


'''simple docstring'''






import json
import os
import shutil
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 AutoConfig, BertConfig, GPTaConfig
from transformers.configuration_utils import PretrainedConfig
from transformers.testing_utils import TOKEN, USER, is_staging_test


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

from test_module.custom_configuration import CustomConfig  # noqa E402


lowercase							={
    'return_dict': False,
    'output_hidden_states': True,
    'output_attentions': True,
    'torchscript': True,
    'torch_dtype': 'float16',
    'use_bfloat16': True,
    'tf_legacy_loss': True,
    'pruned_heads': {'a': 1},
    'tie_word_embeddings': False,
    'is_decoder': True,
    'cross_attention_hidden_size': 128,
    'add_cross_attention': True,
    'tie_encoder_decoder': True,
    'max_length': 50,
    'min_length': 3,
    'do_sample': True,
    'early_stopping': True,
    'num_beams': 3,
    'num_beam_groups': 3,
    'diversity_penalty': 0.5,
    'temperature': 2.0,
    'top_k': 10,
    'top_p': 0.7,
    'typical_p': 0.2,
    'repetition_penalty': 0.8,
    'length_penalty': 0.8,
    'no_repeat_ngram_size': 5,
    'encoder_no_repeat_ngram_size': 5,
    'bad_words_ids': [1, 2, 3],
    'num_return_sequences': 3,
    'chunk_size_feed_forward': 5,
    'output_scores': True,
    'return_dict_in_generate': True,
    'forced_bos_token_id': 2,
    'forced_eos_token_id': 3,
    'remove_invalid_values': True,
    'architectures': ['BertModel'],
    'finetuning_task': 'translation',
    'id2label': {0: 'label'},
    'label2id': {'label': '0'},
    'tokenizer_class': 'BertTokenizerFast',
    'prefix': 'prefix',
    'bos_token_id': 6,
    'pad_token_id': 7,
    'eos_token_id': 8,
    'sep_token_id': 9,
    'decoder_start_token_id': 10,
    'exponential_decay_length_penalty': (5, 1.01),
    'suppress_tokens': [0, 1],
    'begin_suppress_tokens': 2,
    'task_specific_params': {'translation': 'some_params'},
    'problem_type': 'regression',
}






@is_staging_test
class  __magic_name__							(		unittest.TestCase    ):






       @classmethod
       def       lowerCAmelCase		(      cls)						->  Dict:




          '''simple docstring'''
          _UpperCAmelCase       :       Any							   =TOKEN
          HfFolder.save_token(snake_case)






       @classmethod
       def       lowerCAmelCase		(      cls)						->  Union[str, Any]:




          '''simple docstring'''
          try:
             delete_repo(token=cls._token  ,							repo_id='test-config')
          except HTTPError:
             pass

          try:
             delete_repo(token=cls._token  ,							repo_id='valid_org/test-config-org')
          except HTTPError:
             pass

          try:
             delete_repo(token=cls._token  ,							repo_id='test-dynamic-config')
          except HTTPError:
             pass






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




          '''simple docstring'''
          _UpperCAmelCase       :       Tuple							   =BertConfig(
              vocab_size=9_9  ,							hidden_size=3_2  ,							num_hidden_layers=5  ,							num_attention_heads=4  ,							intermediate_size=3_7)
          config.push_to_hub('test-config'  ,							use_auth_token=self._token)

          _UpperCAmelCase       :       Dict							   =BertConfig.from_pretrained(f"{USER}/test-config")
          for k, v in config.to_dict().items():
             if k != "transformers_version":
                self.assertEqual(snake_case  ,							getattr(snake_case  ,							snake_case))

        # Reset repo
          delete_repo(token=self._token  ,							repo_id='test-config')

          # Push to hub via save_pretrained
          with tempfile.TemporaryDirectory() as tmp_dir:
             config.save_pretrained(snake_case  ,							repo_id='test-config'  ,							push_to_hub=snake_case  ,							use_auth_token=self._token)

          _UpperCAmelCase       :       Optional[int]							   =BertConfig.from_pretrained(f"{USER}/test-config")
          for k, v in config.to_dict().items():
             if k != "transformers_version":
                self.assertEqual(snake_case  ,							getattr(snake_case  ,							snake_case))






       def       lowerCAmelCase		(      self)						->  Any:




          '''simple docstring'''
          _UpperCAmelCase       :       Union[str, Any]							   =BertConfig(
              vocab_size=9_9  ,							hidden_size=3_2  ,							num_hidden_layers=5  ,							num_attention_heads=4  ,							intermediate_size=3_7)
          config.push_to_hub('valid_org/test-config-org'  ,							use_auth_token=self._token)

