


import copy
import inspect

from transformers.testing_utils import require_torch, torch_device
from transformers.utils.backbone_utils import BackboneType


@require_torch
class       __lowerCAmelCase       :






  """simple docstring"""





  _SCREAMING_SNAKE_CASE						      =    ()
  _SCREAMING_SNAKE_CASE						      =    True



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




     """simple docstring"""
     snake_case_         =   self.config_class

     # test default config
     snake_case_         =   config_class()
     self.assertIsNotNone(_lowerCAmelCase					)
     snake_case_         =   ["stem"] + [F'''stage{idx}''' for idx in range(1      ,			len(config.depths					) + 1					)]
     self.assertEqual(config.stage_names      ,			_lowerCAmelCase					)
     self.assertTrue(set(config.out_features					).issubset(set(config.stage_names					)					)					)

     # Test out_features and out_indices are correctly set
     # out_features and out_indices both None
     snake_case_         =   config_class(out_features=_lowerCAmelCase      ,			out_indices=_lowerCAmelCase					)
     self.assertEqual(config.out_features      ,			[config.stage_names[-1]]					)
     self.assertEqual(config.out_indices      ,			[len(config.stage_names					) - 1]					)

     # out_features and out_indices both set
     snake_case_         =   config_class(out_features=["stem", "stage1"]      ,			out_indices=[0, 1]					)
     self.assertEqual(config.out_features      ,			["stem", "stage1"]					)
     self.assertEqual(config.out_indices      ,			[0, 1]					)

     # Only out_features set
     snake_case_         =   config_class(out_features=["stage1", "stage3"]					)
     self.assertEqual(config.out_features      ,			["stage1", "stage3"]					)
     self.assertEqual(config.out_indices      ,			[1, 3]					)

     # Only out_indices set
     snake_case_         =   config_class(out_indices=[0, 2]					)
     self.assertEqual(config.out_features      ,			[config.stage_names[0], config.stage_names[2]]					)
     self.assertEqual(config.out_indices      ,			[0, 2]					)

     # Error raised when out_indices do not correspond to out_features
     with self.assertRaises(_lowerCAmelCase					):
        snake_case_         =   config_class(out_features=["stage1", "stage2"]      ,			out_indices=[0, 2]					)



  def    lowerCAmelCase__					(       self    :    str					)				->	int:




     """simple docstring"""
     snake_case_      ,      snake_case_         =   self.model_tester.prepare_config_and_inputs_for_common()

     for model_class in self.all_model_classes:
        snake_case_         =   model_class(_lowerCAmelCase					)
        snake_case_         =   inspect.signature(model.forward					)
        # signature.parameters is an OrderedDict => so arg_names order is deterministic
        snake_case_         =   [*signature.parameters.keys()]
        snake_case_         =   ["pixel_values"]
        self.assertListEqual(arg_names[:1]      ,			_lowerCAmelCase					)



  def    lowerCAmelCase__					(       self    :    List[Any]					)				->	int:




     """simple docstring"""
     snake_case_      ,      snake_case_         =   self.model_tester.prepare_config_and_inputs_for_common()

     for model_class in self.all_model_classes:
        snake_case_         =   model_class(_lowerCAmelCase					)
        self.assertEqual(len(model.channels					)      ,			len(config.out_features					)					)
        snake_case_         =   model.num_features
        snake_case_         =   [config.stage_names.index(_lowerCAmelCase					) for feat in config.out_features]
        snake_case_         =   [num_features[idx] for idx in out_indices]
        self.assertListEqual(model.channels      ,			_lowerCAmelCase					)

        snake_case_         =   copy.deepcopy(_lowerCAmelCase					)
        snake_case_         =   None
        snake_case_         =   model_class(_lowerCAmelCase					)
        self.assertEqual(len(model.channels					)      ,			1					)
        self.assertListEqual(model.channels      ,			[num_features[-1]]					)

        snake_case_         =   copy.deepcopy(_lowerCAmelCase					)
        snake_case_         =   None
        snake_case_         =   model_class(_lowerCAmelCase					)
        self.assertEqual(len(model.channels					)      ,			1					)
        self.assertListEqual(model.channels      ,			[num_features[-1]]					)



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




     """simple docstring"""
     snake_case_      ,      snake_case_         =   self.model_tester.prepare_config_and_inputs_for_common()

     for model_class in self.all_model_classes:
        snake_case_         =   model_class(_lowerCAmelCase					)
        model.to(_lowerCAmelCase					)
        model.eval()
        snake_case_         =   model(**_lowerCAmelCase					)

        self.assertEqual(len(result.feature_maps					)      ,			len(config.out_features					)					)
        self.assertEqual(len(model.channels					)      ,			len(config.out_features					)					)
        self.assertEqual(len(result.feature_maps					)      ,			len(config.out_indices					)					)
        self.assertEqual(len(model.channels					)      ,			len(config.out_indices					)					)

        # Check output of last stage is taken if out_features=None, out_indices=None
        snake_case_         =   copy.deepcopy(_lowerCAmelCase					)
        snake_case_         =   None
        snake_case_         =   model_class(_lowerCAmelCase					)
        model.to(_lowerCAmelCase					)
        model.eval()
        snake_case_         =   model(**_lowerCAmelCase					)

        self.assertEqual(len(result.feature_maps					)      ,			1					)
        self.assertEqual(len(model.channels					)      ,			1					)

        snake_case_         =   copy.deepcopy(_lowerCAmelCase					)
        snake_case_         =   None
        snake_case_         =   model_class(_lowerCAmelCase					)
        model.to(_lowerCAmelCase					)
        model.eval()
        snake_case_         =   model(**_lowerCAmelCase					)

        self.assertEqual(len(result.feature_maps					)      ,			1					)
        self.assertEqual(len(model.channels					)      ,			1					)

