

import unittest

from transformers.image_processing_utils import get_size_dict

class      _a				( unittest.TestCase							):




      """simple docstring"""

      def 		__A  (      self       :							List[Any]  ):
            # Test a dict with the wrong keys raises an error
            A_	     =							{'''wrong_key''': 224}
            with self.assertRaises(_snake_case  ):
                  get_size_dict(_snake_case  )

            A_	     =							{'''height''': 224}
            with self.assertRaises(_snake_case  ):
                  get_size_dict(_snake_case  )

            A_	     =							{'''width''': 224, '''shortest_edge''': 224}
            with self.assertRaises(_snake_case  ):
                  get_size_dict(_snake_case  )

            # Test a dict with the correct keys is returned as is
            A_	     =							{'''height''': 224, '''width''': 224}
            A_	     =							get_size_dict(_snake_case  )
            self.assertEqual(_snake_case	, _snake_case  )

            A_	     =							{'''shortest_edge''': 224}
            A_	     =							get_size_dict(_snake_case  )
            self.assertEqual(_snake_case	, {"shortest_edge": 224}  )

            A_	     =							{'''longest_edge''': 224, '''shortest_edge''': 224}
            A_	     =							get_size_dict(_snake_case  )
            self.assertEqual(_snake_case	, {"longest_edge": 224, "shortest_edge": 224}  )

            # Test a single int value which  represents (size, size)
            A_	     =							get_size_dict(224  )
            self.assertEqual(_snake_case	, {"height": 224, "width": 224}  )

            # Test a single int value which represents the shortest edge
            A_	     =							get_size_dict(224	, default_to_square=_snake_case  )
            self.assertEqual(_snake_case	, {"shortest_edge": 224}  )

            # Test a tuple of ints which represents (height, width)
            A_	     =							get_size_dict((150, 200)  )
            self.assertEqual(_snake_case	, {"height": 150, "width": 200}  )

            # Test a tuple of ints which represents (width, height)
            A_	     =							get_size_dict((150, 200)	, height_width_order=_snake_case  )
            self.assertEqual(_snake_case	, {"height": 200, "width": 150}  )

            # Test an int representing the shortest edge and max_size which represents the longest edge
            A_	     =							get_size_dict(224	, max_size=256	, default_to_square=_snake_case  )
            self.assertEqual(_snake_case	, {"shortest_edge": 224, "longest_edge": 256}  )

            # Test int with default_to_square=True and max_size fails
            with self.assertRaises(_snake_case  ):
                  get_size_dict(224	, max_size=256	, default_to_square=_snake_case  )









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

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


__a						:Optional[Any]            = logging.get_logger(__name__)

__a						:Union[str, Any]            = {
    'vocab_file': 'vocab.json',
    'merges_file': 'merges.txt',
}

__a						:Union[str, Any]            = {
    'vocab_file': {
        'microsoft/biogpt': 'https://huggingface.co/microsoft/biogpt/resolve/main/vocab.json',
    },
    'merges_file': {'microsoft/biogpt': 'https://huggingface.co/microsoft/biogpt/resolve/main/merges.txt'},
}

__a						:str            = {
    'microsoft/biogpt': 1024,
}

def 			__snake_case	(   __UpperCamelCase  :   Any						):



      """simple docstring"""

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



class      _a				( snake_case_							):




      """simple docstring"""

      _lowerCamelCase					: Tuple					=					VOCAB_FILES_NAMES
      _lowerCamelCase					: Any					=					PRETRAINED_VOCAB_FILES_MAP
      _lowerCamelCase					: str					=					PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
      _lowerCamelCase					: List[Any]					=					['input_ids', 'attention_mask']





