






"""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


SCREAMING_SNAKE_CASE						:						Optional[int]					   =       {
    '''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, 1.0_1),
    '''suppress_tokens''': [0, 1],
    '''begin_suppress_tokens''': 2,
    '''task_specific_params''': {'''translation''': '''some_params'''},
    '''problem_type''': '''regression''',
}





@is_staging_test
class       snake_case_       (    unittest.TestCase       ):



	"""simple docstring"""

	@classmethod
	def       _UpperCAmelCase						(      cls						):


					"""simple docstring"""

					A__							 =       TOKEN
					HfFolder.save_token(__a						)


	@classmethod
	def       _UpperCAmelCase						(      cls						):


					"""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       _UpperCAmelCase						(      self						):


					"""simple docstring"""

					A__							 =       BertConfig(
					    vocab_size=99  ,					hidden_size=32  ,					num_hidden_layers=5  ,					num_attention_heads=4  ,					intermediate_size=37						)
					config.push_to_hub('test-config'  ,					use_auth_token=self._token						)

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

        # 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(__a  ,					repo_id='test-config'  ,					push_to_hub=__a  ,					use_auth_token=self._token						)

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


	def       _UpperCAmelCase						(      self						):


					"""simple docstring"""

					A__							 =       BertConfig(
					    vocab_size=99  ,					hidden_size=32  ,					num_hidden_layers=5  ,					num_attention_heads=4  ,					intermediate_size=37						)
					config.push_to_hub('valid_org/test-config-org'  ,					use_auth_token=self._token						)

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

        # 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(
									    __a  ,					repo_id='valid_org/test-config-org'  ,					push_to_hub=__a  ,					use_auth_token=self._token						)

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






	def       _UpperCAmelCase						(      self						):


					"""simple docstring"""

					CustomConfig.register_for_auto_class()
					A__							 =       CustomConfig(attribute=42						)

					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'}						)

					A__							 =       AutoConfig.from_pretrained(f'''{USER}/test-dynamic-config'''  ,					trust_remote_code=__a						)
					# 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  ,					42						)





class       snake_case_       (    unittest.TestCase       ):



	"""simple docstring"""

	def       _UpperCAmelCase						(      self						):


					"""simple docstring"""

					A__							 =       GPTaConfig()

					# attempt to modify each of int/float/bool/str config records and verify they were updated
					A__							 =       c.n_embd + 1  # int
					A__							 =       c.resid_pdrop + 1.0  # float
					A__							 =       not c.scale_attn_weights  # bool
					A__							 =       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(__a  ,					c.n_embd  ,					'mismatch for key: n_embd'						)
					self.assertEqual(__a  ,					c.resid_pdrop  ,					'mismatch for key: resid_pdrop'						)
					self.assertEqual(__a  ,					c.scale_attn_weights  ,					'mismatch for key: scale_attn_weights'						)
					self.assertEqual(__a  ,					c.summary_type  ,					'mismatch for key: summary_type'						)


	def       _UpperCAmelCase						(      self						):


					"""simple docstring"""

					A__							 =       PretrainedConfig()
					A__							 =       [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(
					    __a  ,					['is_encoder_decoder', '_name_or_path', '_commit_hash', 'transformers_version']						)
					A__							 =       [key for key, value in config_common_kwargs.items() if value == getattr(__a  ,					__a						)]
					if len(__a						) > 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(__a						)}.'''						)


	def       _UpperCAmelCase						(      self						):


					"""simple docstring"""

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

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

					self.assertIsNotNone(__a						)


	def       _UpperCAmelCase						(      self						):


					"""simple docstring"""

					A__							 =       mock.Mock()
					A__							 =       500
					A__							 =       {}
					A__							 =       HTTPError
					A__							 =       {}

					# Download this model to make sure it's in the cache.
					A__							 =       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=__a						) as mock_head:
									A__							 =       BertConfig.from_pretrained('hf-internal-testing/tiny-random-bert'						)
									# This check we did call the fake head request
									mock_head.assert_called()


	def       _UpperCAmelCase						(      self						):


					"""simple docstring"""

					A__							 =       BertConfig.from_pretrained(
					    'https://huggingface.co/hf-internal-testing/tiny-random-bert/resolve/main/config.json'						)


	def       _UpperCAmelCase						(      self						):


					"""simple docstring"""

					A__							 =       AutoConfig.from_pretrained('bert-base-cased'						)
					A__							 =       ['config.4.0.0.json']

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

									# This should pick the new configuration file as the version of Transformers is > 4.0.0
									A__							 =       AutoConfig.from_pretrained(__a						)
									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
									A__							 =       ['config.42.0.0.json']
									A__							 =       768
									configuration.save_pretrained(__a						)
									shutil.move(os.path.join(__a  ,					'config.4.0.0.json'						)  ,					os.path.join(__a  ,					'config.42.0.0.json'						)						)
									A__							 =       AutoConfig.from_pretrained(__a						)
									self.assertEqual(new_configuration.hidden_size  ,					768						)






	def       _UpperCAmelCase						(      self						):


					"""simple docstring"""

					A__							 =       'hf-internal-testing/test-two-configs'

					import transformers as new_transformers

					A__							 =       'v4.0.0'
					A__ ,			A__							 =       new_transformers.models.auto.AutoConfig.from_pretrained(
					    __a  ,					return_unused_kwargs=__a						)
					self.assertEqual(new_configuration.hidden_size  ,					2						)
					# This checks `_configuration_file` ia not kept in the kwargs by mistake.
					self.assertDictEqual(__a  ,					{}						)

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

					A__							 =       'v3.0.0'
					A__							 =       old_transformers.models.auto.AutoConfig.from_pretrained(__a						)
					self.assertEqual(old_configuration.hidden_size  ,					768						)










"""simple docstring"""






import numpy as np



def  __lowerCamelCase					(					lowerCAmelCase__				):
				return 1 / (1 + np.exp(-vector				))



def  __lowerCamelCase					(					lowerCAmelCase__				):
				return vector * sigmoid(lowerCAmelCase__				)


if __name__ == "__main__":
					import doctest

					doctest.testmod()


