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

import regex as re

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


lowerCamelCase__    :		List[Any]          =   logging.get_logger(__name__)


lowerCamelCase__    :		Dict          =   {
    """vocab_file""": """vocab.json""",
    """merges_file""": """merges.txt""",
    """tokenizer_config_file""": """tokenizer_config.json""",
}

lowerCamelCase__    :		Optional[int]          =   {
    """vocab_file""": {
        """facebook/blenderbot_small-90M""": """https://huggingface.co/facebook/blenderbot_small-90M/resolve/main/vocab.json"""
    },
    """merges_file""": {
        """facebook/blenderbot_small-90M""": """https://huggingface.co/facebook/blenderbot_small-90M/resolve/main/merges.txt"""
    },
    """tokenizer_config_file""": {
        """facebook/blenderbot_small-90M""": (
            """https://huggingface.co/facebook/blenderbot_small-90M/resolve/main/tokenizer_config.json"""
        )
    },
}

lowerCamelCase__    :		Any          =   {"""facebook/blenderbot_small-90M""": 5_1_2}

def 		UpperCamelCase	(      lowercase_   )		->	Optional[int]:


  '''simple docstring'''






  lowercase__  :   List[str]    		=      set()
  lowercase__  :   int    		=      word[0]
  for char in word[1:]:
    pairs.add((prev_char, char)   )
    lowercase__  :   str    		=      char

  lowercase__  :   Tuple    		=      set(lowercase_   )
  return pairs



class       _snake_case   (	UpperCAmelCase_							):
 __lowerCAmelCase  :     Any        =			VOCAB_FILES_NAMES
 __lowerCAmelCase  :     int        =			PRETRAINED_VOCAB_FILES_MAP
 __lowerCAmelCase  :     List[str]        =			PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
 __lowerCAmelCase  :     Union[str, Any]        =			['input_ids', 'attention_mask']


 def __init__(					self					,  SCREAMING_SNAKE_CASE_					,  SCREAMING_SNAKE_CASE_					,  SCREAMING_SNAKE_CASE_="__start__"					,  SCREAMING_SNAKE_CASE_="__end__"					,  SCREAMING_SNAKE_CASE_="__unk__"					,  SCREAMING_SNAKE_CASE_="__null__"					,  **SCREAMING_SNAKE_CASE_					,  ):


   '''simple docstring'''




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

   with open(SCREAMING_SNAKE_CASE_					,  encoding="""utf-8""") as vocab_handle:
     lowercase__  :   Optional[int]    		=      json.load(SCREAMING_SNAKE_CASE_)
   lowercase__  :   Tuple    		=      {v: k for k, v in self.encoder.items()}
   with open(SCREAMING_SNAKE_CASE_					,  encoding="""utf-8""") as merges_handle:
     lowercase__  :   Union[str, Any]    		=      merges_handle.read().split("""\n""")[1:-1]
   lowercase__  :   List[str]    		=      [tuple(merge.split()) for merge in merges]
   lowercase__  :   str    		=      dict(zip(SCREAMING_SNAKE_CASE_					,  range(len(SCREAMING_SNAKE_CASE_))))
   lowercase__  :   int    		=      {}


 @property
 def      lowercase__     (					self):


   '''simple docstring'''




   return len(self.encoder)


 def      lowercase__     (					self):


   '''simple docstring'''




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


 def      lowercase__     (					self					,  SCREAMING_SNAKE_CASE_):


   '''simple docstring'''




   if token in self.cache:
     return self.cache[token]
   lowercase__  :   Optional[int]    		=      re.sub("""([.,!?()])"""					,  R""" \1"""					,  SCREAMING_SNAKE_CASE_)
   lowercase__  :   str    		=      re.sub("""(')"""					,  R""" \1 """					,  SCREAMING_SNAKE_CASE_)
   lowercase__  :   Tuple    		=      re.sub(R"""\s{2,}"""					,  """ """					,  SCREAMING_SNAKE_CASE_)
   if "\n" in token:
     lowercase__  :   Optional[Any]    		=      token.replace("""\n"""					,  """ __newln__""")

   lowercase__  :   List[str]    		=      token.split(""" """)
   lowercase__  :   List[Any]    		=      []
   for token in tokens:
     if not len(SCREAMING_SNAKE_CASE_):
       continue

     lowercase__  :   Union[str, Any]    		=      token.lower()
     lowercase__  :   Tuple    		=      tuple(SCREAMING_SNAKE_CASE_)
     lowercase__  :   Optional[int]    		=      tuple(list(word[:-1]) + [word[-1] + """</w>"""])
     lowercase__  :   Dict    		=      get_pairs(SCREAMING_SNAKE_CASE_)

     if not pairs:
       words.append(SCREAMING_SNAKE_CASE_)
       continue

     while True:
       lowercase__  :   str    		=      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
       lowercase__  :   str    		=      bigram
       lowercase__  :   List[str]    		=      []
       lowercase__  :   List[Any]    		=      0

       while i < len(SCREAMING_SNAKE_CASE_):
         try:
           lowercase__  :   Optional[Any]    		=      word.index(SCREAMING_SNAKE_CASE_					,  SCREAMING_SNAKE_CASE_)
           new_word.extend(word[i:j])
           lowercase__  :   Any    		=      j
         except ValueError:
           new_word.extend(word[i:])
           break