          _UpperCAmelCase       :       int							   =BertConfig.from_pretrained('valid_org/test-config-org')
          for k, v in config.to_dict().items():
             if k != "transformers_version":
                self.assertEqual(snake_case  ,							getattr(snake_case  ,							snake_case))

        # Reset repo
          delete_repo(token=self._token  ,							repo_id='valid_org/test-config-org')

          # Push to hub via save_pretrained
          with tempfile.TemporaryDirectory() as tmp_dir:
             config.save_pretrained(
                 snake_case  ,							repo_id='valid_org/test-config-org'  ,							push_to_hub=snake_case  ,							use_auth_token=self._token)

          _UpperCAmelCase       :       str							   =BertConfig.from_pretrained('valid_org/test-config-org')
          for k, v in config.to_dict().items():
             if k != "transformers_version":
                self.assertEqual(snake_case  ,							getattr(snake_case  ,							snake_case))






       def       lowerCAmelCase		(      self)						->  List[str]:




          '''simple docstring'''
          CustomConfig.register_for_auto_class()
          _UpperCAmelCase       :       str							   =CustomConfig(attribute=4_2)

          config.push_to_hub('test-dynamic-config'  ,							use_auth_token=self._token)

          # This has added the proper auto_map field to the config
          self.assertDictEqual(config.auto_map  ,							{'AutoConfig': 'custom_configuration.CustomConfig'})

          _UpperCAmelCase       :       Dict							   =AutoConfig.from_pretrained(f"{USER}/test-dynamic-config"  ,							trust_remote_code=snake_case)
          # Can't make an isinstance check because the new_config is from the FakeConfig class of a dynamic module
          self.assertEqual(new_config.__class__.__name__  ,							'CustomConfig')
          self.assertEqual(new_config.attribute  ,							4_2)






class  __magic_name__							(		unittest.TestCase    ):






       def       lowerCAmelCase		(      self)						->  int:




          '''simple docstring'''
          _UpperCAmelCase       :       List[str]							   =GPTaConfig()

          # attempt to modify each of int/float/bool/str config records and verify they were updated
          _UpperCAmelCase       :       List[str]							   =c.n_embd + 1  # int
          _UpperCAmelCase       :       Tuple							   =c.resid_pdrop + 1.0  # float
          _UpperCAmelCase       :       Tuple							   =not c.scale_attn_weights  # bool
          _UpperCAmelCase       :       Union[str, Any]							   =c.summary_type + 'foo'  # str
          c.update_from_string(
              f"n_embd={n_embd},resid_pdrop={resid_pdrop},scale_attn_weights={scale_attn_weights},summary_type={summary_type}")
          self.assertEqual(snake_case  ,							c.n_embd  ,							'mismatch for key: n_embd')
          self.assertEqual(snake_case  ,							c.resid_pdrop  ,							'mismatch for key: resid_pdrop')
          self.assertEqual(snake_case  ,							c.scale_attn_weights  ,							'mismatch for key: scale_attn_weights')
          self.assertEqual(snake_case  ,							c.summary_type  ,							'mismatch for key: summary_type')






       def       lowerCAmelCase		(      self)						->  str:




          '''simple docstring'''
          _UpperCAmelCase       :       Dict							   =PretrainedConfig()
          _UpperCAmelCase       :       Dict							   =[key for key in base_config.__dict__ if key not in config_common_kwargs]
          # If this part of the test fails, you have arguments to addin config_common_kwargs above.
          self.assertListEqual(
              snake_case  ,							['is_encoder_decoder', '_name_or_path', '_commit_hash', 'transformers_version'])
          _UpperCAmelCase       :       Optional[int]							   =[key for key, value in config_common_kwargs.items() if value == getattr(snake_case  ,							snake_case)]
          if len(snake_case) > 0:
             raise ValueError(
                 'The following keys are set with the default values in'
                 ' `test_configuration_common.config_common_kwargs` pick another value for them:'
                 f" {', '.join(snake_case)}.")






       def       lowerCAmelCase		(      self)						->  int:




          '''simple docstring'''
          with self.assertRaises(snake_case):
             # config is in subfolder, the following should not work without specifying the subfolder
             _UpperCAmelCase       :       int							   =BertConfig.from_pretrained('hf-internal-testing/tiny-random-bert-subfolder')

          _UpperCAmelCase       :       Any							   =BertConfig.from_pretrained('hf-internal-testing/tiny-random-bert-subfolder'  ,							subfolder='bert')

          self.assertIsNotNone(snake_case)






       def       lowerCAmelCase		(      self)						->  Dict:




          '''simple docstring'''
          # A mock response for an HTTP head request to emulate server down
          _UpperCAmelCase       :       int							   =mock.Mock()
          _UpperCAmelCase       :       List[str]							   =5_0_0
          _UpperCAmelCase       :       Dict							   ={}
          _UpperCAmelCase       :       Union[str, Any]							   =HTTPError
          _UpperCAmelCase       :       str							   ={}

          # Download this model to make sure it's in the cache.
          _UpperCAmelCase       :       List[str]							   =BertConfig.from_pretrained('hf-internal-testing/tiny-random-bert')

          # Under the mock environment we get a 500 error when trying to reach the model.
          with mock.patch('requests.Session.request'  ,							return_value=snake_case) as mock_head:
             _UpperCAmelCase       :       Tuple							   =BertConfig.from_pretrained('hf-internal-testing/tiny-random-bert')
             # This check we did call the fake head request
             mock_head.assert_called()






       def       lowerCAmelCase		(      self)						->  List[Any]:




          '''simple docstring'''
          # This test is for deprecated behavior and can be removed in v5
          _UpperCAmelCase       :       Optional[int]							   =BertConfig.from_pretrained(
              'https://huggingface.co/hf-internal-testing/tiny-random-bert/resolve/main/config.json')






       def       lowerCAmelCase		(      self)						->  Tuple:




          '''simple docstring'''
          _UpperCAmelCase       :       int							   =AutoConfig.from_pretrained('bert-base-cased')
          _UpperCAmelCase       :       int							   =['config.4.0.0.json']

          with tempfile.TemporaryDirectory() as tmp_dir:
             configuration.save_pretrained(snake_case)
             _UpperCAmelCase       :       Dict							   =2
             json.dump(configuration.to_dict()  ,							open(os.path.join(snake_case  ,							'config.4.0.0.json')  ,							'w'))

             # This should pick the new configuration file as the version of Transformers is > 4.0.0
             _UpperCAmelCase       :       int							   =AutoConfig.from_pretrained(snake_case)
             self.assertEqual(new_configuration.hidden_size  ,							2)

             # Will need to be adjusted if we reach v42 and this test is still here.
             # Should pick the old configuration file as the version of Transformers is < 4.42.0
             _UpperCAmelCase       :       Optional[int]							   =['config.42.0.0.json']
             _UpperCAmelCase       :       str							   =7_6_8
             configuration.save_pretrained(snake_case)
             shutil.move(os.path.join(snake_case  ,							'config.4.0.0.json')  ,							os.path.join(snake_case  ,							'config.42.0.0.json'))
             _UpperCAmelCase       :       Tuple							   =AutoConfig.from_pretrained(snake_case)
             self.assertEqual(new_configuration.hidden_size  ,							7_6_8)






       def       lowerCAmelCase		(      self)						->  List[Any]:




          '''simple docstring'''
          # This repo has two configuration files, one for v4.0.0 and above with a different hidden size.
          _UpperCAmelCase       :       Dict							   ='hf-internal-testing/test-two-configs'

          import transformers as new_transformers

          _UpperCAmelCase       :       Union[str, Any]							   ='v4.0.0'
          _UpperCAmelCase   ,	_UpperCAmelCase       :       Dict							   =new_transformers.models.auto.AutoConfig.from_pretrained(
              snake_case  ,							return_unused_kwargs=snake_case)
          self.assertEqual(new_configuration.hidden_size  ,							2)
          # This checks `_configuration_file` ia not kept in the kwargs by mistake.
          self.assertDictEqual(snake_case  ,							{})

          # Testing an older version by monkey-patching the version in the module it's used.
          import transformers as old_transformers

          _UpperCAmelCase       :       int							   ='v3.0.0'
          _UpperCAmelCase       :       str							   =old_transformers.models.auto.AutoConfig.from_pretrained(snake_case)
          self.assertEqual(old_configuration.hidden_size  ,							7_6_8)





'''simple docstring'''






import warnings

from ...utils import logging
from .image_processing_deformable_detr import DeformableDetrImageProcessor


lowercase							=logging.get_logger(__name__)






class  __magic_name__							(		lowerCAmelCase    ):






       def __init__(      self  ,							*snake_case  ,							**snake_case)						->  None:




          '''simple docstring'''
          warnings.warn(
              'The class DeformableDetrFeatureExtractor is deprecated and will be removed in version 5 of Transformers.'
              ' Please use DeformableDetrImageProcessor instead.'  ,							snake_case  ,							)
          super().__init__(*snake_case  ,							**snake_case)

