



import unittest

from transformers import AutoConfig, AutoTokenizer, BertConfig, TensorType, is_flax_available
from transformers.testing_utils import DUMMY_UNKNOWN_IDENTIFIER, require_flax, slow


if is_flax_available():
			import jax

			from transformers.models.auto.modeling_flax_auto import FlaxAutoModel
			from transformers.models.bert.modeling_flax_bert import FlaxBertModel
			from transformers.models.roberta.modeling_flax_roberta import FlaxRobertaModel



@require_flax
class 	lowerCamelCase      (						unittest.TestCase  ):







					'''simple docstring'''







					@slow
					def    A__		(			self     ):
							for model_name in ["bert-base-cased", "bert-large-uncased"]:
									with self.subTest(lowerCAmelCase     ):
											UpperCAmelCase_						=				AutoConfig.from_pretrained(lowerCAmelCase     )
											self.assertIsNotNone(lowerCAmelCase     )
											self.assertIsInstance(lowerCAmelCase    ,	lowerCAmelCase     )

											UpperCAmelCase_						=				FlaxAutoModel.from_pretrained(lowerCAmelCase     )
											self.assertIsNotNone(lowerCAmelCase     )
											self.assertIsInstance(lowerCAmelCase    ,	lowerCAmelCase     )



					@slow
					def    A__		(			self     ):
							for model_name in ["roberta-base", "roberta-large"]:
									with self.subTest(lowerCAmelCase     ):
											UpperCAmelCase_						=				AutoConfig.from_pretrained(lowerCAmelCase     )
											self.assertIsNotNone(lowerCAmelCase     )
											self.assertIsInstance(lowerCAmelCase    ,	lowerCAmelCase     )

											UpperCAmelCase_						=				FlaxAutoModel.from_pretrained(lowerCAmelCase     )
											self.assertIsNotNone(lowerCAmelCase     )
											self.assertIsInstance(lowerCAmelCase    ,	lowerCAmelCase     )



					@slow
					def    A__		(			self     ):
							for model_name in ["bert-base-cased", "bert-large-uncased"]:
									UpperCAmelCase_						=				AutoTokenizer.from_pretrained(lowerCAmelCase     )
									UpperCAmelCase_						=				FlaxBertModel.from_pretrained(lowerCAmelCase     )
									UpperCAmelCase_						=				tokenizer("Do you support jax jitted function?"    ,	return_tensors=TensorType.JAX     )

									@jax.jit
									def eval(**lowerCAmelCase     ):
											return model(**lowerCAmelCase     )

									eval(**lowerCAmelCase     ).block_until_ready()



					@slow
					def    A__		(			self     ):
							for model_name in ["roberta-base", "roberta-large"]:
									UpperCAmelCase_						=				AutoTokenizer.from_pretrained(lowerCAmelCase     )
									UpperCAmelCase_						=				FlaxRobertaModel.from_pretrained(lowerCAmelCase     )
									UpperCAmelCase_						=				tokenizer("Do you support jax jitted function?"    ,	return_tensors=TensorType.JAX     )

									@jax.jit
									def eval(**lowerCAmelCase     ):
											return model(**lowerCAmelCase     )

									eval(**lowerCAmelCase     ).block_until_ready()



					def    A__		(			self     ):
							with self.assertRaisesRegex(
							    lowerCAmelCase    ,	"bert-base is not a local folder and is not a valid model identifier"     ):
									UpperCAmelCase_						=				FlaxAutoModel.from_pretrained("bert-base"     )



					def    A__		(			self     ):
							with self.assertRaisesRegex(
							    lowerCAmelCase    ,	r"aaaaaa is not a valid git identifier \(branch name, tag name or commit id\)"     ):
									UpperCAmelCase_						=				FlaxAutoModel.from_pretrained(lowerCAmelCase    ,	revision="aaaaaa"     )



					def    A__		(			self     ):
							with self.assertRaisesRegex(
							    lowerCAmelCase    ,	"hf-internal-testing/config-no-model does not appear to have a file named flax_model.msgpack"    ,	):
									UpperCAmelCase_						=				FlaxAutoModel.from_pretrained("hf-internal-testing/config-no-model"     )



					def    A__		(			self     ):
							with self.assertRaisesRegex(lowerCAmelCase    ,	"Use `from_pt=True` to load this model"     ):
									UpperCAmelCase_						=				FlaxAutoModel.from_pretrained("hf-internal-testing/tiny-bert-pt-only"     )






import math







def snake_case__  (			__SCREAMING_SNAKE_CASE )		->							list[int]:
		UpperCAmelCase_						=				[]
		UpperCAmelCase_						=				2
		UpperCAmelCase_						=				int(math.sqrt(__SCREAMING_SNAKE_CASE ) )  # Size of every segment
		UpperCAmelCase_						=				[True] * (end + 1)
		UpperCAmelCase_						=				[]

		while start <= end:
				if temp[start] is True:
						in_prime.append(__SCREAMING_SNAKE_CASE )
						for i in range(start * start			,     end + 1			,     __SCREAMING_SNAKE_CASE ):
								UpperCAmelCase_						=				False
				start += 1
		prime += in_prime

		UpperCAmelCase_						=				end + 1
		UpperCAmelCase_						=				min(2 * end			,     __SCREAMING_SNAKE_CASE )

		while low <= n:
				UpperCAmelCase_						=				[True] * (high - low + 1)
				for each in in_prime:
						UpperCAmelCase_						=				math.floor(low / each ) * each
						if t < low:
								t += each

						for j in range(__SCREAMING_SNAKE_CASE			,     high + 1			,     __SCREAMING_SNAKE_CASE ):
								UpperCAmelCase_						=				False

				for j in range(len(__SCREAMING_SNAKE_CASE ) ):
						if temp[j] is True:
								prime.append(j + low )

				UpperCAmelCase_						=				high + 1
				UpperCAmelCase_						=				min(high + end			,     __SCREAMING_SNAKE_CASE )

		return prime

print(sieve(10**6))

