


'''simple docstring'''






from __future__ import annotations

from typing import Dict

from ...configuration_utils import PretrainedConfig


__UpperCAmelCase       							=				{
    '''susnato/ernie-m-base_pytorch''': '''https://huggingface.co/susnato/ernie-m-base_pytorch/blob/main/config.json''',
    '''susnato/ernie-m-large_pytorch''': '''https://huggingface.co/susnato/ernie-m-large_pytorch/blob/main/config.json''',
}




class 						a__							(				a__    ):





							'''simple docstring'''






							lowercase__     :  Dict      		= "ernie_m"
							lowercase__     :  Dict[str, str]      		= {"dropout": "classifier_dropout", "num_classes": "num_labels"}







							def __init__(						self   ,       lowerCamelCase_ = 25_00_02   ,       lowerCamelCase_ = 7_68   ,       lowerCamelCase_ = 12   ,       lowerCamelCase_ = 12   ,       lowerCamelCase_ = 30_72   ,       lowerCamelCase_ = "gelu"   ,       lowerCamelCase_ = 0.1   ,       lowerCamelCase_ = 0.1   ,       lowerCamelCase_ = 5_14   ,       lowerCamelCase_ = 0.02   ,       lowerCamelCase_ = 1   ,       lowerCamelCase_ = 1e-05   ,       lowerCamelCase_=None   ,       lowerCamelCase_=False   ,       lowerCamelCase_=0.0   ,       **lowerCamelCase_   ,       )			->				str:
														super().__init__(pad_token_id=lowerCamelCase_   ,       **lowerCamelCase_  )
														lowerCAmelCase__			  =      vocab_size
														lowerCAmelCase__			  =      hidden_size
														lowerCAmelCase__			  =      num_hidden_layers
														lowerCAmelCase__			  =      num_attention_heads
														lowerCAmelCase__			  =      intermediate_size
														lowerCAmelCase__			  =      hidden_act
														lowerCAmelCase__			  =      hidden_dropout_prob
														lowerCAmelCase__			  =      attention_probs_dropout_prob
														lowerCAmelCase__			  =      max_position_embeddings
														lowerCAmelCase__			  =      initializer_range
														lowerCAmelCase__			  =      layer_norm_eps
														lowerCAmelCase__			  =      classifier_dropout
														lowerCAmelCase__			  =      is_decoder
														lowerCAmelCase__			  =      act_dropout





'''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


UpperCamelCase_    	=				get_tests_dir("fixtures")






class 							_a				(			unittest.TestCase ):





       '''simple docstring'''






       def        UpperCamelCase_							(      self  ):







             '''simple docstring'''







             SCREAMING_SNAKE_CASE   :      Optional[int]    					=						mock.Mock()
             SCREAMING_SNAKE_CASE   :      List[Any]    					=						500
             SCREAMING_SNAKE_CASE   :      Optional[Any]    					=						{}
             SCREAMING_SNAKE_CASE   :      Any    					=						HTTPError
             SCREAMING_SNAKE_CASE   :      Any    					=						{}

             # Download this model to make sure it's in the cache.
             SCREAMING_SNAKE_CASE   :      str    					=						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:
                   SCREAMING_SNAKE_CASE   :      List[Any]    					=						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  ):







             '''simple docstring'''







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







       def        UpperCamelCase_							(      self  ):







             '''simple docstring'''







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

             SCREAMING_SNAKE_CASE   :      Dict    					=						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        UpperCamelCase_							(      cls  ):







             '''simple docstring'''







             SCREAMING_SNAKE_CASE   :      Tuple    					=						TOKEN
             HfFolder.save_token(A  )







       @classmethod
       def        UpperCamelCase_							(      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        UpperCamelCase_							(      self  ):







             '''simple docstring'''







             SCREAMING_SNAKE_CASE   :      Optional[Any]    					=						ViTImageProcessor.from_pretrained(A  )
             image_processor.push_to_hub('test-image-processor',							use_auth_token=self._token  )

             SCREAMING_SNAKE_CASE   :      int    					=						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  )

             SCREAMING_SNAKE_CASE   :      List[str]    					=						ViTImageProcessor.from_pretrained(F"{USER}/test-image-processor"  )
             for k, v in image_processor.__dict__.items():
                   self.assertEqual(A,							getattr(A,							A  )  )







       def        UpperCamelCase_							(      self  ):







             '''simple docstring'''







             SCREAMING_SNAKE_CASE   :      List[Any]    					=						ViTImageProcessor.from_pretrained(A  )
             image_processor.push_to_hub('valid_org/test-image-processor',							use_auth_token=self._token  )

             SCREAMING_SNAKE_CASE   :      str    					=						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  )

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







       def        UpperCamelCase_							(      self  ):







             '''simple docstring'''







             CustomImageProcessor.register_for_auto_class()
             SCREAMING_SNAKE_CASE   :      Tuple    					=						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'},							)

             SCREAMING_SNAKE_CASE   :      Optional[int]    					=						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'  )


