


'''simple docstring'''






from __future__ import annotations

from sys import maxsize
from typing import Generic, TypeVar

a_   :      Optional[Any]				    =      TypeVar("T")






def 		_A			(lowerCAmelCase__					:int						)				->					int:




     '''simple docstring'''



     return (position - 1) // 2






def 		_A			(lowerCAmelCase__					:int						)				->					int:




     '''simple docstring'''



     return (2 * position) + 1






def 		_A			(lowerCAmelCase__					:int						)				->					int:




     '''simple docstring'''



     return (2 * position) + 2




class 	a       (       Generic[T]    ):
 def __init__(	self  )   ->							None:
      _a      =							[]
      _a      =							{}
      _a      =							0
 def __len__(	self  )   ->							int:
      return self.elements
 def __repr__(	self  )   ->							str:
      return str(self.heap  )
 def 							__UpperCAmelCase						(	self  )   ->							bool:
      # Check if the priority queue is empty
      return self.elements == 0
 def 							__UpperCAmelCase						(	self ,			__magic_name__ ,			__magic_name__  )   ->							None:
      # Add an element with given priority to the queue
      self.heap.append((elem, weight)  )
      _a      =							self.elements
      self.elements += 1
      self._bubble_up(__magic_name__  )
 def 							__UpperCAmelCase						(	self  )   ->							T:
      # Remove and return the element with lowest weight (highest priority)
      if self.elements > 1:
           self._swap_nodes(0 ,			self.elements - 1  )
      _a ,				_a      =							self.heap.pop()
      del self.position_map[elem]
      self.elements -= 1
      if self.elements > 0:
           _a ,				_a      =							self.heap[0]
           self._bubble_down(__magic_name__  )
      return elem
 def 							__UpperCAmelCase						(	self ,			__magic_name__ ,			__magic_name__  )   ->							None:
      # Update the weight of the given key
      _a      =							self.position_map[elem]
      _a      =							(elem, weight)
      if position > 0:
           _a      =							get_parent_position(__magic_name__  )
           _a ,				_a      =							self.heap[parent_position]
           if parent_weight > weight:
                self._bubble_up(__magic_name__  )
           else:
                self._bubble_down(__magic_name__  )
      else:
           self._bubble_down(__magic_name__  )
 def 							__UpperCAmelCase						(	self ,			__magic_name__  )   ->							None:
      # Place a node at the proper position (upward movement) [to be used internally
      # only]
      _a      =							self.position_map[elem]
      if curr_pos == 0:
           return None
      _a      =							get_parent_position(__magic_name__  )
      _a ,				_a      =							self.heap[curr_pos]
      _a ,				_a      =							self.heap[parent_position]
      if parent_weight > weight:
           self._swap_nodes(__magic_name__ ,			__magic_name__  )
           return self._bubble_up(__magic_name__  )
      return None
 def 							__UpperCAmelCase						(	self ,			__magic_name__  )   ->							None:
      # Place a node at the proper position (downward movement) [to be used
      # internally only]
      _a      =							self.position_map[elem]
      _a ,				_a      =							self.heap[curr_pos]
      _a      =							get_child_left_position(__magic_name__  )
      _a      =							get_child_right_position(__magic_name__  )
      if child_left_position < self.elements and child_right_position < self.elements:
           _a ,				_a      =							self.heap[child_left_position]
           _a ,				_a      =							self.heap[child_right_position]
           if child_right_weight < child_left_weight and child_right_weight < weight:
                self._swap_nodes(__magic_name__ ,			__magic_name__  )
                return self._bubble_down(__magic_name__  )
      if child_left_position < self.elements:
           _a ,				_a      =							self.heap[child_left_position]
           if child_left_weight < weight:
                self._swap_nodes(__magic_name__ ,			__magic_name__  )
                return self._bubble_down(__magic_name__  )
      else:
           return None
      if child_right_position < self.elements:
           _a ,				_a      =							self.heap[child_right_position]
           if child_right_weight < weight:
                self._swap_nodes(__magic_name__ ,			__magic_name__  )
                return self._bubble_down(__magic_name__  )
      return None




 def 							__UpperCAmelCase						(	self ,			__magic_name__ ,			__magic_name__  )   ->							None:
      # Swap the nodes at the given positions
      _a      =							self.heap[nodea_pos][0]
      _a      =							self.heap[nodea_pos][0]
      _a ,				_a      =							(
          self.heap[nodea_pos],
          self.heap[nodea_pos],
      )
      _a      =							nodea_pos
      _a      =							nodea_pos





