





'''simple docstring'''




import json
import os
from functools import lru_cache
from typing import List, Optional, Tuple

import regex as re

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


lowercase__    :      Union[str, Any]						=    logging.get_logger(__name__)


lowercase__    :      Tuple						=    {'''vocab_file''': '''vocab.json''', '''merges_file''': '''merges.txt'''}

lowercase__    :      List[str]						=    {
    '''vocab_file''': {
        '''allenai/longformer-base-4096''': '''https://huggingface.co/allenai/longformer-base-4096/resolve/main/vocab.json''',
        '''allenai/longformer-large-4096''': (
            '''https://huggingface.co/allenai/longformer-large-4096/resolve/main/vocab.json'''
        ),
        '''allenai/longformer-large-4096-finetuned-triviaqa''': (
            '''https://huggingface.co/allenai/longformer-large-4096-finetuned-triviaqa/resolve/main/vocab.json'''
        ),
        '''allenai/longformer-base-4096-extra.pos.embd.only''': (
            '''https://huggingface.co/allenai/longformer-base-4096-extra.pos.embd.only/resolve/main/vocab.json'''
        ),
        '''allenai/longformer-large-4096-extra.pos.embd.only''': (
            '''https://huggingface.co/allenai/longformer-large-4096-extra.pos.embd.only/resolve/main/vocab.json'''
        ),
    },
    '''merges_file''': {
        '''allenai/longformer-base-4096''': '''https://huggingface.co/allenai/longformer-base-4096/resolve/main/merges.txt''',
        '''allenai/longformer-large-4096''': (
            '''https://huggingface.co/allenai/longformer-large-4096/resolve/main/merges.txt'''
        ),
        '''allenai/longformer-large-4096-finetuned-triviaqa''': (
            '''https://huggingface.co/allenai/longformer-large-4096-finetuned-triviaqa/resolve/main/merges.txt'''
        ),
        '''allenai/longformer-base-4096-extra.pos.embd.only''': (
            '''https://huggingface.co/allenai/longformer-base-4096-extra.pos.embd.only/resolve/main/merges.txt'''
        ),
        '''allenai/longformer-large-4096-extra.pos.embd.only''': (
            '''https://huggingface.co/allenai/longformer-large-4096-extra.pos.embd.only/resolve/main/merges.txt'''
        ),
    },
}

lowercase__    :      Any						=    {
    '''allenai/longformer-base-4096''': 40_96,
    '''allenai/longformer-large-4096''': 40_96,
    '''allenai/longformer-large-4096-finetuned-triviaqa''': 40_96,
    '''allenai/longformer-base-4096-extra.pos.embd.only''': 40_96,
    '''allenai/longformer-large-4096-extra.pos.embd.only''': 40_96,
}






@lru_cache()
# Copied from transformers.models.roberta.tokenization_roberta.bytes_to_unicode
def        _lowerCAmelCase			(  )     ->     Any:
     __A						: Optional[Any]      =       (
         list(range(ord('!'			) ,							ord('~'			) + 1			)			) + list(range(ord('¡'			) ,							ord('¬'			) + 1			)			) + list(range(ord('®'			) ,							ord('ÿ'			) + 1			)			)
     )
     __A						: int      =       bs[:]
     __A						: Optional[Any]      =       0
     for b in range(2**8			):
          if b not in bs:
               bs.append(__snake_case			)
               cs.append(2**8 + n			)
               n += 1
     __A						: Optional[int]      =       [chr(__snake_case			) for n in cs]
     return dict(zip(__snake_case ,							__snake_case			)			)






def        _lowerCAmelCase			(  __snake_case  : Union[str, Any]			)     ->     Optional[Any]:
     __A						: str      =       set()
     __A						: List[Any]      =       word[0]
     for char in word[1:]:
          pairs.add((prev_char, char)			)
          __A						: Optional[Any]      =       char
     return pairs







class  SCREAMING_SNAKE_CASE    (a__							):
     lowerCAmelCase					=       VOCAB_FILES_NAMES
     lowerCAmelCase					=       PRETRAINED_VOCAB_FILES_MAP
     lowerCAmelCase					=       PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
     lowerCAmelCase					=       ['''input_ids''', '''attention_mask''']


     def __init__(						self						,	_UpperCAmelCase						,	_UpperCAmelCase						,	_UpperCAmelCase="replace"						,	_UpperCAmelCase="<s>"						,	_UpperCAmelCase="</s>"						,	_UpperCAmelCase="</s>"						,	_UpperCAmelCase="<s>"						,	_UpperCAmelCase="<unk>"						,	_UpperCAmelCase="<pad>"						,	_UpperCAmelCase="<mask>"						,	_UpperCAmelCase=False						,	**_UpperCAmelCase						,	):

