




'''simple docstring'''


import json
import sys
import tempfile
import unittest
from pathlib import Path

import transformers
from transformers import (
    CONFIG_MAPPING,
    IMAGE_PROCESSOR_MAPPING,
    AutoConfig,
    AutoImageProcessor,
    CLIPConfig,
    CLIPImageProcessor,
)
from transformers.testing_utils import DUMMY_UNKNOWN_IDENTIFIER


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

from test_module.custom_configuration import CustomConfig  # noqa E402
from test_module.custom_image_processing import CustomImageProcessor  # noqa E402

class      A       (						unittest.TestCase       ):







							def   __lowerCAmelCase     (    self			:    Optional[Any]   )     ->				Optional[Any]:


														"""simple docstring"""


														_a      	=							0







							def   __lowerCAmelCase     (    self			:    str   )     ->				str:


														"""simple docstring"""


														_a      	=							AutoImageProcessor.from_pretrained('''openai/clip-vit-base-patch32'''   )
														self.assertIsInstance(lowerCAmelCase_				,     lowerCAmelCase_   )







							def   __lowerCAmelCase     (    self			:    List[str]   )     ->				Optional[int]:


														"""simple docstring"""


														with tempfile.TemporaryDirectory() as tmpdirname:
																					_a      	=							Path(lowerCAmelCase_   ) / '''preprocessor_config.json'''
																					_a      	=							Path(lowerCAmelCase_   ) / '''config.json'''
																					json.dump(
																					    {'''image_processor_type''': '''CLIPImageProcessor''', '''processor_class''': '''CLIPProcessor'''}				,     open(lowerCAmelCase_				,     '''w'''   )				,     )
																					json.dump({'''model_type''': '''clip'''}				,     open(lowerCAmelCase_				,     '''w'''   )   )

																					_a      	=							AutoImageProcessor.from_pretrained(lowerCAmelCase_   )
																					self.assertIsInstance(lowerCAmelCase_				,     lowerCAmelCase_   )







							def   __lowerCAmelCase     (    self			:    List[str]   )     ->				Any:


														"""simple docstring"""


														with tempfile.TemporaryDirectory() as tmpdirname:
																					_a      	=							Path(lowerCAmelCase_   ) / '''preprocessor_config.json'''
																					_a      	=							Path(lowerCAmelCase_   ) / '''config.json'''
																					json.dump(
																					    {'''feature_extractor_type''': '''CLIPFeatureExtractor''', '''processor_class''': '''CLIPProcessor'''}				,     open(lowerCAmelCase_				,     '''w'''   )				,     )
																					json.dump({'''model_type''': '''clip'''}				,     open(lowerCAmelCase_				,     '''w'''   )   )

																					_a      	=							AutoImageProcessor.from_pretrained(lowerCAmelCase_   )
																					self.assertIsInstance(lowerCAmelCase_				,     lowerCAmelCase_   )







							def   __lowerCAmelCase     (    self			:    Any   )     ->				List[str]:


														"""simple docstring"""


														with tempfile.TemporaryDirectory() as tmpdirname:
																					_a      	=							CLIPConfig()

																					# Create a dummy config file with image_proceesor_type
																					_a      	=							Path(lowerCAmelCase_   ) / '''preprocessor_config.json'''
																					_a      	=							Path(lowerCAmelCase_   ) / '''config.json'''
																					json.dump(
																					    {'''image_processor_type''': '''CLIPImageProcessor''', '''processor_class''': '''CLIPProcessor'''}				,     open(lowerCAmelCase_				,     '''w'''   )				,     )
																					json.dump({'''model_type''': '''clip'''}				,     open(lowerCAmelCase_				,     '''w'''   )   )

																					# remove image_processor_type to make sure config.json alone is enough to load image processor locally
																					_a      	=							AutoImageProcessor.from_pretrained(lowerCAmelCase_   ).to_dict()

																					config_dict.pop('''image_processor_type'''   )
																					_a      	=							CLIPImageProcessor(**lowerCAmelCase_   )

