




import tempfile
import unittest

import numpy as np
from huggingface_hub import HfFolder, delete_repo
from requests.exceptions import HTTPError

from transformers import BertConfig, is_flax_available
from transformers.testing_utils import TOKEN, USER, is_staging_test, require_flax


if is_flax_available():
		import os

		from flax.core.frozen_dict import unfreeze
		from flax.traverse_util import flatten_dict

		from transformers import FlaxBertModel

		__lowerCAmelCase	:       Optional[int]     =	'0.12'  # assumed parallelism: 8




@require_flax
@is_staging_test
class 					snake_case__							(unittest.TestCase     ):
				"""simple docstring"""



				@classmethod
				def 							__UpperCAmelCase							(   cls       :  List[Any]							)      ->  Optional[Any]:
							a					=    TOKEN
							HfFolder.save_token(__lowerCamelCase							)





				@classmethod
				def 							__UpperCAmelCase							(   cls       :  Any							)      ->  Any:
							try:
										delete_repo(token=cls._token      ,   repo_id="test-model-flax"							)
							except HTTPError:
										pass

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





				def 							__UpperCAmelCase							(   self       :  Union[str, Any]							)      ->  str:
							a					=    BertConfig(
							    vocab_size=99      ,   hidden_size=32      ,   num_hidden_layers=5      ,   num_attention_heads=4      ,   intermediate_size=37							)
							a					=    FlaxBertModel(__lowerCamelCase							)
							model.push_to_hub("test-model-flax"      ,   use_auth_token=self._token							)

							a					=    FlaxBertModel.from_pretrained(f"""{USER}/test-model-flax"""							)

							a					=    flatten_dict(unfreeze(model.params							)							)
							a					=    flatten_dict(unfreeze(new_model.params							)							)

							for key in base_params.keys():
										a					=    (base_params[key] - new_params[key]).sum().item()
										self.assertLessEqual(__lowerCamelCase      ,   1e-3      ,   msg=f"""{key} not identical"""							)

							# Reset repo
							delete_repo(token=self._token      ,   repo_id="test-model-flax"							)

							# Push to hub via save_pretrained
							with tempfile.TemporaryDirectory() as tmp_dir:
										model.save_pretrained(__lowerCamelCase      ,   repo_id="test-model-flax"      ,   push_to_hub=__lowerCamelCase      ,   use_auth_token=self._token							)

							a					=    FlaxBertModel.from_pretrained(f"""{USER}/test-model-flax"""							)

							a					=    flatten_dict(unfreeze(model.params							)							)
							a					=    flatten_dict(unfreeze(new_model.params							)							)

							for key in base_params.keys():
										a					=    (base_params[key] - new_params[key]).sum().item()
										self.assertLessEqual(__lowerCamelCase      ,   1e-3      ,   msg=f"""{key} not identical"""							)





				def 							__UpperCAmelCase							(   self       :  Any							)      ->  Optional[int]:
							a					=    BertConfig(
							    vocab_size=99      ,   hidden_size=32      ,   num_hidden_layers=5      ,   num_attention_heads=4      ,   intermediate_size=37							)
							a					=    FlaxBertModel(__lowerCamelCase							)
							model.push_to_hub("valid_org/test-model-flax-org"      ,   use_auth_token=self._token							)

							a					=    FlaxBertModel.from_pretrained("valid_org/test-model-flax-org"							)

							a					=    flatten_dict(unfreeze(model.params							)							)
							a					=    flatten_dict(unfreeze(new_model.params							)							)

							for key in base_params.keys():
										a					=    (base_params[key] - new_params[key]).sum().item()
										self.assertLessEqual(__lowerCamelCase      ,   1e-3      ,   msg=f"""{key} not identical"""							)

							# Reset repo
							delete_repo(token=self._token      ,   repo_id="valid_org/test-model-flax-org"							)

							# Push to hub via save_pretrained
							with tempfile.TemporaryDirectory() as tmp_dir:
										model.save_pretrained(
										    __lowerCamelCase      ,   repo_id="valid_org/test-model-flax-org"      ,   push_to_hub=__lowerCamelCase      ,   use_auth_token=self._token							)

							a					=    FlaxBertModel.from_pretrained("valid_org/test-model-flax-org"							)

							a					=    flatten_dict(unfreeze(model.params							)							)
							a					=    flatten_dict(unfreeze(new_model.params							)							)

							for key in base_params.keys():
										a					=    (base_params[key] - new_params[key]).sum().item()
										self.assertLessEqual(__lowerCamelCase      ,   1e-3      ,   msg=f"""{key} not identical"""							)




def     __magic_name__       (				A	:      str,						A	:      List[str]     ):






