





"""simple docstring"""
import inspect
import unittest

from transformers import is_torch_available, is_vision_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, slow, torch_device

from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTesterMixin, floats_tensor, ids_tensor
from ...test_pipeline_mixin import PipelineTesterMixin


if is_torch_available():
  import torch

  from transformers import MODEL_MAPPING, PoolFormerConfig, PoolFormerForImageClassification, PoolFormerModel
  from transformers.models.poolformer.modeling_poolformer import POOLFORMER_PRETRAINED_MODEL_ARCHIVE_LIST


if is_vision_available():
  from PIL import Image

  from transformers import PoolFormerImageProcessor






class       _SCREAMING_SNAKE_CASE(     A						):




       def 					_UpperCamelCase  (		self							)    ->   int:





             """simple docstring"""






             __SCREAMING_SNAKE_CASE     :int	       =						self.config_class(**self.inputs_dict							)
             self.parent.assertTrue(hasattr(SCREAMING_SNAKE_CASE__	,'''hidden_sizes'''							)							)
             self.parent.assertTrue(hasattr(SCREAMING_SNAKE_CASE__	,'''num_encoder_blocks'''							)							)






class       _SCREAMING_SNAKE_CASE:




       def __init__(		self	,SCREAMING_SNAKE_CASE__	,SCREAMING_SNAKE_CASE__=13	,SCREAMING_SNAKE_CASE__=64	,SCREAMING_SNAKE_CASE__=3	,SCREAMING_SNAKE_CASE__=4	,SCREAMING_SNAKE_CASE__=[2, 2, 2, 2]	,SCREAMING_SNAKE_CASE__=[8, 4, 2, 1]	,SCREAMING_SNAKE_CASE__=[16, 32, 64, 1_28]	,SCREAMING_SNAKE_CASE__=[1, 4, 8, 16]	,SCREAMING_SNAKE_CASE__=False	,SCREAMING_SNAKE_CASE__=True	,SCREAMING_SNAKE_CASE__="gelu"	,SCREAMING_SNAKE_CASE__=0.1	,SCREAMING_SNAKE_CASE__=0.0_2	,SCREAMING_SNAKE_CASE__=3	,SCREAMING_SNAKE_CASE__=None	,)    ->   Optional[Any]:





             """simple docstring"""






             __SCREAMING_SNAKE_CASE     :List[Any]	       =						parent
             __SCREAMING_SNAKE_CASE     :Optional[Any]	       =						batch_size
             __SCREAMING_SNAKE_CASE     :Dict	       =						image_size
             __SCREAMING_SNAKE_CASE     :Tuple	       =						num_channels
             __SCREAMING_SNAKE_CASE     :List[str]	       =						num_encoder_blocks
             __SCREAMING_SNAKE_CASE     :Any	       =						sr_ratios
             __SCREAMING_SNAKE_CASE     :Dict	       =						depths
             __SCREAMING_SNAKE_CASE     :List[Any]	       =						hidden_sizes
             __SCREAMING_SNAKE_CASE     :Dict	       =						downsampling_rates
             __SCREAMING_SNAKE_CASE     :Union[str, Any]	       =						is_training
             __SCREAMING_SNAKE_CASE     :str	       =						use_labels
             __SCREAMING_SNAKE_CASE     :Any	       =						hidden_act
             __SCREAMING_SNAKE_CASE     :Dict	       =						hidden_dropout_prob
             __SCREAMING_SNAKE_CASE     :Optional[int]	       =						initializer_range
             __SCREAMING_SNAKE_CASE     :Optional[int]	       =						num_labels
             __SCREAMING_SNAKE_CASE     :Union[str, Any]	       =						scope




       def 					_UpperCamelCase  (		self							)    ->   str:





             """simple docstring"""






             __SCREAMING_SNAKE_CASE     :Dict	       =						floats_tensor([self.batch_size, self.num_channels, self.image_size, self.image_size]							)

             __SCREAMING_SNAKE_CASE     :int	       =						None
             if self.use_labels:
                   __SCREAMING_SNAKE_CASE     :List[str]	       =						ids_tensor([self.batch_size, self.image_size, self.image_size]	,self.num_labels							)