         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
       lowercase__  :   Any    		=      tuple(SCREAMING_SNAKE_CASE_)
       lowercase__  :   Tuple    		=      new_word
       if len(SCREAMING_SNAKE_CASE_) == 1:
         break
       else:
         lowercase__  :   int    		=      get_pairs(SCREAMING_SNAKE_CASE_)
     lowercase__  :   str    		=      """@@ """.join(SCREAMING_SNAKE_CASE_)
     lowercase__  :   List[str]    		=      word[:-4]

     lowercase__  :   Optional[int]    		=      word
     words.append(SCREAMING_SNAKE_CASE_)
   return " ".join(SCREAMING_SNAKE_CASE_)


 def      lowercase__     (					self					,  SCREAMING_SNAKE_CASE_):


   '''simple docstring'''




   lowercase__  :   Any    		=      []

   lowercase__  :   Union[str, Any]    		=      re.findall(R"""\S+\n?"""					,  SCREAMING_SNAKE_CASE_)

   for token in words:
     split_tokens.extend(list(self.bpe(SCREAMING_SNAKE_CASE_).split(""" """)))
   return split_tokens


 def      lowercase__     (					self					,  SCREAMING_SNAKE_CASE_):


   '''simple docstring'''




   lowercase__  :   List[Any]    		=      token.lower()
   return self.encoder.get(SCREAMING_SNAKE_CASE_					,  self.encoder.get(self.unk_token))


 def      lowercase__     (					self					,  SCREAMING_SNAKE_CASE_):


   '''simple docstring'''




   return self.decoder.get(SCREAMING_SNAKE_CASE_					,  self.unk_token)


 def      lowercase__     (					self					,  SCREAMING_SNAKE_CASE_):


   '''simple docstring'''




   lowercase__  :   str    		=      """ """.join(SCREAMING_SNAKE_CASE_).replace("""@@ """					,  """""").strip()
   return out_string



 def      lowercase__     (					self					,  SCREAMING_SNAKE_CASE_					,  SCREAMING_SNAKE_CASE_ = None):


   '''simple docstring'''




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

   lowercase__  :   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!""")
         lowercase__  :   Dict    		=      token_index
       writer.write(""" """.join(SCREAMING_SNAKE_CASE_) + """\n""")
       index += 1

   return vocab_file, merge_file



# Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
from typing import TYPE_CHECKING

import torch

from ..models.auto import AutoModelForVisualQuestionAnswering, AutoProcessor
from ..utils import requires_backends
from .base import PipelineTool


if TYPE_CHECKING:
     from PIL import Image



class       _snake_case   (	UpperCAmelCase_							):
 __lowerCAmelCase  :     Any        =			'dandelin/vilt-b32-finetuned-vqa'
 __lowerCAmelCase  :     Union[str, Any]        =			(
     'This is a tool that answers a question about an image. It takes an input named `image` which should be the '
     'image containing the information, as well as a `question` which should be the question in English. It '
     'returns a text that is the answer to the question.'
 )
 __lowerCAmelCase  :     str        =			'image_qa'
 __lowerCAmelCase  :     int        =			AutoProcessor
 __lowerCAmelCase  :     Optional[Any]        =			AutoModelForVisualQuestionAnswering

 __lowerCAmelCase  :     str        =			['image', 'text']
 __lowerCAmelCase  :     Optional[int]        =			['text']


 def __init__(					self					,  *SCREAMING_SNAKE_CASE_					,  **SCREAMING_SNAKE_CASE_):


   '''simple docstring'''




   requires_backends(self					,  ["""vision"""])
   super().__init__(*SCREAMING_SNAKE_CASE_					,  **SCREAMING_SNAKE_CASE_)


 def      lowercase__     (					self					,  SCREAMING_SNAKE_CASE_					,  SCREAMING_SNAKE_CASE_):


   '''simple docstring'''




   return self.pre_processor(SCREAMING_SNAKE_CASE_					,  SCREAMING_SNAKE_CASE_					,  return_tensors="""pt""")


 def      lowercase__     (					self					,  SCREAMING_SNAKE_CASE_):


   '''simple docstring'''




   with torch.no_grad():
     return self.model(**SCREAMING_SNAKE_CASE_).logits



 def      lowercase__     (					self					,  SCREAMING_SNAKE_CASE_):


   '''simple docstring'''




   lowercase__  :   Dict    		=      outputs.argmax(-1).item()
   return self.model.config.idalabel[idx]






