
"""simple docstring"""




def 						__magic_name__			(   __a      :	List[Any]	,		__a      :	List[Any]						):



     '''simple docstring'''




     UpperCamelCase__				=    len(__lowerCAmelCase						)
     UpperCamelCase__				=    []
     for i in range(len(__lowerCAmelCase						) - pat_len + 1						):
          UpperCamelCase__				=    True
          for j in range(__lowerCAmelCase						):
               if s[i + j] != pattern[j]:
                    UpperCamelCase__				=    False
                    break
          if match_found:
               position.append(__lowerCAmelCase						)
     return position


if __name__ == "__main__":
    assert naive_pattern_search('''ABCDEFG''', '''DE''') == [3]
    print(naive_pattern_search('''ABAAABCDBBABCDDEBCABC''', '''ABC'''))







from pathlib import Path
from typing import List

from transformers import is_torch_available, is_vision_available
from transformers.testing_utils import get_tests_dir, is_tool_test
from transformers.tools.agent_types import AGENT_TYPE_MAPPING, AgentAudio, AgentImage, AgentText


if is_torch_available():
    import torch

if is_vision_available():
    from PIL import Image


lowerCamelCase_						     =					['''text''', '''image''', '''audio''']






def 						__magic_name__			(   __a      :	List[str]						):



     '''simple docstring'''




     UpperCamelCase__				=    []

     for input_type in input_types:
          if input_type == "text":
               inputs.append("""Text input"""						)
          elif input_type == "image":
               inputs.append(
                   Image.open(Path(get_tests_dir("""fixtures/tests_samples/COCO"""						)						) / """000000039769.png"""						).resize((512, 512)						)						)
          elif input_type == "audio":
               inputs.append(torch.ones(3_000						)						)
          elif isinstance(__a	,		__a						):
               inputs.append(create_inputs(__a						)						)
          else:
               raise ValueError(f"Invalid type requested: {input_type}"						)

     return inputs






def 						__magic_name__			(   __a      :	List						):



     '''simple docstring'''




     UpperCamelCase__				=    []

     for output in outputs:
          if isinstance(__a	,		(str, AgentText)						):
               output_types.append("""text"""						)
          elif isinstance(__a	,		(Image.Image, AgentImage)						):
               output_types.append("""image"""						)
          elif isinstance(__a	,		(torch.Tensor, AgentAudio)						):
               output_types.append("""audio"""						)
          else:
               raise ValueError(f"Invalid output: {output}"						)

     return output_types




@is_tool_test
class      __A:

  """simple docstring"""







  def 	UpperCAmelCase_ (self						):
       self.assertTrue(hasattr(self.tool	,      """inputs"""						)						)
       self.assertTrue(hasattr(self.tool	,      """outputs"""						)						)

       UpperCamelCase__				=    self.tool.inputs
       for _input in inputs:
            if isinstance(_input	,      SCREAMING_SNAKE_CASE_						):
                 for __input in _input:
                      self.assertTrue(__input in authorized_types						)
            else:
                 self.assertTrue(_input in authorized_types						)

       UpperCamelCase__				=    self.tool.outputs
       for _output in outputs:
            self.assertTrue(_output in authorized_types						)







  def 	UpperCAmelCase_ (self						):
       UpperCamelCase__				=    create_inputs(self.tool.inputs						)
       UpperCamelCase__				=    self.tool(*SCREAMING_SNAKE_CASE_						)

       # There is a single output
       if len(self.tool.outputs						) == 1:
            UpperCamelCase__				=    [outputs]

       self.assertListEqual(output_types(SCREAMING_SNAKE_CASE_						)	,      self.tool.outputs						)







  def 	UpperCAmelCase_ (self						):
       self.assertTrue(hasattr(self.tool	,      """description"""						)						)
       self.assertTrue(hasattr(self.tool	,      """default_checkpoint"""						)						)
       self.assertTrue(self.tool.description.startswith("""This is a tool that"""						)						)







  def 	UpperCAmelCase_ (self						):
       UpperCamelCase__				=    create_inputs(self.tool.inputs						)
       UpperCamelCase__				=    self.tool(*SCREAMING_SNAKE_CASE_						)

       if not isinstance(SCREAMING_SNAKE_CASE_	,      SCREAMING_SNAKE_CASE_						):
            UpperCamelCase__				=    [outputs]

       self.assertEqual(len(SCREAMING_SNAKE_CASE_						)	,      len(self.tool.outputs						)						)

       for output, output_type in zip(SCREAMING_SNAKE_CASE_	,      self.tool.outputs						):
            UpperCamelCase__				=    AGENT_TYPE_MAPPING[output_type]
            self.assertTrue(isinstance(SCREAMING_SNAKE_CASE_	,      SCREAMING_SNAKE_CASE_						)						)







  def 	UpperCAmelCase_ (self						):
       UpperCamelCase__				=    create_inputs(self.tool.inputs						)

       UpperCamelCase__				=    []

       for _input, input_type in zip(SCREAMING_SNAKE_CASE_	,      self.tool.inputs						):
            if isinstance(SCREAMING_SNAKE_CASE_	,      SCREAMING_SNAKE_CASE_						):
                 _inputs.append([AGENT_TYPE_MAPPING[_input_type](_input						) for _input_type in input_type]						)
            else:
                 _inputs.append(AGENT_TYPE_MAPPING[input_type](_input						)						)

        # Should not raise an error
       UpperCamelCase__				=    self.tool(*SCREAMING_SNAKE_CASE_						)

       if not isinstance(SCREAMING_SNAKE_CASE_	,      SCREAMING_SNAKE_CASE_						):
            UpperCamelCase__				=    [outputs]

       self.assertEqual(len(SCREAMING_SNAKE_CASE_						)	,      len(self.tool.outputs						)						)