             __SCREAMING_SNAKE_CASE     :List[Any]	       =						PoolFormerConfig(
                 image_size=self.image_size	,num_channels=self.num_channels	,num_encoder_blocks=self.num_encoder_blocks	,depths=self.depths	,hidden_sizes=self.hidden_sizes	,hidden_act=self.hidden_act	,hidden_dropout_prob=self.hidden_dropout_prob	,initializer_range=self.initializer_range	,)

             return config, pixel_values, labels




       def 					_UpperCamelCase  (		self	,SCREAMING_SNAKE_CASE__	,SCREAMING_SNAKE_CASE__	,SCREAMING_SNAKE_CASE__							)    ->   Optional[int]:





             """simple docstring"""






             __SCREAMING_SNAKE_CASE     :Union[str, Any]	       =						PoolFormerModel(config=SCREAMING_SNAKE_CASE__							)
             model.to(SCREAMING_SNAKE_CASE__							)
             model.eval()
             __SCREAMING_SNAKE_CASE     :Union[str, Any]	       =						model(SCREAMING_SNAKE_CASE__							)
             __SCREAMING_SNAKE_CASE     :List[Any]	       =						self.image_size // 3_2.0
             self.parent.assertEqual(
                 result.last_hidden_state.shape	,(self.batch_size, self.hidden_sizes[-1], expected_height, expected_width)							)




       def 					_UpperCamelCase  (		self							)    ->   Tuple:





             """simple docstring"""






             __SCREAMING_SNAKE_CASE     :Tuple	       =						self.prepare_config_and_inputs()
             __SCREAMING_SNAKE_CASE       ,__SCREAMING_SNAKE_CASE       ,__SCREAMING_SNAKE_CASE     :Union[str, Any]	       =						config_and_inputs
             __SCREAMING_SNAKE_CASE     :Any	       =						{'''pixel_values''': pixel_values}
             return config, inputs_dict






@require_torch
class       _SCREAMING_SNAKE_CASE(     A					,			A					,			unittest.TestCase						):
       SCREAMING_SNAKE_CASE_     :   Union[str, Any]					=						(PoolFormerModel, PoolFormerForImageClassification) if is_torch_available() else ()
       SCREAMING_SNAKE_CASE_     :   Dict					=						(
           {'''feature-extraction''': PoolFormerModel, '''image-classification''': PoolFormerForImageClassification}
           if is_torch_available()
           else {}
       )

       SCREAMING_SNAKE_CASE_     :   Union[str, Any]					=						False
       SCREAMING_SNAKE_CASE_     :   List[str]					=						False
       SCREAMING_SNAKE_CASE_     :   Tuple					=						False
       SCREAMING_SNAKE_CASE_     :   Optional[int]					=						False
       SCREAMING_SNAKE_CASE_     :   List[Any]					=						False




       def 					_UpperCamelCase  (		self							)    ->   Tuple:





             """simple docstring"""






             __SCREAMING_SNAKE_CASE     :Optional[int]	       =						PoolFormerModelTester(self							)
             __SCREAMING_SNAKE_CASE     :Any	       =						PoolFormerConfigTester(self	,config_class=SCREAMING_SNAKE_CASE__							)




       def 					_UpperCamelCase  (		self							)    ->   Any:





             """simple docstring"""






             self.config_tester.run_common_tests()




       def 					_UpperCamelCase  (		self							)    ->   Dict:





             """simple docstring"""






             __SCREAMING_SNAKE_CASE     :Union[str, Any]	       =						self.model_tester.prepare_config_and_inputs()
             self.model_tester.create_and_check_model(*SCREAMING_SNAKE_CASE__							)




       @unittest.skip('''PoolFormer does not use inputs_embeds'''							)
       def 					_UpperCamelCase  (		self							)    ->   List[str]:





             """simple docstring"""






             pass




       @unittest.skip('''PoolFormer does not have get_input_embeddings method and get_output_embeddings methods'''							)
       def 					_UpperCamelCase  (		self							)    ->   Union[str, Any]:





             """simple docstring"""






             pass




       def 					_UpperCamelCase  (		self							)    ->   List[Any]:





             """simple docstring"""






             def check_hidden_states_output(SCREAMING_SNAKE_CASE__	,SCREAMING_SNAKE_CASE__	,SCREAMING_SNAKE_CASE__							):
                   __SCREAMING_SNAKE_CASE     :List[str]	       =						model_class(SCREAMING_SNAKE_CASE__							)
                   model.to(SCREAMING_SNAKE_CASE__							)
                   model.eval()

                   with torch.no_grad():
                         __SCREAMING_SNAKE_CASE     :Optional[int]	       =						model(**self._prepare_for_class(SCREAMING_SNAKE_CASE__	,SCREAMING_SNAKE_CASE__							)							)