          '''simple docstring'''






          __A						: str      =       AddedToken(_UpperCAmelCase						,	lstrip=_UpperCAmelCase						,	rstrip=_UpperCAmelCase) if isinstance(_UpperCAmelCase						,	_UpperCAmelCase) else bos_token
          __A						: List[str]      =       AddedToken(_UpperCAmelCase						,	lstrip=_UpperCAmelCase						,	rstrip=_UpperCAmelCase) if isinstance(_UpperCAmelCase						,	_UpperCAmelCase) else eos_token
          __A						: str      =       AddedToken(_UpperCAmelCase						,	lstrip=_UpperCAmelCase						,	rstrip=_UpperCAmelCase) if isinstance(_UpperCAmelCase						,	_UpperCAmelCase) else sep_token
          __A						: Union[str, Any]      =       AddedToken(_UpperCAmelCase						,	lstrip=_UpperCAmelCase						,	rstrip=_UpperCAmelCase) if isinstance(_UpperCAmelCase						,	_UpperCAmelCase) else cls_token
          __A						: str      =       AddedToken(_UpperCAmelCase						,	lstrip=_UpperCAmelCase						,	rstrip=_UpperCAmelCase) if isinstance(_UpperCAmelCase						,	_UpperCAmelCase) else unk_token
          __A						: Optional[Any]      =       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						: Dict      =       AddedToken(_UpperCAmelCase						,	lstrip=_UpperCAmelCase						,	rstrip=_UpperCAmelCase) if isinstance(_UpperCAmelCase						,	_UpperCAmelCase) else mask_token

          super().__init__(
              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						,	)

          with open(_UpperCAmelCase						,	encoding='utf-8') as vocab_handle:
               __A						: Union[str, Any]      =       json.load(_UpperCAmelCase)
          __A						: str      =       {v: k for k, v in self.encoder.items()}
          __A						: Union[str, Any]      =       errors  # how to handle errors in decoding
          __A						: Any      =       bytes_to_unicode()
          __A						: Any      =       {v: k for k, v in self.byte_encoder.items()}
          with open(_UpperCAmelCase						,	encoding='utf-8') as merges_handle:
               __A						: Optional[int]      =       merges_handle.read().split('\n')[1:-1]
          __A						: Tuple      =       [tuple(merge.split()) for merge in bpe_merges]
          __A						: Dict      =       dict(zip(_UpperCAmelCase						,	range(len(_UpperCAmelCase))))
          __A						: Optional[int]      =       {}
          __A						: Optional[int]      =       add_prefix_space

          # Should have added re.IGNORECASE so BPE merges can happen for capitalized versions of contractions
          __A						: Any      =       re.compile(R'\'s|\'t|\'re|\'ve|\'m|\'ll|\'d| ?\p{L}+| ?\p{N}+| ?[^\s\p{L}\p{N}]+|\s+(?!\S)|\s+')


     @property
     def 							SCREAMING_SNAKE_CASE  (						self):

          '''simple docstring'''






          return len(self.encoder)


     def 							SCREAMING_SNAKE_CASE  (						self):

          '''simple docstring'''






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


     def 							SCREAMING_SNAKE_CASE  (						self						,	_UpperCAmelCase):

          '''simple docstring'''






          if token in self.cache:
               return self.cache[token]
          __A						: Union[str, Any]      =       tuple(_UpperCAmelCase)
          __A						: Union[str, Any]      =       get_pairs(_UpperCAmelCase)

          if not pairs:
               return token

          while True:
               __A						: Any      =       min(_UpperCAmelCase						,	key=lambda _UpperCAmelCase: self.bpe_ranks.get(_UpperCAmelCase						,	float('inf')))
               if bigram not in self.bpe_ranks:
                    break
               __A ,__A						: Tuple      =       bigram
               __A						: Dict      =       []
               __A						: List[str]      =       0
               while i < len(_UpperCAmelCase):
                    try:
                         __A						: List[str]      =       word.index(_UpperCAmelCase						,	_UpperCAmelCase)
                    except ValueError:
                         new_word.extend(word[i:])
                         break
                    else:
                         new_word.extend(word[i:j])
                         __A						: Optional[Any]      =       j