																					# save in new folder
																					model_config.save_pretrained(lowerCAmelCase_   )
																					config.save_pretrained(lowerCAmelCase_   )

																					_a      	=							AutoImageProcessor.from_pretrained(lowerCAmelCase_   )

																					# make sure private variable is not incorrectly saved
																					_a      	=							json.loads(config.to_json_string()   )
																					self.assertTrue('''_processor_class''' not in dict_as_saved   )

														self.assertIsInstance(lowerCAmelCase_				,     lowerCAmelCase_   )







							def   __lowerCAmelCase     (    self			:    Tuple   )     ->				Dict:


														"""simple docstring"""


														with tempfile.TemporaryDirectory() as tmpdirname:
																					_a      	=							Path(lowerCAmelCase_   ) / '''preprocessor_config.json'''
																					json.dump(
																					    {'''image_processor_type''': '''CLIPImageProcessor''', '''processor_class''': '''CLIPProcessor'''}				,     open(lowerCAmelCase_				,     '''w'''   )				,     )

																					_a      	=							AutoImageProcessor.from_pretrained(lowerCAmelCase_   )
																					self.assertIsInstance(lowerCAmelCase_				,     lowerCAmelCase_   )







							def   __lowerCAmelCase     (    self			:    int   )     ->				str:


														"""simple docstring"""


														with self.assertRaisesRegex(
														    lowerCAmelCase_				,     '''clip-base is not a local folder and is not a valid model identifier'''   ):
																					_a      	=							AutoImageProcessor.from_pretrained('''clip-base'''   )







							def   __lowerCAmelCase     (    self			:    Optional[int]   )     ->				int:


														"""simple docstring"""


														with self.assertRaisesRegex(
														    lowerCAmelCase_				,     R'''aaaaaa is not a valid git identifier \(branch name, tag name or commit id\)'''   ):
																					_a      	=							AutoImageProcessor.from_pretrained(lowerCAmelCase_				,     revision='''aaaaaa'''   )







							def   __lowerCAmelCase     (    self			:    List[str]   )     ->				Any:


														"""simple docstring"""


														with self.assertRaisesRegex(
														    lowerCAmelCase_				,     '''hf-internal-testing/config-no-model does not appear to have a file named preprocessor_config.json.'''				,     ):
																					_a      	=							AutoImageProcessor.from_pretrained('''hf-internal-testing/config-no-model'''   )







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


														"""simple docstring"""


														with self.assertRaises(lowerCAmelCase_   ):
																					_a      	=							AutoImageProcessor.from_pretrained('''hf-internal-testing/test_dynamic_image_processor'''   )
														# If remote code is disabled, we can't load this config.
														with self.assertRaises(lowerCAmelCase_   ):
																					_a      	=							AutoImageProcessor.from_pretrained(
																					    '''hf-internal-testing/test_dynamic_image_processor'''				,     trust_remote_code=lowerCAmelCase_   )

														_a      	=							AutoImageProcessor.from_pretrained(
														    '''hf-internal-testing/test_dynamic_image_processor'''				,     trust_remote_code=lowerCAmelCase_   )
														self.assertEqual(image_processor.__class__.__name__				,     '''NewImageProcessor'''   )

														# Test image processor can be reloaded.
														with tempfile.TemporaryDirectory() as tmp_dir:
																					image_processor.save_pretrained(lowerCAmelCase_   )
																					_a      	=							AutoImageProcessor.from_pretrained(lowerCAmelCase_				,     trust_remote_code=lowerCAmelCase_   )
														self.assertEqual(reloaded_image_processor.__class__.__name__				,     '''NewImageProcessor'''   )







							def   __lowerCAmelCase     (    self			:    List[str]   )     ->				Any:


