

'''simple docstring'''







from typing import Dict, List, Optional

from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging


__lowerCamelCase		       =    logging.get_logger(__name__)


__lowerCamelCase		       =    {
    '''nielsr/canine-s''': 2048,
}

# Unicode defines 1,114,112 total “codepoints”
__lowerCamelCase		       =    111_4112

# Below: Constants defining canonical codepoints for special, pseudo-characters.
# Copied from https://github.com/google-research/language/blob/master/language/canine/special_codepoints.py
__lowerCamelCase		       =    0

__lowerCamelCase		       =    0Xe000
__lowerCamelCase		       =    0Xe001
__lowerCamelCase		       =    0Xe002
__lowerCamelCase		       =    0Xe003
__lowerCamelCase		       =    0Xe004

# Maps special codepoints to human-readable names.
__lowerCamelCase		       =    {
    # Special symbols are represented using codepoints values that are valid,
    # but designated as "Private Use", meaning that they will never be assigned
    # characters by the Unicode Consortium, and are thus safe for use here.
    #
    # NOTE: Do *NOT* add any sort of [UNK_CHAR] here. They are explicitly
    # excluded and should fail with a hard error.
    CLS: '''[CLS]''',
    SEP: '''[SEP]''',
    BOS: '''[BOS]''',
    MASK: '''[MASK]''',
    PAD: '''[PAD]''',
    RESERVED: '''[RESERVED]''',
}

# Maps special codepoint human-readable names to their codepoint values.
__lowerCamelCase		       =    {name: codepoint for codepoint, name in SPECIAL_CODEPOINTS.items()}


class 					A__      (      _snake_case			):
				lowercase						=		PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES



				def __init__(					self		,				UpperCamelCase__=chr(UpperCamelCase__       )		,				UpperCamelCase__=chr(UpperCamelCase__       )		,				UpperCamelCase__=chr(UpperCamelCase__       )		,				UpperCamelCase__=chr(UpperCamelCase__       )		,				UpperCamelCase__=chr(UpperCamelCase__       )		,				UpperCamelCase__=chr(UpperCamelCase__       )		,				UpperCamelCase__=False		,				UpperCamelCase__=2048		,				**UpperCamelCase__		,				)						->      List[Any]:





											'''simple docstring'''
											A_						=      AddedToken(UpperCamelCase__		,				lstrip=UpperCamelCase__		,				rstrip=UpperCamelCase__       ) if isinstance(UpperCamelCase__		,				UpperCamelCase__       ) else bos_token
											A_						=      AddedToken(UpperCamelCase__		,				lstrip=UpperCamelCase__		,				rstrip=UpperCamelCase__       ) if isinstance(UpperCamelCase__		,				UpperCamelCase__       ) else eos_token
											A_						=      AddedToken(UpperCamelCase__		,				lstrip=UpperCamelCase__		,				rstrip=UpperCamelCase__       ) if isinstance(UpperCamelCase__		,				UpperCamelCase__       ) else sep_token
											A_						=      AddedToken(UpperCamelCase__		,				lstrip=UpperCamelCase__		,				rstrip=UpperCamelCase__       ) if isinstance(UpperCamelCase__		,				UpperCamelCase__       ) else cls_token
											A_						=      AddedToken(UpperCamelCase__		,				lstrip=UpperCamelCase__		,				rstrip=UpperCamelCase__       ) if isinstance(UpperCamelCase__		,				UpperCamelCase__       ) else pad_token

											# Mask token behave like a normal word, i.e. include the space before it
											A_						=      AddedToken(UpperCamelCase__		,				lstrip=UpperCamelCase__		,				rstrip=UpperCamelCase__       ) if isinstance(UpperCamelCase__		,				UpperCamelCase__       ) else mask_token

											super().__init__(
											    bos_token=UpperCamelCase__		,				eos_token=UpperCamelCase__		,				sep_token=UpperCamelCase__		,				cls_token=UpperCamelCase__		,				pad_token=UpperCamelCase__		,				mask_token=UpperCamelCase__		,				add_prefix_space=UpperCamelCase__		,				model_max_length=UpperCamelCase__		,				**UpperCamelCase__		,				)

											# Creates a mapping for looking up the IDs of special symbols.
											A_						=      {}
											for codepoint, name in SPECIAL_CODEPOINTS.items():
																		A_						=      codepoint

											# Creates a mapping for looking up the string forms of special symbol IDs.
											A_						=      {
											    codepoint: name for name, codepoint in self._special_codepoints.items()
											}

											A_						=      UNICODE_VOCAB_SIZE
											A_						=      len(self._special_codepoints       )



				@property
				def 					snake_case_			(					self       )						->      int:





											'''simple docstring'''
											return self._unicode_vocab_size



				def 					snake_case_			(					self		,				UpperCamelCase__       )						->      List[str]:





											'''simple docstring'''
											return list(UpperCamelCase__       )



				def 					snake_case_			(					self		,				UpperCamelCase__       )						->      int:





											'''simple docstring'''
											try:
																		return ord(UpperCamelCase__       )
											except TypeError:
																		raise ValueError(f'''invalid token: \'{token}\''''       )



				def 					snake_case_			(					self		,				UpperCamelCase__       )						->      str:





											'''simple docstring'''
											try:
																		if index in SPECIAL_CODEPOINTS:
																									return SPECIAL_CODEPOINTS[index]
																		return chr(UpperCamelCase__       )
											except TypeError:
																		raise ValueError(f'''invalid id: {index}'''       )



				def 					snake_case_			(					self		,				UpperCamelCase__       )						->      str:





											'''simple docstring'''
											return "".join(UpperCamelCase__       )



				def 					snake_case_			(					self		,				UpperCamelCase__		,				UpperCamelCase__ = None       )						->      List[int]:





											'''simple docstring'''
											A_						=      [self.sep_token_id]
											A_						=      [self.cls_token_id]

											A_						=      cls + token_ids_a + sep
											if token_ids_a is not None:
																		result += token_ids_a + sep
											return result



				def 					snake_case_			(					self		,				UpperCamelCase__		,				UpperCamelCase__ = None		,				UpperCamelCase__ = False       )						->      List[int]:





											'''simple docstring'''
											if already_has_special_tokens:
																		return super().get_special_tokens_mask(
																		    token_ids_a=UpperCamelCase__		,				token_ids_a=UpperCamelCase__		,				already_has_special_tokens=UpperCamelCase__       )

											A_						=      [1] + ([0] * len(UpperCamelCase__       )) + [1]
											if token_ids_a is not None:
																		result += ([0] * len(UpperCamelCase__       )) + [1]
											return result



				def 					snake_case_			(					self		,				UpperCamelCase__		,				UpperCamelCase__ = None       )						->      List[int]:





											'''simple docstring'''
											A_						=      [self.sep_token_id]
											A_						=      [self.cls_token_id]

											A_						=      len(cls + token_ids_a + sep       ) * [0]
											if token_ids_a is not None:
																		result += len(token_ids_a + sep       ) * [1]
											return result







				def 					snake_case_			(					self		,				UpperCamelCase__		,				UpperCamelCase__ = None       )						->      Tuple:





											'''simple docstring'''
											return ()



'''simple docstring'''







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		       =    imread(r'''digital_image_processing/image_data/lena_small.jpg''')
__lowerCamelCase		       =    cvtColor(img, COLOR_BGR2GRAY)
def       UpperCAmelCase__    (      )			->			Dict:
       A_						=      cn.convert_to_negative(UpperCAmelCase__				)
       # assert negative_img array for at least one True
       assert negative_img.any()
def       UpperCAmelCase__    (      )			->			List[Any]:
       with Image.open("""digital_image_processing/image_data/lena_small.jpg"""				) as img:
              # Work around assertion for response
              assert str(cc.change_contrast(UpperCAmelCase__,       1_10				)				).startswith(
                  """<PIL.Image.Image image mode=RGB size=100x100 at"""				)
def       UpperCAmelCase__    (      )			->			str:
       A_						=      canny.gen_gaussian_kernel(9,       sigma=1.4				)
       # Assert ambiguous array
       assert resp.all()
def       UpperCAmelCase__    (      )			->			Union[str, Any]:
       A_						=      imread("""digital_image_processing/image_data/lena_small.jpg""",       0				)
       # assert ambiguous array for all == True
       assert canny_img.all()
       A_						=      canny.canny(UpperCAmelCase__				)
       # assert canny array for at least one True
       assert canny_array.any()
def       UpperCAmelCase__    (      )			->			Dict:
       assert gg.gaussian_filter(UpperCAmelCase__,       5,       sigma=0.9				).all()
def       UpperCAmelCase__    (      )			->			int:
       # laplace diagonals
       A_						=      array([[0.25, 0.5, 0.25], [0.5, -3, 0.5], [0.25, 0.5, 0.25]]				)
       A_						=      conv.img_convolve(UpperCAmelCase__,       UpperCAmelCase__				).astype(UpperCAmelCase__				)
       assert res.any()
def       UpperCAmelCase__    (      )			->			List[Any]:
       assert med.median_filter(UpperCAmelCase__,       3				).any()
def       UpperCAmelCase__    (      )			->			List[Any]:
       A_					,			A_						=      sob.sobel_filter(UpperCAmelCase__				)
       assert grad.any() and theta.any()
def       UpperCAmelCase__    (      )			->			List[str]:
       A_						=      sp.make_sepia(UpperCAmelCase__,       20				)
       assert sepia.all()
def       UpperCAmelCase__    (      UpperCAmelCase__ = "digital_image_processing/image_data/lena_small.jpg"				)			->			List[Any]:
       A_						=      bs.Burkes(imread(UpperCAmelCase__,       1				),       1_20				)
       burkes.process()
       assert burkes.output_img.any()
def       UpperCAmelCase__    (      UpperCAmelCase__ = "digital_image_processing/image_data/lena_small.jpg",       )			->			Optional[int]:
       A_						=      rs.NearestNeighbour(imread(UpperCAmelCase__,       1				),       4_00,       2_00				)
       nn.process()
       assert nn.output.any()







def       UpperCAmelCase__    (      )			->			Optional[int]:
       A_						=      """digital_image_processing/image_data/lena.jpg"""

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

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

       A_						=      lbp.get_neighbors_pixel(
           UpperCAmelCase__,       UpperCAmelCase__,       UpperCAmelCase__,       UpperCAmelCase__				)

       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
       A_						=      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]				):
                     A_						=      lbp.local_binary_value(UpperCAmelCase__,       UpperCAmelCase__,       UpperCAmelCase__				)

       assert lbp_image.any()