                    if word[i] == first and i < len(_UpperCAmelCase) - 1 and word[i + 1] == second:
                         new_word.append(first + second)
                         i += 2
                    else:
                         new_word.append(word[i])
                         i += 1
               __A						: Optional[Any]      =       tuple(_UpperCAmelCase)
               __A						: Tuple      =       new_word
               if len(_UpperCAmelCase) == 1:
                    break
               else:
                    __A						: Optional[int]      =       get_pairs(_UpperCAmelCase)
          __A						: List[Any]      =       ' '.join(_UpperCAmelCase)
          __A						: int      =       word
          return word


     def 							SCREAMING_SNAKE_CASE  (						self						,	_UpperCAmelCase):

          '''simple docstring'''






          __A						: List[str]      =       []
          for token in re.findall(self.pat						,	_UpperCAmelCase):
               __A						: Any      =       ''.join(
                   self.byte_encoder[b] for b in token.encode('utf-8'))  # Maps all our bytes to unicode strings, avoiding control tokens of the BPE (spaces in our case)
               bpe_tokens.extend(bpe_token for bpe_token in self.bpe(_UpperCAmelCase).split(' '))
          return bpe_tokens


     def 							SCREAMING_SNAKE_CASE  (						self						,	_UpperCAmelCase):

          '''simple docstring'''






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


     def 							SCREAMING_SNAKE_CASE  (						self						,	_UpperCAmelCase):

          '''simple docstring'''






          return self.decoder.get(_UpperCAmelCase)


     def 							SCREAMING_SNAKE_CASE  (						self						,	_UpperCAmelCase):

          '''simple docstring'''






          __A						: Dict      =       ''.join(_UpperCAmelCase)
          __A						: Any      =       bytearray([self.byte_decoder[c] for c in text]).decode('utf-8'						,	errors=self.errors)
          return text


     def 							SCREAMING_SNAKE_CASE  (						self						,	_UpperCAmelCase						,	_UpperCAmelCase = None):

          '''simple docstring'''






          if not os.path.isdir(_UpperCAmelCase):
               logger.error(F'Vocabulary path ({save_directory}) should be a directory')
               return
          __A						: str      =       os.path.join(
              _UpperCAmelCase						,	(filename_prefix + '-' if filename_prefix else '') + VOCAB_FILES_NAMES['vocab_file'])
          __A						: List[Any]      =       os.path.join(
              _UpperCAmelCase						,	(filename_prefix + '-' if filename_prefix else '') + VOCAB_FILES_NAMES['merges_file'])

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

          __A						: int      =       0
          with open(_UpperCAmelCase						,	'w'						,	encoding='utf-8') as writer:
               writer.write('#version: 0.2\n')
               for bpe_tokens, token_index in sorted(self.bpe_ranks.items()						,	key=lambda _UpperCAmelCase: kv[1]):
                    if index != token_index:
                         logger.warning(
                             F'Saving vocabulary to {merge_file}: BPE merge indices are not consecutive.'
                             ' Please check that the tokenizer is not corrupted!')
                         __A						: List[str]      =       token_index
                    writer.write(' '.join(_UpperCAmelCase) + '\n')
                    index += 1

          return vocab_file, merge_file


     def 							SCREAMING_SNAKE_CASE  (						self						,	_UpperCAmelCase						,	_UpperCAmelCase = None):

          '''simple docstring'''






          if token_ids_a is None:
               return [self.cls_token_id] + token_ids_a + [self.sep_token_id]
          __A						: List[Any]      =       [self.cls_token_id]
          __A						: List[str]      =       [self.sep_token_id]
          return cls + token_ids_a + sep + sep + token_ids_a + sep


     def 							SCREAMING_SNAKE_CASE  (						self						,	_UpperCAmelCase						,	_UpperCAmelCase = None						,	_UpperCAmelCase = False):

          '''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)

          if token_ids_a is None:
               return [1] + ([0] * len(_UpperCAmelCase)) + [1]
          return [1] + ([0] * len(_UpperCAmelCase)) + [1, 1] + ([0] * len(_UpperCAmelCase)) + [1]


     def 							SCREAMING_SNAKE_CASE  (						self						,	_UpperCAmelCase						,	_UpperCAmelCase = None):

          '''simple docstring'''






