


"""simple docstring"""







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_       :       Any      						=  "0.12"  # assumed parallelism: 8






@require_flax
@is_staging_test
class 				__A    (	unittest.TestCase							):






 """simple docstring"""




 @classmethod
 def 				SCREAMING_SNAKE_CASE							(		cls						) ->					Dict:
     a					=TOKEN
     HfFolder.save_token(_a						)


 @classmethod
 def 				SCREAMING_SNAKE_CASE							(		cls						) ->					int:


     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 				SCREAMING_SNAKE_CASE							(		self						) ->					Dict:
     a					=BertConfig(
         vocab_size=99			,   hidden_size=32			,   num_hidden_layers=5			,   num_attention_heads=4			,   intermediate_size=37						)
     a					=FlaxBertModel(_a						)
     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(_a			,   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(_a			,   repo_id='''test-model-flax'''			,   push_to_hub=_a			,   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(_a			,   1E-3			,   msg=f'''{key} not identical'''						)





 def 				SCREAMING_SNAKE_CASE							(		self						) ->					Dict:
     a					=BertConfig(
         vocab_size=99			,   hidden_size=32			,   num_hidden_layers=5			,   num_attention_heads=4			,   intermediate_size=37						)
     a					=FlaxBertModel(_a						)
     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(_a			,   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(
             _a			,   repo_id='''valid_org/test-model-flax-org'''			,   push_to_hub=_a			,   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(_a			,   1E-3			,   msg=f'''{key} not identical'''						)

def _A						(						lowercase	,   lowercase		):







    """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 				__A    (	unittest.TestCase							):






 """simple docstring"""




 def 				SCREAMING_SNAKE_CASE							(		self						) ->					int:
     a					=BertConfig.from_pretrained('''hf-internal-testing/tiny-bert-flax-only'''						)
     a					=FlaxBertModel(_a						)

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

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

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

     self.assertTrue(check_models_equal(_a			,   _a						)						)


 def 				SCREAMING_SNAKE_CASE							(		self						) ->					Optional[int]:
     a					=BertConfig.from_pretrained('''hf-internal-testing/tiny-bert-flax-only'''						)
     a					=FlaxBertModel(_a						)

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

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

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

     self.assertTrue(check_models_equal(_a			,   _a						)						)


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

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

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

     self.assertIsNotNone(_a						)





 def 				SCREAMING_SNAKE_CASE							(		self						) ->					List[Any]:
     a					="""bert"""
     a					="""hf-internal-testing/tiny-random-bert-sharded-subfolder"""
     with self.assertRaises(_a						):
         a					=FlaxBertModel.from_pretrained(_a						)

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

     self.assertIsNotNone(_a						)



"""simple docstring"""







def _A						(						lowercase = 2_00_00_00		):







    """simple docstring"""
    a					=[0 for i in range(n + 1		)]
    a					=1
    a					=1

    for i in range(2	,   int(n**0.5		) + 1		):
        if primality_list[i] == 0:
            for j in range(i * i	,   n + 1	,   lowercase		):
                a					=1
    a					=0
    for i in range(lowercase		):
        if primality_list[i] == 0:
            sum_of_primes += i
    return sum_of_primes


if __name__ == "__main__":
       print(F'{solution() = }')