			'''simple docstring'''







			a					=    True
			a					=    flatten_dict(modela.params     )
			a					=    flatten_dict(modela.params     )
			for key in flat_params_a.keys():
						if np.sum(np.abs(flat_params_a[key] - flat_params_a[key]     )     ) > 1E-4:
									a					=    False

			return models_are_equal






@require_flax
class 					snake_case__							(unittest.TestCase     ):
				"""simple docstring"""



				def 							__UpperCAmelCase							(   self       :  Optional[Any]							)      ->  Tuple:
							a					=    BertConfig.from_pretrained("hf-internal-testing/tiny-bert-flax-only"							)
							a					=    FlaxBertModel(__lowerCamelCase							)

							a					=    "bert"
							with tempfile.TemporaryDirectory() as tmp_dir:
										model.save_pretrained(os.path.join(__lowerCamelCase      ,   __lowerCamelCase							)							)

										with self.assertRaises(__lowerCamelCase							):
													a					=    FlaxBertModel.from_pretrained(__lowerCamelCase							)

										a					=    FlaxBertModel.from_pretrained(__lowerCamelCase      ,   subfolder=__lowerCamelCase							)

							self.assertTrue(check_models_equal(__lowerCamelCase      ,   __lowerCamelCase							)							)





				def 							__UpperCAmelCase							(   self       :  List[str]							)      ->  Any:
							a					=    BertConfig.from_pretrained("hf-internal-testing/tiny-bert-flax-only"							)
							a					=    FlaxBertModel(__lowerCamelCase							)

							a					=    "bert"
							with tempfile.TemporaryDirectory() as tmp_dir:
										model.save_pretrained(os.path.join(__lowerCamelCase      ,   __lowerCamelCase							)      ,   max_shard_size="10KB"							)

										with self.assertRaises(__lowerCamelCase							):
													a					=    FlaxBertModel.from_pretrained(__lowerCamelCase							)

										a					=    FlaxBertModel.from_pretrained(__lowerCamelCase      ,   subfolder=__lowerCamelCase							)

							self.assertTrue(check_models_equal(__lowerCamelCase      ,   __lowerCamelCase							)							)





				def 							__UpperCAmelCase							(   self       :  Any							)      ->  List[str]:
							a					=    "bert"
							a					=    "hf-internal-testing/tiny-random-bert-subfolder"

							with self.assertRaises(__lowerCamelCase							):
										a					=    FlaxBertModel.from_pretrained(__lowerCamelCase							)

							a					=    FlaxBertModel.from_pretrained(__lowerCamelCase      ,   subfolder=__lowerCamelCase							)

							self.assertIsNotNone(__lowerCamelCase							)





				def 							__UpperCAmelCase							(   self       :  Tuple							)      ->  Union[str, Any]:
							a					=    "bert"
							a					=    "hf-internal-testing/tiny-random-bert-sharded-subfolder"
							with self.assertRaises(__lowerCamelCase							):
										a					=    FlaxBertModel.from_pretrained(__lowerCamelCase							)

							a					=    FlaxBertModel.from_pretrained(__lowerCamelCase      ,   subfolder=__lowerCamelCase							)

							self.assertIsNotNone(__lowerCamelCase							)












def     __magic_name__       (				A	:      str,						A	:      str     ):






			'''simple docstring'''







			def get_matched_characters(A	:      str,						A	:      str     ) -> str:
						a					=    []
						a					=    min(len(_stra     ),						len(_stra     )     ) // 2
						for i, l in enumerate(_stra     ):
									a					=    int(max(0,						i - limit     )     )
									a					=    int(min(i + limit + 1,						len(_stra     )     )     )
									if l in _stra[left:right]:
												matched.append(A     )
												a					=    F"""{_stra[0:_stra.index(A     )]} {_stra[_stra.index(A     ) + 1:]}"""

						return "".join(A     )

			# matching characters
			a					=    get_matched_characters(A,						A     )
			a					=    get_matched_characters(A,						A     )
			a					=    len(A     )

			# transposition
			a					=    (
			    len([(ca, ca) for ca, ca in zip(A,						A     ) if ca != ca]     ) // 2
			)

			if not match_count:
						a					=    0.0
			else:
						a					=    (
						    1
						    / 3
						    * (
						        match_count / len(A     )
						        + match_count / len(A     )
						        + (match_count - transpositions) / match_count
						    )
						)

			# common prefix up to 4 characters
			a					=    0
			for ca, ca in zip(stra[:4],						stra[:4]     ):
						if ca == ca:
									prefix_len += 1
						else:
									break

			return jaro + 0.1 * prefix_len * (1 - jaro)


if __name__ == "__main__":
		import doctest

		doctest.testmod()
		print(jaro_winkler('hello', 'world'))






