



'''simple docstring'''





from __future__ import annotations

from collections import deque
from collections.abc import Iterator
from dataclasses import dataclass






@dataclass
class __A    :



 '''simple docstring'''







 __lowerCamelCase					: int
 __lowerCamelCase					: int






class __A    :



 '''simple docstring'''







 def __init__(self				,     A )					->  str:


      """simple docstring"""



      _a											=						[[] for _ in range(A )]
      _a											=						size



 def __getitem__(self				,     A )					->  Iterator[Edge]:


      """simple docstring"""



      return iter(self._graph[vertex] )



 @property
 def       a__						(self )					->  Optional[Any]:


      """simple docstring"""



      return self._size



 def       a__						(self				,     A				,     A				,     A )					->  Optional[int]:


      """simple docstring"""



      if weight not in (0, 1):
           raise ValueError('''Edge weight must be either 0 or 1.''' )

      if to_vertex < 0 or to_vertex >= self.size:
           raise ValueError('''Vertex indexes must be in [0; size).''' )

      self._graph[from_vertex].append(Edge(A				,     A ) )



 def       a__						(self				,     A				,     A )					->  int | None:


      """simple docstring"""



      _a											=						deque([start_vertex] )
      _a											=						[None] * self.size
      _a											=						0

      while queue:
           _a											=						queue.popleft()
           _a											=						distances[current_vertex]
           if current_distance is None:
                continue

           for edge in self[current_vertex]:
                _a											=						current_distance + edge.weight
                _a											=						distances[edge.destination_vertex]
                if (
                    isinstance(A				,     A )
                    and new_distance >= dest_vertex_distance
                ):
                     continue
                _a											=						new_distance
                if edge.weight == 0:
                     queue.appendleft(edge.destination_vertex )
                else:
                     queue.append(edge.destination_vertex )

      if distances[finish_vertex] is None:
           raise ValueError('''No path from start_vertex to finish_vertex.''' )

      return distances[finish_vertex]


if __name__ == "__main__":
  import doctest

  doctest.testmod()








'''simple docstring'''





import sys
import tempfile
import unittest
import unittest.mock as mock
from pathlib import Path

from huggingface_hub import HfFolder, delete_repo
from requests.exceptions import HTTPError

from transformers import AutoImageProcessor, ViTImageProcessor
from transformers.testing_utils import TOKEN, USER, get_tests_dir, is_staging_test


sys.path.append(str(Path(__file__).parent.parent / "utils"))

from test_module.custom_image_processing import CustomImageProcessor  # noqa E402


lowercase_	 =						get_tests_dir("fixtures")






class __A    (						unittest.TestCase		):



 '''simple docstring'''







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


      """simple docstring"""



      _a											=						mock.Mock()
      _a											=						500
      _a											=						{}
      _a											=						HTTPError
      _a											=						{}

      # Download this model to make sure it's in the cache.
      _a											=						ViTImageProcessor.from_pretrained('''hf-internal-testing/tiny-random-vit''' )
      # Under the mock environment we get a 500 error when trying to reach the model.
      with mock.patch('''requests.Session.request'''				,     return_value=A ) as mock_head:
           _a											=						ViTImageProcessor.from_pretrained('''hf-internal-testing/tiny-random-vit''' )
           # This check we did call the fake head request
           mock_head.assert_called()



 def       a__						(self )					->  str:


      """simple docstring"""



      _a											=						ViTImageProcessor.from_pretrained(
          '''https://huggingface.co/hf-internal-testing/tiny-random-vit/resolve/main/preprocessor_config.json''' )



 def       a__						(self )					->  Dict:


      """simple docstring"""



      with self.assertRaises(A ):
           # config is in subfolder, the following should not work without specifying the subfolder
           _a											=						AutoImageProcessor.from_pretrained('''hf-internal-testing/stable-diffusion-all-variants''' )

      _a											=						AutoImageProcessor.from_pretrained(
          '''hf-internal-testing/stable-diffusion-all-variants'''				,     subfolder='''feature_extractor''' )

      self.assertIsNotNone(A )






@is_staging_test
class __A    (						unittest.TestCase		):



 '''simple docstring'''







 @classmethod
 def       a__						(cls )					->  Any:


      """simple docstring"""



      _a											=						TOKEN
      HfFolder.save_token(A )



 @classmethod
 def       a__						(cls )					->  Union[str, Any]:


      """simple docstring"""



      try:
           delete_repo(token=cls._token				,     repo_id='''test-image-processor''' )
      except HTTPError:
           pass

      try:
           delete_repo(token=cls._token				,     repo_id='''valid_org/test-image-processor-org''' )
      except HTTPError:
           pass

      try:
           delete_repo(token=cls._token				,     repo_id='''test-dynamic-image-processor''' )
      except HTTPError:
           pass



 def       a__						(self )					->  str:


      """simple docstring"""



      _a											=						ViTImageProcessor.from_pretrained(A )
      image_processor.push_to_hub('''test-image-processor'''				,     use_auth_token=self._token )

      _a											=						ViTImageProcessor.from_pretrained(f'''{USER}/test-image-processor''' )
      for k, v in image_processor.__dict__.items():
           self.assertEqual(A				,     getattr(A				,     A ) )

      # Reset repo
      delete_repo(token=self._token				,     repo_id='''test-image-processor''' )

      # Push to hub via save_pretrained
      with tempfile.TemporaryDirectory() as tmp_dir:
           image_processor.save_pretrained(
               A				,     repo_id='''test-image-processor'''				,     push_to_hub=A				,     use_auth_token=self._token )

      _a											=						ViTImageProcessor.from_pretrained(f'''{USER}/test-image-processor''' )
      for k, v in image_processor.__dict__.items():
           self.assertEqual(A				,     getattr(A				,     A ) )



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


      """simple docstring"""



      _a											=						ViTImageProcessor.from_pretrained(A )
      image_processor.push_to_hub('''valid_org/test-image-processor'''				,     use_auth_token=self._token )

      _a											=						ViTImageProcessor.from_pretrained('''valid_org/test-image-processor''' )
      for k, v in image_processor.__dict__.items():
           self.assertEqual(A				,     getattr(A				,     A ) )

      # Reset repo
      delete_repo(token=self._token				,     repo_id='''valid_org/test-image-processor''' )

      # Push to hub via save_pretrained
      with tempfile.TemporaryDirectory() as tmp_dir:
           image_processor.save_pretrained(
               A				,     repo_id='''valid_org/test-image-processor-org'''				,     push_to_hub=A				,     use_auth_token=self._token )

      _a											=						ViTImageProcessor.from_pretrained('''valid_org/test-image-processor-org''' )
      for k, v in image_processor.__dict__.items():
           self.assertEqual(A				,     getattr(A				,     A ) )



 def       a__						(self )					->  Union[str, Any]:


      """simple docstring"""



      CustomImageProcessor.register_for_auto_class()
      _a											=						CustomImageProcessor.from_pretrained(A )

      image_processor.push_to_hub('''test-dynamic-image-processor'''				,     use_auth_token=self._token )

      # This has added the proper auto_map field to the config
      self.assertDictEqual(
          image_processor.auto_map				,     {'''AutoImageProcessor''': '''custom_image_processing.CustomImageProcessor'''}				,     )

      _a											=						AutoImageProcessor.from_pretrained(
          f'''{USER}/test-dynamic-image-processor'''				,     trust_remote_code=A )
      # Can't make an isinstance check because the new_image_processor is from the CustomImageProcessor class of a dynamic module
      self.assertEqual(new_image_processor.__class__.__name__				,     '''CustomImageProcessor''' )