														"""simple docstring"""


														try:
																					AutoConfig.register('''custom'''				,     lowerCAmelCase_   )
																					AutoImageProcessor.register(lowerCAmelCase_				,     lowerCAmelCase_   )
																					# Trying to register something existing in the Transformers library will raise an error
																					with self.assertRaises(lowerCAmelCase_   ):
																												AutoImageProcessor.register(lowerCAmelCase_				,     lowerCAmelCase_   )

																					with tempfile.TemporaryDirectory() as tmpdirname:
																												_a      	=							Path(lowerCAmelCase_   ) / '''preprocessor_config.json'''
																												_a      	=							Path(lowerCAmelCase_   ) / '''config.json'''
																												json.dump(
																												    {'''feature_extractor_type''': '''CLIPFeatureExtractor''', '''processor_class''': '''CLIPProcessor'''}				,     open(lowerCAmelCase_				,     '''w'''   )				,     )
																												json.dump({'''model_type''': '''clip'''}				,     open(lowerCAmelCase_				,     '''w'''   )   )

																												_a      	=							CustomImageProcessor.from_pretrained(lowerCAmelCase_   )

																					# Now that the config is registered, it can be used as any other config with the auto-API
																					with tempfile.TemporaryDirectory() as tmp_dir:
																												image_processor.save_pretrained(lowerCAmelCase_   )
																												_a      	=							AutoImageProcessor.from_pretrained(lowerCAmelCase_   )
																												self.assertIsInstance(lowerCAmelCase_				,     lowerCAmelCase_   )

														finally:
																					if "custom" in CONFIG_MAPPING._extra_content:
																												del CONFIG_MAPPING._extra_content["custom"]
																					if CustomConfig in IMAGE_PROCESSOR_MAPPING._extra_content:
																												del IMAGE_PROCESSOR_MAPPING._extra_content[CustomConfig]







							def   __lowerCAmelCase     (    self			:    Optional[int]   )     ->				Any:


														"""simple docstring"""


														class      A       (						_a       ):
																					lowercase_							     =							True

														try:
																					AutoConfig.register('''custom'''				,     lowerCAmelCase_   )
																					AutoImageProcessor.register(lowerCAmelCase_				,     lowerCAmelCase_   )
																					# If remote code is not set, the default is to use local
																					_a      	=							AutoImageProcessor.from_pretrained('''hf-internal-testing/test_dynamic_image_processor'''   )
																					self.assertEqual(image_processor.__class__.__name__				,     '''NewImageProcessor'''   )
																					self.assertTrue(image_processor.is_local   )

																					# If remote code is disabled, we load the local one.
																					_a      	=							AutoImageProcessor.from_pretrained(
																					    '''hf-internal-testing/test_dynamic_image_processor'''				,     trust_remote_code=lowerCAmelCase_   )
																					self.assertEqual(image_processor.__class__.__name__				,     '''NewImageProcessor'''   )
																					self.assertTrue(image_processor.is_local   )

																					# If remote is enabled, we load from the Hub
																					_a      	=							AutoImageProcessor.from_pretrained(
																					    '''hf-internal-testing/test_dynamic_image_processor'''				,     trust_remote_code=lowerCAmelCase_   )
																					self.assertEqual(image_processor.__class__.__name__				,     '''NewImageProcessor'''   )
																					self.assertTrue(not hasattr(lowerCAmelCase_				,     '''is_local'''   )   )

														finally:
																					if "custom" in CONFIG_MAPPING._extra_content:
																												del CONFIG_MAPPING._extra_content["custom"]
																					if CustomConfig in IMAGE_PROCESSOR_MAPPING._extra_content:
																												del IMAGE_PROCESSOR_MAPPING._extra_content[CustomConfig]








"""simple docstring"""



from collections import namedtuple

import requests
from lxml import html  # type: ignore

a_					=     namedtuple("""covid_data""", """cases deaths recovered""")







def 						__lowercase	(  snake_case_    :    str = "https://www.worldometers.info/coronavirus/"		)  ->covid_data:



    '''simple docstring'''







    __A       :		List[str]							=	'''//div[@class = "maincounter-number"]/span/text()'''
    return covid_data(*html.fromstring(requests.get(snake_case_		).content		).xpath(snake_case_		)		)


a_					=     """Total COVID-19 cases in the world: {}
Total deaths due to COVID-19 in the world: {}
Total COVID-19 patients recovered in the world: {}"""




print(fmt.format(*covid_stats()))