        # Check backbone can be initialized with fresh weights
        snake_case_         =   copy.deepcopy(_lowerCAmelCase					)
        snake_case_         =   False
        snake_case_         =   model_class(_lowerCAmelCase					)
        model.to(_lowerCAmelCase					)
        model.eval()
        snake_case_         =   model(**_lowerCAmelCase					)



  def    lowerCAmelCase__					(       self    :    Tuple					)				->	Optional[Any]:




     """simple docstring"""
     snake_case_      ,      snake_case_         =   self.model_tester.prepare_config_and_inputs_for_common()

     for backbone_class in self.all_model_classes:
        snake_case_         =   backbone_class(_lowerCAmelCase					)

        self.assertTrue(hasattr(_lowerCAmelCase      ,			"backbone_type"					)					)
        self.assertTrue(hasattr(_lowerCAmelCase      ,			"stage_names"					)					)
        self.assertTrue(hasattr(_lowerCAmelCase      ,			"num_features"					)					)
        self.assertTrue(hasattr(_lowerCAmelCase      ,			"out_indices"					)					)
        self.assertTrue(hasattr(_lowerCAmelCase      ,			"out_features"					)					)
        self.assertTrue(hasattr(_lowerCAmelCase      ,			"out_feature_channels"					)					)
        self.assertTrue(hasattr(_lowerCAmelCase      ,			"channels"					)					)

        self.assertIsInstance(backbone.backbone_type      ,			_lowerCAmelCase					)
        # Verify num_features has been initialized in the backbone init
        self.assertIsNotNone(backbone.num_features					)
        self.assertTrue(len(backbone.channels					) == len(backbone.out_indices					)					)
        self.assertTrue(len(backbone.stage_names					) == len(backbone.num_features					)					)
        self.assertTrue(len(backbone.channels					) <= len(backbone.num_features					)					)
        self.assertTrue(len(backbone.out_feature_channels					) == len(backbone.stage_names					)					)



  def    lowerCAmelCase__					(       self    :    List[str]					)				->	Tuple:




     """simple docstring"""
     snake_case_      ,      snake_case_         =   self.model_tester.prepare_config_and_inputs_for_common()
     snake_case_         =   inputs_dict["pixel_values"].shape[0]

     for backbone_class in self.all_model_classes:
        snake_case_         =   backbone_class(_lowerCAmelCase					)
        backbone.to(_lowerCAmelCase					)
        backbone.eval()

        snake_case_         =   backbone(**_lowerCAmelCase					)

        # Test default outputs and verify feature maps
        self.assertIsInstance(outputs.feature_maps      ,			_lowerCAmelCase					)
        self.assertTrue(len(outputs.feature_maps					) == len(backbone.channels					)					)
        for feature_map, n_channels in zip(outputs.feature_maps      ,			backbone.channels					):
           self.assertTrue(feature_map.shape[:2]      ,			(batch_size, n_channels)					)
        self.assertIsNone(outputs.hidden_states					)
        self.assertIsNone(outputs.attentions					)

        # Test output_hidden_states=True
        snake_case_         =   backbone(**_lowerCAmelCase      ,			output_hidden_states=_lowerCAmelCase					)
        self.assertIsNotNone(outputs.hidden_states					)
        self.assertTrue(len(outputs.hidden_states					)      ,			len(backbone.stage_names					)					)
        for hidden_state, n_channels in zip(outputs.hidden_states      ,			backbone.channels					):
           self.assertTrue(hidden_state.shape[:2]      ,			(batch_size, n_channels)					)

        # Test output_attentions=True
        if self.has_attentions:
           snake_case_         =   backbone(**_lowerCAmelCase      ,			output_attentions=_lowerCAmelCase					)
           self.assertIsNotNone(outputs.attentions					)








import os

import requests
from bsa import BeautifulSoup
from fake_useragent import UserAgent

SCREAMING_SNAKE_CASE		:Dict											=       {'''UserAgent''': UserAgent().random}
SCREAMING_SNAKE_CASE		:Dict											=       '''https://www.mywaifulist.moe/random'''



def      _lowerCAmelCase  (							lowerCAmelCase_							:str						,  lowerCAmelCase_							:str							)->None:
   '''simple docstring'''






   snake_case_         =   requests.get(lowerCAmelCase_						,  headers=lowerCAmelCase_							)
   with open(lowerCAmelCase_						,  "wb"							) as file:
      file.write(image.content							)



def      _lowerCAmelCase  (							)->tuple[str, str, str]:
   '''simple docstring'''






   snake_case_         =   BeautifulSoup(requests.get(lowerCAmelCase_						,  headers=lowerCAmelCase_							).text						,  "html.parser"							)
   snake_case_         =   soup.find("meta"						,  attrs={"property": "og:title"}							).attrs["content"]
   snake_case_         =   soup.find("meta"						,  attrs={"property": "og:image"}							).attrs["content"]
   snake_case_         =   soup.find("p"						,  id="description"							).get_text()
   snake_case_      ,      snake_case_         =   os.path.splitext(os.path.basename(lowerCAmelCase_							)							)
   snake_case_         =   title.strip().replace(" "						,  "_"							)
   snake_case_         =   F'''{image_title}{image_extension}'''
   save_image(lowerCAmelCase_						,  lowerCAmelCase_							)
   return (title, description, image_title)


if __name__ == "__main__":
   SCREAMING_SNAKE_CASE						,		SCREAMING_SNAKE_CASE						,		SCREAMING_SNAKE_CASE		:Optional[Any]											=       random_anime_character()
   print(F'''{title}\n\n{desc}\n\nImage saved : {image_title}''')