      def __init__(      self       :							Union[str, Any]	, UpperCAmelCase       :							Union[str, Any]	, UpperCAmelCase       :							Optional[int]	, UpperCAmelCase       :							List[Any]="<unk>"	, UpperCAmelCase       :							Dict="<s>"	, UpperCAmelCase       :							Tuple="</s>"	, UpperCAmelCase       :							Optional[int]="</s>"	, UpperCAmelCase       :							int="<pad>"	, **UpperCAmelCase       :							List[str]	, ):
            super().__init__(
                bos_token=UpperCAmelCase	, eos_token=UpperCAmelCase	, sep_token=UpperCAmelCase	, unk_token=UpperCAmelCase	, pad_token=UpperCAmelCase	, **UpperCAmelCase	, )

            try:
                  import sacremoses
            except ImportError:
                  raise ImportError(
                      "You need to install sacremoses to use BioGptTokenizer. "
                      "See https://pypi.org/project/sacremoses/ for installation."  )

            A_	     =							"en"
            A_	     =							sacremoses
            # cache of sm.MosesTokenizer instance
            A_	     =							{}
            A_	     =							{}
            with open(UpperCAmelCase	, encoding="utf-8"  ) as vocab_handle:
                  A_	     =							json.load(UpperCAmelCase  )
            A_	     =							{v: k for k, v in self.encoder.items()}
            with open(UpperCAmelCase	, encoding="utf-8"  ) as merges_handle:
                  A_	     =							merges_handle.read().split("\n"  )[:-1]
            A_	     =							[tuple(merge.split()[:2]  ) for merge in merges]
            A_	     =							dict(zip(UpperCAmelCase	, range(len(UpperCAmelCase  )  )  )  )
            A_	     =							{}





      @property
      def 		__A  (      self       :							int  ):
            return len(self.encoder  )





      def 		__A  (      self       :							Union[str, Any]  ):
            return dict(self.encoder	, **self.added_tokens_encoder  )





      def 		__A  (      self       :							Any	, UpperCAmelCase       :							Union[str, Any]	, UpperCAmelCase       :							Optional[Any]  ):
            if lang not in self.cache_moses_tokenizer:
                  A_	     =							self.sm.MosesTokenizer(lang=UpperCAmelCase  )
                  A_	     =							moses_tokenizer
            return self.cache_moses_tokenizer[lang].tokenize(
                UpperCAmelCase	, aggressive_dash_splits=UpperCAmelCase	, return_str=UpperCAmelCase	, escape=UpperCAmelCase  )





      def 		__A  (      self       :							List[Any]	, UpperCAmelCase       :							Tuple	, UpperCAmelCase       :							List[Any]  ):
            if lang not in self.cache_moses_detokenizer:
                  A_	     =							self.sm.MosesDetokenizer(lang=UpperCAmelCase  )
                  A_	     =							moses_detokenizer
            return self.cache_moses_detokenizer[lang].detokenize(UpperCAmelCase  )





      def 		__A  (      self       :							Optional[Any]	, UpperCAmelCase       :							int  ):
            A_	     =							tuple(token[:-1]  ) + (token[-1] + "</w>",)
            if token in self.cache:
                  return self.cache[token]
            A_	     =							get_pairs(UpperCAmelCase  )

            if not pairs:
                  return token + "</w>"

            while True:
                  A_	     =							min(UpperCAmelCase	, key=lambda UpperCAmelCase  : self.bpe_ranks.get(UpperCAmelCase	, float("inf"  )  )  )
                  if bigram not in self.bpe_ranks:
                        break
                  A_     ,    A_	     =							bigram
                  A_	     =							[]
                  A_	     =							0
                  while i < len(UpperCAmelCase  ):
                        try:
                              A_	     =							word.index(UpperCAmelCase	, UpperCAmelCase  )
                        except ValueError:
                              new_word.extend(word[i:]  )
                              break
                        else:
                              new_word.extend(word[i:j]  )
                              A_	     =							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_	     =							tuple(UpperCAmelCase  )
                  A_	     =							new_word
                  if len(UpperCAmelCase  ) == 1:
                        break
                  else:
                        A_	     =							get_pairs(UpperCAmelCase  )
            A_	     =							" ".join(UpperCAmelCase  )
            if word == "\n  </w>":
                  A_	     =							"\n</w>"
            A_	     =							word
            return word





      def 		__A  (      self       :							Optional[int]	, UpperCAmelCase       :							str	, UpperCAmelCase       :							Optional[Any]=False  ):
            if bypass_tokenizer:
                  A_	     =							text.split()
            else:
                  A_	     =							self.moses_tokenize(UpperCAmelCase	, self.lang  )