class 	a       (       Generic[T]    ):
 def __init__(	self  )   ->							None:
      _a      =							{}
      _a      =							0
 def __repr__(	self  )   ->							str:
      return str(self.connections  )
 def __len__(	self  )   ->							int:
      return self.nodes
 def 							__UpperCAmelCase						(	self ,			__magic_name__  )   ->							None:
      # Add a node in the graph if it is not in the graph
      if node not in self.connections:
           _a      =							{}
           self.nodes += 1




 def 							__UpperCAmelCase						(	self ,			__magic_name__ ,			__magic_name__ ,			__magic_name__  )   ->							None:
      # Add an edge between 2 nodes in the graph
      self.add_node(__magic_name__  )
      self.add_node(__magic_name__  )
      _a      =							weight
      _a      =							weight






def 		_A			(lowerCAmelCase__					:GraphUndirectedWeighted[T]			,  )				->					tuple[dict[T, int], dict[T, T | None]]:




     '''simple docstring'''



     _a      =							{node: maxsize for node in graph.connections}
     _a      =							{node: None for node in graph.connections}

     _a      =							MinPriorityQueue()
     for node, weight in dist.items():
          priority_queue.push(lowerCAmelCase__			,  lowerCAmelCase__						)

     if priority_queue.is_empty():
          return dist, parent

     # initialization
     _a      =							priority_queue.extract_min()
     _a      =							0
     for neighbour in graph.connections[node]:
          if dist[neighbour] > dist[node] + graph.connections[node][neighbour]:
               _a      =							dist[node] + graph.connections[node][neighbour]
               priority_queue.update_key(lowerCAmelCase__			,  dist[neighbour]						)
               _a      =							node

    # running prim's algorithm
     while not priority_queue.is_empty():
          _a      =							priority_queue.extract_min()
          for neighbour in graph.connections[node]:
               if dist[neighbour] > dist[node] + graph.connections[node][neighbour]:
                    _a      =							dist[node] + graph.connections[node][neighbour]
                    priority_queue.update_key(lowerCAmelCase__			,  dist[neighbour]						)
                    _a      =							node
     return dist, parent





'''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


a_   :      Tuple				    =      get_tests_dir("fixtures")




class 	a       (       unittest.TestCase    ):
 def 							__UpperCAmelCase						(	self  )   ->							str:
      # A mock response for an HTTP head request to emulate server down
      _a      =							mock.Mock()
      _a      =							5_00
      _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=__magic_name__  ) 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 							__UpperCAmelCase						(	self  )   ->							Optional[int]:
      # This test is for deprecated behavior and can be removed in v5
      _a      =							ViTImageProcessor.from_pretrained(
          'https://huggingface.co/hf-internal-testing/tiny-random-vit/resolve/main/preprocessor_config.json'  )




 def 							__UpperCAmelCase						(	self  )   ->							Dict:
      with self.assertRaises(__magic_name__  ):
           # 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(__magic_name__  )





@is_staging_test
class 	a       (       unittest.TestCase    ):
 @classmethod
 def 							__UpperCAmelCase						(	cls  )   ->							Dict:
      _a      =							TOKEN
      HfFolder.save_token(__magic_name__  )
 @classmethod
 def 							__UpperCAmelCase						(	cls  )   ->							List[Any]:
      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 							__UpperCAmelCase						(	self  )   ->							str:
      _a      =							ViTImageProcessor.from_pretrained(__magic_name__  )
      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(__magic_name__ ,			getattr(__magic_name__ ,			__magic_name__  )  )

      # 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(
               __magic_name__ ,			repo_id='test-image-processor' ,			push_to_hub=__magic_name__ ,			use_auth_token=self._token  )

      _a      =							ViTImageProcessor.from_pretrained(f'{USER}/test-image-processor'  )
      for k, v in image_processor.__dict__.items():
           self.assertEqual(__magic_name__ ,			getattr(__magic_name__ ,			__magic_name__  )  )
 def 							__UpperCAmelCase						(	self  )   ->							Optional[Any]:
      _a      =							ViTImageProcessor.from_pretrained(__magic_name__  )
      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(__magic_name__ ,			getattr(__magic_name__ ,			__magic_name__  )  )

      # 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(
               __magic_name__ ,			repo_id='valid_org/test-image-processor-org' ,			push_to_hub=__magic_name__ ,			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(__magic_name__ ,			getattr(__magic_name__ ,			__magic_name__  )  )




 def 							__UpperCAmelCase						(	self  )   ->							Any:
      CustomImageProcessor.register_for_auto_class()
      _a      =							CustomImageProcessor.from_pretrained(__magic_name__  )

      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=__magic_name__  )
      # 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'  )

