



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


_snake_case		=  get_tests_dir("fixtures")



class   UpperCAmelCase_    (       unittest.TestCase):







							def    snake_case__      (   self):

														'''simple docstring'''

														_lowerCAmelCase     :							Optional[Any]    =    mock.Mock()
														_lowerCAmelCase     :							int    =    500
														_lowerCAmelCase     :							Tuple    =    {}
														_lowerCAmelCase     :							str    =    HTTPError
														_lowerCAmelCase     :							Union[str, Any]    =    {}

														# Download this model to make sure it's in the cache.
														_lowerCAmelCase     :							Tuple    =    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:
																					_lowerCAmelCase     :							Optional[int]    =    ViTImageProcessor.from_pretrained("hf-internal-testing/tiny-random-vit")
																					# This check we did call the fake head request
																					mock_head.assert_called()







							def    snake_case__      (   self):

														'''simple docstring'''

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







							def    snake_case__      (   self):

														'''simple docstring'''

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

														_lowerCAmelCase     :							Optional[Any]    =    AutoImageProcessor.from_pretrained(
														    "hf-internal-testing/stable-diffusion-all-variants",			subfolder="feature_extractor")

														self.assertIsNotNone(__a)



@is_staging_test
class   UpperCAmelCase_    (       unittest.TestCase):







							@classmethod
							def    snake_case__      (   cls):

														'''simple docstring'''

														_lowerCAmelCase     :							Union[str, Any]    =    TOKEN
														HfFolder.save_token(__a)







							@classmethod
							def    snake_case__      (   cls):

														'''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    snake_case__      (   self):

														'''simple docstring'''

														_lowerCAmelCase     :							Optional[int]    =    ViTImageProcessor.from_pretrained(__a)
														image_processor.push_to_hub("test-image-processor",			use_auth_token=self._token)

														_lowerCAmelCase     :							str    =    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)

														_lowerCAmelCase     :							Optional[int]    =    ViTImageProcessor.from_pretrained(f"{USER}/test-image-processor")
														for k, v in image_processor.__dict__.items():
																					self.assertEqual(__a,			getattr(__a,			__a))







							def    snake_case__      (   self):

														'''simple docstring'''

														_lowerCAmelCase     :							Any    =    ViTImageProcessor.from_pretrained(__a)
														image_processor.push_to_hub("valid_org/test-image-processor",			use_auth_token=self._token)

														_lowerCAmelCase     :							Tuple    =    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)

														_lowerCAmelCase     :							Optional[int]    =    ViTImageProcessor.from_pretrained("valid_org/test-image-processor-org")
														for k, v in image_processor.__dict__.items():
																					self.assertEqual(__a,			getattr(__a,			__a))







							def    snake_case__      (   self):

														'''simple docstring'''

														CustomImageProcessor.register_for_auto_class()
														_lowerCAmelCase     :							List[str]    =    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"},			)

														_lowerCAmelCase     :							Tuple    =    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")





'''simple docstring'''




# Author: OMKAR PATHAK, Nwachukwu Chidiebere

# Use a Python dictionary to construct the graph.
from __future__ import annotations

from pprint import pformat
from typing import Generic, TypeVar

lowerCamelCase							:str				    =					TypeVar('''T''')







class 	_lowerCAmelCase							(			Generic[T] ):


	def __init__(self       ,      lowercase = True							):
				A_	:						dict[T, list[T]]	=     {}  # dictionary of lists
				A_	:						Any	=     directed


	def     _a	(self       ,      lowercase       ,      lowercase							):

				if not self.directed:  # For undirected graphs
							# if both source vertex and destination vertex are both present in the
							# adjacency list, add destination vertex to source vertex list of adjacent
							# vertices and add source vertex to destination vertex list of adjacent
							# vertices.
							if source_vertex in self.adj_list and destination_vertex in self.adj_list:
										self.adj_list[source_vertex].append(lowercase							)
										self.adj_list[destination_vertex].append(lowercase							)
							# if only source vertex is present in adjacency list, add destination vertex
							# to source vertex list of adjacent vertices, then create a new vertex with
							# destination vertex as key and assign a list containing the source vertex
							# as it's first adjacent vertex.
							elif source_vertex in self.adj_list:
										self.adj_list[source_vertex].append(lowercase							)
										A_	:						Dict	=     [source_vertex]
							# if only destination vertex is present in adjacency list, add source vertex
							# to destination vertex list of adjacent vertices, then create a new vertex
							# with source vertex as key and assign a list containing the source vertex
							# as it's first adjacent vertex.
							elif destination_vertex in self.adj_list:
										self.adj_list[destination_vertex].append(lowercase							)
										A_	:						int	=     [destination_vertex]
							# if both source vertex and destination vertex are not present in adjacency
							# list, create a new vertex with source vertex as key and assign a list
							# containing the destination vertex as it's first adjacent vertex also
							# create a new vertex with destination vertex as key and assign a list
							# containing the source vertex as it's first adjacent vertex.
							else:
										A_	:						Optional[Any]	=     [destination_vertex]
										A_	:						Tuple	=     [source_vertex]
				else:  # For directed graphs
							# if both source vertex and destination vertex are present in adjacency
							# list, add destination vertex to source vertex list of adjacent vertices.
							if source_vertex in self.adj_list and destination_vertex in self.adj_list:
										self.adj_list[source_vertex].append(lowercase							)
							# if only source vertex is present in adjacency list, add destination
							# vertex to source vertex list of adjacent vertices and create a new vertex
							# with destination vertex as key, which has no adjacent vertex
							elif source_vertex in self.adj_list:
										self.adj_list[source_vertex].append(lowercase							)
										A_	:						Tuple	=     []
							# if only destination vertex is present in adjacency list, create a new
							# vertex with source vertex as key and assign a list containing destination
							# vertex as first adjacent vertex
							elif destination_vertex in self.adj_list:
										A_	:						Tuple	=     [destination_vertex]
							# if both source vertex and destination vertex are not present in adjacency
							# list, create a new vertex with source vertex as key and a list containing
							# destination vertex as it's first adjacent vertex. Then create a new vertex
							# with destination vertex as key, which has no adjacent vertex
							else:
										A_	:						int	=     [destination_vertex]
										A_	:						List[str]	=     []

				return self


	def __repr__(self							):
				return pformat(self.adj_list							)