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

            return split_tokens





      def 		__A  (      self       :							Dict	, UpperCAmelCase       :							Union[str, Any]  ):
            return self.encoder.get(UpperCAmelCase	, self.encoder.get(self.unk_token  )  )





      def 		__A  (      self       :							Optional[Any]	, UpperCAmelCase       :							List[str]  ):
            return self.decoder.get(UpperCAmelCase	, self.unk_token  )





      def 		__A  (      self       :							Dict	, UpperCAmelCase       :							Any  ):
            A_	     =							[t.replace(" "	, ""  ).replace("</w>"	, " "  ) for t in tokens]
            A_	     =							"".join(UpperCAmelCase  ).split()
            # detokenize
            A_	     =							self.moses_detokenize(UpperCAmelCase	, self.lang  )
            return text





      def 		__A  (      self       :							List[str]	, UpperCAmelCase       :							List[int]	, UpperCAmelCase       :							Optional[List[int]] = None  ):
            if token_ids_a is None:
                  return [self.sep_token_id] + token_ids_a
            A_	     =							[self.sep_token_id]
            return sep + token_ids_a + sep + token_ids_a





      def 		__A  (      self       :							Any	, UpperCAmelCase       :							List[int]	, UpperCAmelCase       :							Optional[List[int]] = None	, UpperCAmelCase       :							bool = False  ):
            if already_has_special_tokens:
                  return super().get_special_tokens_mask(
                      token_ids_a=UpperCAmelCase	, token_ids_a=UpperCAmelCase	, already_has_special_tokens=UpperCAmelCase  )
            # no bos used in fairseq
            if token_ids_a is not None:
                  return [1] + ([0] * len(UpperCAmelCase  )) + [1] + ([0] * len(UpperCAmelCase  ))
            return [1] + ([0] * len(UpperCAmelCase  ))





      def 		__A  (      self       :							Optional[Any]	, UpperCAmelCase       :							List[int]	, UpperCAmelCase       :							Optional[List[int]] = None  ):
            A_	     =							[self.sep_token_id]

            # no bos used in fairseq
            if token_ids_a is None:
                  return len(token_ids_a + sep  ) * [0]
            return len(token_ids_a + sep  ) * [0] + len(token_ids_a + sep  ) * [1]





      def 		__A  (      self       :							Union[str, Any]	, UpperCAmelCase       :							str	, UpperCAmelCase       :							Optional[str] = None  ):
            if not os.path.isdir(UpperCAmelCase  ):
                  logger.error(f'''Vocabulary path ({save_directory}) should be a directory'''  )
                  return
            A_	     =							os.path.join(
                UpperCAmelCase	, (filename_prefix + "-" if filename_prefix else "") + VOCAB_FILES_NAMES["vocab_file"]  )
            A_	     =							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_	     =							0
            with open(UpperCAmelCase	, "w"	, encoding="utf-8"  ) as writer:
                  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_	     =							token_index
                        writer.write(" ".join(UpperCAmelCase  ) + "\n"  )
                        index += 1

            return vocab_file, merge_file





      def __getstate__(      self       :							Union[str, Any]  ):
            A_	     =							self.__dict__.copy()
            A_	     =							None
            return state







      def __setstate__(      self       :							List[Any]	, UpperCAmelCase       :							Dict  ):
            A_	     =							d

            try:
                  import sacremoses
            except ImportError:
                  raise ImportError(
                      "You need to install sacremoses to use XLMTokenizer. "
                      "See https://pypi.org/project/sacremoses/ for installation."  )

            A_	     =							sacremoses