






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        UpperCamelCase    (							self    ):
							"""simple docstring"""







							for model_name in ["bert-base-cased", "bert-large-uncased"]:
													with self.subTest(UpperCAmelCase    ):
																			_UpperCAmelCase									=			AutoConfig.from_pretrained(UpperCAmelCase    )
																			self.assertIsNotNone(UpperCAmelCase    )
																			self.assertIsInstance(UpperCAmelCase       ,    UpperCAmelCase    )

																			_UpperCAmelCase									=			FlaxAutoModel.from_pretrained(UpperCAmelCase    )
																			self.assertIsNotNone(UpperCAmelCase    )
																			self.assertIsInstance(UpperCAmelCase       ,    UpperCAmelCase    )

	@slow
	def        UpperCamelCase    (							self    ):
							"""simple docstring"""







							for model_name in ["roberta-base", "roberta-large"]:
													with self.subTest(UpperCAmelCase    ):
																			_UpperCAmelCase									=			AutoConfig.from_pretrained(UpperCAmelCase    )
																			self.assertIsNotNone(UpperCAmelCase    )
																			self.assertIsInstance(UpperCAmelCase       ,    UpperCAmelCase    )

																			_UpperCAmelCase									=			FlaxAutoModel.from_pretrained(UpperCAmelCase    )
																			self.assertIsNotNone(UpperCAmelCase    )
																			self.assertIsInstance(UpperCAmelCase       ,    UpperCAmelCase    )

	@slow
	def        UpperCamelCase    (							self    ):
							"""simple docstring"""







							for model_name in ["bert-base-cased", "bert-large-uncased"]:
													_UpperCAmelCase									=			AutoTokenizer.from_pretrained(UpperCAmelCase    )
													_UpperCAmelCase									=			FlaxBertModel.from_pretrained(UpperCAmelCase    )
													_UpperCAmelCase									=			tokenizer('Do you support jax jitted function?'       ,    return_tensors=TensorType.JAX    )

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

													eval(**UpperCAmelCase    ).block_until_ready()

	@slow
	def        UpperCamelCase    (							self    ):
							"""simple docstring"""







							for model_name in ["roberta-base", "roberta-large"]:
													_UpperCAmelCase									=			AutoTokenizer.from_pretrained(UpperCAmelCase    )
													_UpperCAmelCase									=			FlaxRobertaModel.from_pretrained(UpperCAmelCase    )
													_UpperCAmelCase									=			tokenizer('Do you support jax jitted function?'       ,    return_tensors=TensorType.JAX    )

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

													eval(**UpperCAmelCase    ).block_until_ready()

	def        UpperCamelCase    (							self    ):
							"""simple docstring"""







							with self.assertRaisesRegex(
							    UpperCAmelCase       ,    'bert-base is not a local folder and is not a valid model identifier'    ):
													_UpperCAmelCase									=			FlaxAutoModel.from_pretrained('bert-base'    )

	def        UpperCamelCase    (							self    ):
							"""simple docstring"""







							with self.assertRaisesRegex(
							    UpperCAmelCase       ,    R'aaaaaa is not a valid git identifier \(branch name, tag name or commit id\)'    ):
													_UpperCAmelCase									=			FlaxAutoModel.from_pretrained(UpperCAmelCase       ,    revision='aaaaaa'    )

	def        UpperCamelCase    (							self    ):
							"""simple docstring"""







							with self.assertRaisesRegex(
							    UpperCAmelCase       ,    '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        UpperCamelCase    (							self    ):
							"""simple docstring"""







							with self.assertRaisesRegex(UpperCAmelCase       ,    'Use `from_pt=True` to load this model'    ):
													_UpperCAmelCase									=			FlaxAutoModel.from_pretrained('hf-internal-testing/tiny-bert-pt-only'    )







from __future__ import annotations

import math

def   a_    ( lowerCAmelCase_      :			int,	lowerCAmelCase_      :			int,	lowerCAmelCase_      :			bool,	lowerCAmelCase_      :			list[int],	lowerCAmelCase_      :			float	):

   if depth < 0:
      raise ValueError('Depth cannot be less than 0'	)

   if len(lowerCAmelCase_	) == 0:
      raise ValueError('Scores cannot be empty'	)

   if depth == height:
      return scores[node_index]

   if is_max:
      return max(
          minimax(depth + 1,	node_index * 2,	lowerCAmelCase_,	lowerCAmelCase_,	lowerCAmelCase_	),	minimax(depth + 1,	node_index * 2 + 1,	lowerCAmelCase_,	lowerCAmelCase_,	lowerCAmelCase_	),	)

   return min(
       minimax(depth + 1,	node_index * 2,	lowerCAmelCase_,	lowerCAmelCase_,	lowerCAmelCase_	),	minimax(depth + 1,	node_index * 2 + 1,	lowerCAmelCase_,	lowerCAmelCase_,	lowerCAmelCase_	),	)

def   a_    ( ):
   __lowerCAmelCase								=	[90, 23, 6, 33, 21, 65, 123, 3_4423]
   __lowerCAmelCase								=	math.log(len(lowerCAmelCase_	),	2	)
   print('Optimal value : ',	end=''	)
   print(minimax(0,	0,	lowerCAmelCase_,	lowerCAmelCase_,	lowerCAmelCase_	)	)


if __name__ == "__main__":
     import doctest

     doctest.testmod()
     main()

