any()






def     _SCREAMING_SNAKE_CASE    (							):


      '''simple docstring'''



      lowerCamelCase_	  =					'digital_image_processing/image_data/lena.jpg'

      # Reading the image and converting it to grayscale.
      lowerCamelCase_	  =					imread(lowercase			,							0  )

      # Test for get_neighbors_pixel function() return not None
      lowerCamelCase_	  =					0
      lowerCamelCase_	  =					0
      lowerCamelCase_	  =					image[x_coordinate][y_coordinate]

      lowerCamelCase_	  =					lbp.get_neighbors_pixel(
          lowercase			,							lowercase			,							lowercase			,							lowercase  )

      assert neighbors_pixels is not None

      # Test for local_binary_pattern function()
      # Create a numpy array as the same height and width of read image
      lowerCamelCase_	  =					np.zeros((image.shape[0], image.shape[1])  )

      # Iterating through the image and calculating the local binary pattern value
      # for each pixel.
      for i in range(0			,							image.shape[0]  ):
            for j in range(0			,							image.shape[1]  ):
                  lowerCamelCase_	  =					lbp.local_binary_value(lowercase			,							lowercase			,							lowercase  )

      assert lbp_image.any()



