
import argparse
from collections import defaultdict

def 		UpperCamelCase	(      lowercase_ , lowercase_ , lowercase_ , lowercase_ , lowercase_   )		->	Union[str, Any]:


  '''simple docstring'''






  lowercase__  :   int    		=      F'{file}_{class_name}_{test_name}'
  done_test[_id] += 1

  with open(lowerCAmelCase__ , """r"""   ) as f:
    lowercase__  :   List[Any]    		=      f.readlines()

  lowercase__  :   List[str]    		=      F'class {class_name}('
  lowercase__  :   Any    		=      F'{4 * " "}def {test_name}('
  lowercase__  :   List[str]    		=      F'{8 * " "}{correct_line.split()[0]}'
  lowercase__  :   Optional[int]    		=      F'{16 * " "}{correct_line.split()[0]}'
  lowercase__  :   str    		=      False
  lowercase__  :   int    		=      False
  lowercase__  :   List[Any]    		=      False
  lowercase__  :   Optional[int]    		=      False
  lowercase__  :   List[Any]    		=      0
  lowercase__  :   List[str]    		=      0

  lowercase__  :   List[str]    		=      []
  for line in lines:
    if line.startswith(lowerCAmelCase__   ):
      lowercase__  :   Union[str, Any]    		=      True
    elif in_class and line.startswith(lowerCAmelCase__   ):
      lowercase__  :   Optional[int]    		=      True
    elif in_class and in_func and (line.startswith(lowerCAmelCase__   ) or line.startswith(lowerCAmelCase__   )):
      lowercase__  :   List[str]    		=      len(line.split(correct_line.split()[0]   )[0]   )
      count += 1

      if count == done_test[_id]:
        lowercase__  :   str    		=      True

    if in_class and in_func and in_line:
      if ")" not in line:
        continue
      else:
        lowercase__  :   Dict    		=      True

    if in_class and in_func and in_line and insert_line:
      new_lines.append(F'{spaces * " "}{correct_line}'   )
      lowercase__  :   str    		=      False
    else:
      new_lines.append(lowerCAmelCase__   )

  with open(lowerCAmelCase__ , """w"""   ) as f:
    for line in new_lines:
      f.write(lowerCAmelCase__   )

def 		UpperCamelCase	(      lowercase_ , lowercase_=None   )		->	Any:


  '''simple docstring'''






  if fail is not None:
    with open(lowerCAmelCase__ , """r"""   ) as f:
      lowercase__  :   Optional[int]    		=      {l.strip() for l in f.readlines()}
  else:
    lowercase__  :   Any    		=      None

  with open(lowerCAmelCase__ , """r"""   ) as f:
    lowercase__  :   int    		=      f.readlines()

  lowercase__  :   Dict    		=      defaultdict(lowerCAmelCase__   )
  for line in correct_lines:
    lowercase__		,    lowercase__		,    lowercase__		,    lowercase__  :   Optional[int]    		=      line.split(""";"""   )
    if test_failures is None or "::".join([file, class_name, test_name]   ) in test_failures:
      overwrite_file(lowerCAmelCase__ , lowerCAmelCase__ , lowerCAmelCase__ , lowerCAmelCase__ , lowerCAmelCase__   )


if __name__ == "__main__":
     lowerCamelCase__    :		List[str]          =   argparse.ArgumentParser()
     parser.add_argument("""--correct_filename""", help="""filename of tests with expected result""")
     parser.add_argument("""--fail_filename""", help="""filename of test failures""", type=str, default=None)
     lowerCamelCase__    :		Union[str, Any]          =   parser.parse_args()

     main(args.correct_filename, args.fail_filename)



# 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]