                   __SCREAMING_SNAKE_CASE     :List[str]	       =						outputs.hidden_states

                   __SCREAMING_SNAKE_CASE     :str	       =						self.model_tester.num_encoder_blocks
                   self.assertEqual(len(SCREAMING_SNAKE_CASE__							)	,SCREAMING_SNAKE_CASE__							)

                   # verify the first hidden states (first block)
                   self.assertListEqual(
                       list(hidden_states[0].shape[-3:]							)	,[
                           self.model_tester.hidden_sizes[0],
                           self.model_tester.image_size // 4,
                           self.model_tester.image_size // 4,
                       ]	,)

             __SCREAMING_SNAKE_CASE       ,__SCREAMING_SNAKE_CASE     :Optional[int]	       =						self.model_tester.prepare_config_and_inputs_for_common()

             for model_class in self.all_model_classes:
                   __SCREAMING_SNAKE_CASE     :List[str]	       =						True
                   check_hidden_states_output(SCREAMING_SNAKE_CASE__	,SCREAMING_SNAKE_CASE__	,SCREAMING_SNAKE_CASE__							)

                   # check that output_hidden_states also work using config
                   del inputs_dict["output_hidden_states"]
                   __SCREAMING_SNAKE_CASE     :Tuple	       =						True

                   check_hidden_states_output(SCREAMING_SNAKE_CASE__	,SCREAMING_SNAKE_CASE__	,SCREAMING_SNAKE_CASE__							)




       def 					_UpperCamelCase  (		self							)    ->   List[Any]:





             """simple docstring"""






             if not self.model_tester.is_training:
                   return

             __SCREAMING_SNAKE_CASE       ,__SCREAMING_SNAKE_CASE     :Any	       =						self.model_tester.prepare_config_and_inputs_for_common()
             __SCREAMING_SNAKE_CASE     :Dict	       =						True

             for model_class in self.all_model_classes:
                   if model_class in get_values(SCREAMING_SNAKE_CASE__							):
                         continue
                   __SCREAMING_SNAKE_CASE     :int	       =						model_class(SCREAMING_SNAKE_CASE__							)
                   model.to(SCREAMING_SNAKE_CASE__							)
                   model.train()
                   __SCREAMING_SNAKE_CASE     :Tuple	       =						self._prepare_for_class(SCREAMING_SNAKE_CASE__	,SCREAMING_SNAKE_CASE__	,return_labels=SCREAMING_SNAKE_CASE__							)
                   __SCREAMING_SNAKE_CASE     :List[Any]	       =						model(**SCREAMING_SNAKE_CASE__							).loss
                   loss.backward()




       def 					_UpperCamelCase  (		self							)    ->   Tuple:





             """simple docstring"""






             __SCREAMING_SNAKE_CASE       ,__SCREAMING_SNAKE_CASE     :Optional[int]	       =						self.model_tester.prepare_config_and_inputs_for_common()

             for model_class in self.all_model_classes:
                   __SCREAMING_SNAKE_CASE     :Any	       =						model_class(SCREAMING_SNAKE_CASE__							)
                   __SCREAMING_SNAKE_CASE     :str	       =						inspect.signature(model.forward							)
                   # signature.parameters is an OrderedDict => so arg_names order is deterministic
                   __SCREAMING_SNAKE_CASE     :int	       =						[*signature.parameters.keys()]

                   __SCREAMING_SNAKE_CASE     :int	       =						['''pixel_values''']
                   self.assertListEqual(arg_names[:1]	,SCREAMING_SNAKE_CASE__							)




       @slow
       def 					_UpperCamelCase  (		self							)    ->   Optional[int]:





             """simple docstring"""






             for model_name in POOLFORMER_PRETRAINED_MODEL_ARCHIVE_LIST[:1]:
                   __SCREAMING_SNAKE_CASE     :str	       =						PoolFormerModel.from_pretrained(SCREAMING_SNAKE_CASE__							)
                   self.assertIsNotNone(SCREAMING_SNAKE_CASE__							)




def   __lowerCamelCase     (							)    ->   Union[str, Any]:
      __SCREAMING_SNAKE_CASE     :Optional[Any]	       =						Image.open('''./tests/fixtures/tests_samples/COCO/000000039769.png'''							)
      return image







@require_torch
class       _SCREAMING_SNAKE_CASE(     unittest.TestCase						):




       @slow
       def 					_UpperCamelCase  (		self							)    ->   Any:





             """simple docstring"""






             __SCREAMING_SNAKE_CASE     :Union[str, Any]	       =						PoolFormerImageProcessor()
             __SCREAMING_SNAKE_CASE     :Optional[int]	       =						PoolFormerForImageClassification.from_pretrained('''sail/poolformer_s12'''							).to(SCREAMING_SNAKE_CASE__							)

             __SCREAMING_SNAKE_CASE     :Any	       =						image_processor(images=prepare_img()	,return_tensors='''pt'''							).to(SCREAMING_SNAKE_CASE__							)

             # forward pass
             with torch.no_grad():
                   __SCREAMING_SNAKE_CASE     :Optional[int]	       =						model(**SCREAMING_SNAKE_CASE__							)

             # verify the logits
             __SCREAMING_SNAKE_CASE     :Tuple	       =						torch.Size((1, 10_00)							)
             self.assertEqual(outputs.logits.shape	,SCREAMING_SNAKE_CASE__							)

             __SCREAMING_SNAKE_CASE     :Any	       =						torch.tensor([-0.6_1_1_3, 0.1_6_8_5, -0.0_4_9_2]							).to(SCREAMING_SNAKE_CASE__							)
             self.assertTrue(torch.allclose(outputs.logits[0, :3]	,SCREAMING_SNAKE_CASE__	,atol=1E-4							)							)






"""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


lowerCamelCase_          =	logging.get_logger(__name__)


lowerCamelCase_          =	{"vocab_file": "vocab.json", "merges_file": "merges.txt"}

# See all MVP models at https://huggingface.co/models?filter=mvp
lowerCamelCase_          =	{
    "vocab_file": {
        "RUCAIBox/mvp": "https://huggingface.co/RUCAIBox/mvp/resolve/main/vocab.json",
    },
    "added_tokens.json": {
        "RUCAIBox/mvp": "https://huggingface.co/RUCAIBox/mvp/resolve/main/added_tokens.json",
    },
    "merges_file": {
        "RUCAIBox/mvp": "https://huggingface.co/RUCAIBox/mvp/resolve/main/merges.txt",
    },
}

lowerCamelCase_          =	{
    "RUCAIBox/mvp": 1_0_2_4,
}



@lru_cache()
def   __lowerCamelCase     (							)    ->   List[Any]:
      __SCREAMING_SNAKE_CASE     :Optional[Any]	       =						(
          list(range(ord('''!'''							)				,     ord('''~'''							) + 1							)							) + list(range(ord('''¡'''							)				,     ord('''¬'''							) + 1							)							) + list(range(ord('''®'''							)				,     ord('''ÿ'''							) + 1							)							)
      )
      __SCREAMING_SNAKE_CASE     :Optional[Any]	       =						bs[:]
      __SCREAMING_SNAKE_CASE     :str	       =						0
      for b in range(2**8							):
            if b not in bs:
                  bs.append(a_							)
                  cs.append(2**8 + n							)
                  n += 1
      __SCREAMING_SNAKE_CASE     :int	       =						[chr(a_							) for n in cs]
      return dict(zip(a_				,     a_							)							)



def   __lowerCamelCase     (							a_  :	Dict							)    ->   List[str]:
      __SCREAMING_SNAKE_CASE     :Optional[Any]	       =						set()
      __SCREAMING_SNAKE_CASE     :Dict	       =						word[0]
      for char in word[1:]:
            pairs.add((prev_char, char)							)
            __SCREAMING_SNAKE_CASE     :List[str]	       =						char
      return pairs







class       _SCREAMING_SNAKE_CASE(     A						):
       SCREAMING_SNAKE_CASE_     :   str					=						VOCAB_FILES_NAMES
       SCREAMING_SNAKE_CASE_     :   Union[str, Any]					=						PRETRAINED_VOCAB_FILES_MAP
       SCREAMING_SNAKE_CASE_     :   Tuple					=						PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
       SCREAMING_SNAKE_CASE_     :   List[Any]					=						['''input_ids''', '''attention_mask''']




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





             """simple docstring"""