          __A						: Union[str, Any]      =       [self.sep_token_id]
          __A						: Tuple      =       [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 + sep + token_ids_a + sep) * [0]


     def 							SCREAMING_SNAKE_CASE  (						self						,	_UpperCAmelCase						,	_UpperCAmelCase=False						,	**_UpperCAmelCase):

          '''simple docstring'''






          __A						: List[str]      =       kwargs.pop('add_prefix_space'						,	self.add_prefix_space)
          if (is_split_into_words or add_prefix_space) and (len(_UpperCAmelCase) > 0 and not text[0].isspace()):
               __A						: Optional[int]      =       ' ' + text
          return (text, kwargs)






'''simple docstring'''




import hashlib
import unittest
from typing import Dict

import numpy as np

from transformers import (
    MODEL_FOR_MASK_GENERATION_MAPPING,
    TF_MODEL_FOR_MASK_GENERATION_MAPPING,
    is_vision_available,
    pipeline,
)
from transformers.pipelines import MaskGenerationPipeline
from transformers.testing_utils import (
    is_pipeline_test,
    nested_simplify,
    require_tf,
    require_torch,
    require_vision,
    slow,
)


if is_vision_available():
  from PIL import Image
else:


  class  SCREAMING_SNAKE_CASE    :


       @staticmethod
       def 							SCREAMING_SNAKE_CASE  (						*_UpperCAmelCase						,	**_UpperCAmelCase):

            '''simple docstring'''






            pass






def        _lowerCAmelCase			(  __snake_case  : Image			)     ->     str:
     __A						: Dict      =       hashlib.mda(image.tobytes()			)
     return m.hexdigest()[:10]






def        _lowerCAmelCase			(  __snake_case  : Image			)     ->     Dict:
     __A						: Dict      =       np.array(__snake_case			)
     __A						: List[Any]      =       npimg.shape
     return {"hash": hashimage(__snake_case			), "shape": shape}







@is_pipeline_test
@require_vision
@require_torch
class  SCREAMING_SNAKE_CASE    (unittest.TestCase							):
     lowerCAmelCase					=       dict(
         (list(MODEL_FOR_MASK_GENERATION_MAPPING.items()							) if MODEL_FOR_MASK_GENERATION_MAPPING else [])							)
     lowerCAmelCase					=       dict(
         (list(TF_MODEL_FOR_MASK_GENERATION_MAPPING.items()							) if TF_MODEL_FOR_MASK_GENERATION_MAPPING else [])							)


     def 							SCREAMING_SNAKE_CASE  (						self						,	_UpperCAmelCase						,	_UpperCAmelCase						,	_UpperCAmelCase):

          '''simple docstring'''






          __A						: Any      =       MaskGenerationPipeline(model=_UpperCAmelCase						,	image_processor=_UpperCAmelCase)
          return image_segmenter, [
              "./tests/fixtures/tests_samples/COCO/000000039769.png",
              "./tests/fixtures/tests_samples/COCO/000000039769.png",
          ]


     def 							SCREAMING_SNAKE_CASE  (						self						,	_UpperCAmelCase						,	_UpperCAmelCase):

          '''simple docstring'''






          pass


     @require_tf
     @unittest.skip('Image segmentation not implemented in TF')
     def 							SCREAMING_SNAKE_CASE  (						self):

          '''simple docstring'''






          pass


     @slow
     @require_torch
     def 							SCREAMING_SNAKE_CASE  (						self):

          '''simple docstring'''






          __A						: Optional[int]      =       pipeline('mask-generation'						,	model='facebook/sam-vit-huge')

          __A						: Tuple      =       image_segmenter('http://images.cocodataset.org/val2017/000000039769.jpg'						,	points_per_batch=256)

          # Shortening by hashing
          __A						: int      =       []
          for i, o in enumerate(outputs['masks']):
               new_outupt += [{"mask": mask_to_test_readable(_UpperCAmelCase), "scores": outputs["scores"][i]}]

          # fmt: off
          self.assertEqual(
              nested_simplify(_UpperCAmelCase						,	decimals=4)						,	[
                  {'mask': {'hash': '115ad19f5f', 'shape': (480, 640)}, 'scores': 1.0444},
                  {'mask': {'hash': '6affa964c6', 'shape': (480, 640)}, 'scores': 1.021},
                  {'mask': {'hash': 'dfe28a0388', 'shape': (480, 640)}, 'scores': 1.0167},
                  {'mask': {'hash': 'c0a5f4a318', 'shape': (480, 640)}, 'scores': 1.0132},
                  {'mask': {'hash': 'fe8065c197', 'shape': (480, 640)}, 'scores': 1.0053},
                  {'mask': {'hash': 'e2d0b7a0b7', 'shape': (480, 640)}, 'scores': 0.9967},
                  {'mask': {'hash': '453c7844bd', 'shape': (480, 640)}, 'scores': 0.993},
                  {'mask': {'hash': '3d44f2926d', 'shape': (480, 640)}, 'scores': 0.9909},
                  {'mask': {'hash': '64033ddc3f', 'shape': (480, 640)}, 'scores': 0.9879},
                  {'mask': {'hash': '801064ff79', 'shape': (480, 640)}, 'scores': 0.9834},
                  {'mask': {'hash': '6172f276ef', 'shape': (480, 640)}, 'scores': 0.9716},
                  {'mask': {'hash': 'b49e60e084', 'shape': (480, 640)}, 'scores': 0.9612},
                  {'mask': {'hash': 'a811e775fd', 'shape': (480, 640)}, 'scores': 0.9599},
                  {'mask': {'hash': 'a6a8ebcf4b', 'shape': (480, 640)}, 'scores': 0.9552},
                  {'mask': {'hash': '9d8257e080', 'shape': (480, 640)}, 'scores': 0.9532},
                  {'mask': {'hash': '32de6454a8', 'shape': (480, 640)}, 'scores': 0.9516},
                  {'mask': {'hash': 'af3d4af2c8', 'shape': (480, 640)}, 'scores': 0.9499},
                  {'mask': {'hash': '3c6db475fb', 'shape': (480, 640)}, 'scores': 0.9483},
                  {'mask': {'hash': 'c290813fb9', 'shape': (480, 640)}, 'scores': 0.9464},
                  {'mask': {'hash': 'b6f0b8f606', 'shape': (480, 640)}, 'scores': 0.943},
                  {'mask': {'hash': '92ce16bfdf', 'shape': (480, 640)}, 'scores': 0.943},
                  {'mask': {'hash': 'c749b25868', 'shape': (480, 640)}, 'scores': 0.9408},
                  {'mask': {'hash': 'efb6cab859', 'shape': (480, 640)}, 'scores': 0.9335},
                  {'mask': {'hash': '1ff2eafb30', 'shape': (480, 640)}, 'scores': 0.9326},
                  {'mask': {'hash': '788b798e24', 'shape': (480, 640)}, 'scores': 0.9262},
                  {'mask': {'hash': 'abea804f0e', 'shape': (480, 640)}, 'scores': 0.8999},
                  {'mask': {'hash': '7b9e8ddb73', 'shape': (480, 640)}, 'scores': 0.8986},
                  {'mask': {'hash': 'cd24047c8a', 'shape': (480, 640)}, 'scores': 0.8984},
                  {'mask': {'hash': '6943e6bcbd', 'shape': (480, 640)}, 'scores': 0.8873},
                  {'mask': {'hash': 'b5f47c9191', 'shape': (480, 640)}, 'scores': 0.8871}
              ]						,	)
          # fmt: on


     @require_torch
     @slow
     def 							SCREAMING_SNAKE_CASE  (						self):

          '''simple docstring'''






          __A						: int      =       'facebook/sam-vit-huge'
          __A						: Optional[Any]      =       pipeline('mask-generation'						,	model=_UpperCAmelCase)

          __A						: int      =       image_segmenter(
              'http://images.cocodataset.org/val2017/000000039769.jpg'						,	pred_iou_thresh=1						,	points_per_batch=256)

          # Shortening by hashing
          __A						: int      =       []
          for i, o in enumerate(outputs['masks']):
               new_outupt += [{"mask": mask_to_test_readable(_UpperCAmelCase), "scores": outputs["scores"][i]}]

          self.assertEqual(
              nested_simplify(_UpperCAmelCase						,	decimals=4)						,	[
                  {'mask': {'hash': '115ad19f5f', 'shape': (480, 640)}, 'scores': 1.0444},
                  {'mask': {'hash': '6affa964c6', 'shape': (480, 640)}, 'scores': 1.0210},
                  {'mask': {'hash': 'dfe28a0388', 'shape': (480, 640)}, 'scores': 1.0167},
                  {'mask': {'hash': 'c0a5f4a318', 'shape': (480, 640)}, 'scores': 1.0132},
                  {'mask': {'hash': 'fe8065c197', 'shape': (480, 640)}, 'scores': 1.0053},
              ]						,	)