             __SCREAMING_SNAKE_CASE     :Dict	       =						AddedToken(SCREAMING_SNAKE_CASE__	,lstrip=SCREAMING_SNAKE_CASE__	,rstrip=SCREAMING_SNAKE_CASE__							) if isinstance(SCREAMING_SNAKE_CASE__	,SCREAMING_SNAKE_CASE__							) else bos_token
             __SCREAMING_SNAKE_CASE     :List[Any]	       =						AddedToken(SCREAMING_SNAKE_CASE__	,lstrip=SCREAMING_SNAKE_CASE__	,rstrip=SCREAMING_SNAKE_CASE__							) if isinstance(SCREAMING_SNAKE_CASE__	,SCREAMING_SNAKE_CASE__							) else eos_token
             __SCREAMING_SNAKE_CASE     :str	       =						AddedToken(SCREAMING_SNAKE_CASE__	,lstrip=SCREAMING_SNAKE_CASE__	,rstrip=SCREAMING_SNAKE_CASE__							) if isinstance(SCREAMING_SNAKE_CASE__	,SCREAMING_SNAKE_CASE__							) else sep_token
             __SCREAMING_SNAKE_CASE     :Dict	       =						AddedToken(SCREAMING_SNAKE_CASE__	,lstrip=SCREAMING_SNAKE_CASE__	,rstrip=SCREAMING_SNAKE_CASE__							) if isinstance(SCREAMING_SNAKE_CASE__	,SCREAMING_SNAKE_CASE__							) else cls_token
             __SCREAMING_SNAKE_CASE     :str	       =						AddedToken(SCREAMING_SNAKE_CASE__	,lstrip=SCREAMING_SNAKE_CASE__	,rstrip=SCREAMING_SNAKE_CASE__							) if isinstance(SCREAMING_SNAKE_CASE__	,SCREAMING_SNAKE_CASE__							) else unk_token
             __SCREAMING_SNAKE_CASE     :Optional[int]	       =						AddedToken(SCREAMING_SNAKE_CASE__	,lstrip=SCREAMING_SNAKE_CASE__	,rstrip=SCREAMING_SNAKE_CASE__							) if isinstance(SCREAMING_SNAKE_CASE__	,SCREAMING_SNAKE_CASE__							) else pad_token

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

             super().__init__(
                 errors=SCREAMING_SNAKE_CASE__	,bos_token=SCREAMING_SNAKE_CASE__	,eos_token=SCREAMING_SNAKE_CASE__	,unk_token=SCREAMING_SNAKE_CASE__	,sep_token=SCREAMING_SNAKE_CASE__	,cls_token=SCREAMING_SNAKE_CASE__	,pad_token=SCREAMING_SNAKE_CASE__	,mask_token=SCREAMING_SNAKE_CASE__	,add_prefix_space=SCREAMING_SNAKE_CASE__	,**SCREAMING_SNAKE_CASE__	,)
             with open(SCREAMING_SNAKE_CASE__	,encoding='''utf-8'''							) as vocab_handle:
                   __SCREAMING_SNAKE_CASE     :List[str]	       =						json.load(SCREAMING_SNAKE_CASE__							)
             __SCREAMING_SNAKE_CASE     :Any	       =						{v: k for k, v in self.encoder.items()}
             __SCREAMING_SNAKE_CASE     :Optional[Any]	       =						errors  # how to handle errors in decoding
             __SCREAMING_SNAKE_CASE     :Dict	       =						bytes_to_unicode()
             __SCREAMING_SNAKE_CASE     :Dict	       =						{v: k for k, v in self.byte_encoder.items()}
             with open(SCREAMING_SNAKE_CASE__	,encoding='''utf-8'''							) as merges_handle:
                   __SCREAMING_SNAKE_CASE     :Optional[Any]	       =						merges_handle.read().split('''\n'''							)[1:-1]
             __SCREAMING_SNAKE_CASE     :Optional[int]	       =						[tuple(merge.split()							) for merge in bpe_merges]
             __SCREAMING_SNAKE_CASE     :Union[str, Any]	       =						dict(zip(SCREAMING_SNAKE_CASE__	,range(len(SCREAMING_SNAKE_CASE__							)							)							)							)
             __SCREAMING_SNAKE_CASE     :Any	       =						{}
             __SCREAMING_SNAKE_CASE     :Union[str, Any]	       =						add_prefix_space

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




       @property
       def 					_UpperCamelCase  (		self							)    ->   Union[str, Any]:





             """simple docstring"""






             return len(self.encoder							)




       def 					_UpperCamelCase  (		self							)    ->   Dict:





             """simple docstring"""






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




       def 					_UpperCamelCase  (		self	,SCREAMING_SNAKE_CASE__							)    ->   Tuple:





             """simple docstring"""






             if token in self.cache:
                   return self.cache[token]
             __SCREAMING_SNAKE_CASE     :Tuple	       =						tuple(SCREAMING_SNAKE_CASE__							)
             __SCREAMING_SNAKE_CASE     :List[str]	       =						get_pairs(SCREAMING_SNAKE_CASE__							)

             if not pairs:
                   return token

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

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




       def 					_UpperCamelCase  (		self	,SCREAMING_SNAKE_CASE__							)    ->   Optional[Any]:





             """simple docstring"""






             __SCREAMING_SNAKE_CASE     :str	       =						[]
             for token in re.findall(self.pat	,SCREAMING_SNAKE_CASE__							):
                   __SCREAMING_SNAKE_CASE     :List[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(SCREAMING_SNAKE_CASE__							).split(''' '''							)							)
             return bpe_tokens




       def 					_UpperCamelCase  (		self	,SCREAMING_SNAKE_CASE__							)    ->   List[Any]:





             """simple docstring"""






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




       def 					_UpperCamelCase  (		self	,SCREAMING_SNAKE_CASE__							)    ->   Optional[Any]:





             """simple docstring"""






             return self.decoder.get(SCREAMING_SNAKE_CASE__							)




       def 					_UpperCamelCase  (		self	,SCREAMING_SNAKE_CASE__							)    ->   int:





             """simple docstring"""






             __SCREAMING_SNAKE_CASE     :Union[str, Any]	       =						''''''.join(SCREAMING_SNAKE_CASE__							)
             __SCREAMING_SNAKE_CASE     :List[Any]	       =						bytearray([self.byte_decoder[c] for c in text]							).decode('''utf-8'''	,errors=self.errors							)
             return text




       def 					_UpperCamelCase  (		self	,SCREAMING_SNAKE_CASE__	,SCREAMING_SNAKE_CASE__ = None							)    ->   Tuple[str]:





             """simple docstring"""






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

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

             __SCREAMING_SNAKE_CASE     :Optional[int]	       =						0
             with open(SCREAMING_SNAKE_CASE__	,'''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 SCREAMING_SNAKE_CASE__							: 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!'''							)
                               __SCREAMING_SNAKE_CASE     :int	       =						token_index
                         writer.write(''' '''.join(SCREAMING_SNAKE_CASE__							) + '''\n'''							)
                         index += 1

             return vocab_file, merge_file




       def 					_UpperCamelCase  (		self	,SCREAMING_SNAKE_CASE__	,SCREAMING_SNAKE_CASE__ = None							)    ->   List[int]:





             """simple docstring"""






             if token_ids_a is None:
                   return [self.cls_token_id] + token_ids_a + [self.sep_token_id]
             __SCREAMING_SNAKE_CASE     :Optional[Any]	       =						[self.cls_token_id]
             __SCREAMING_SNAKE_CASE     :Optional[int]	       =						[self.sep_token_id]
             return cls + token_ids_a + sep + sep + token_ids_a + sep




       def 					_UpperCamelCase  (		self	,SCREAMING_SNAKE_CASE__	,SCREAMING_SNAKE_CASE__ = None	,SCREAMING_SNAKE_CASE__ = False							)    ->   List[int]:





             """simple docstring"""






             if already_has_special_tokens:
                   return super().get_special_tokens_mask(
                       token_ids_a=SCREAMING_SNAKE_CASE__	,token_ids_a=SCREAMING_SNAKE_CASE__	,already_has_special_tokens=SCREAMING_SNAKE_CASE__							)

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




       def 					_UpperCamelCase  (		self	,SCREAMING_SNAKE_CASE__	,SCREAMING_SNAKE_CASE__ = None							)    ->   List[int]:





             """simple docstring"""






             __SCREAMING_SNAKE_CASE     :List[Any]	       =						[self.sep_token_id]
             __SCREAMING_SNAKE_CASE     :str	       =						[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 					_UpperCamelCase  (		self	,SCREAMING_SNAKE_CASE__	,SCREAMING_SNAKE_CASE__=False	,**SCREAMING_SNAKE_CASE__							)    ->   Union[str, Any]:





             """simple docstring"""






             __SCREAMING_SNAKE_CASE     :Tuple	       =						kwargs.pop('''add_prefix_space'''	,self.add_prefix_space							)
             if (is_split_into_words or add_prefix_space) and (len(SCREAMING_SNAKE_CASE__							) > 0 and not text[0].isspace()):
                   __SCREAMING_SNAKE_CASE     :Any	       =						''' ''' + text
             return (text, kwargs)