



'''simple docstring'''
def A__       (	UpperCAmelCase_    ,    UpperCAmelCase_				):
						_enforce_args(UpperCAmelCase_    ,    UpperCAmelCase_				)
						if n == 0:
												return 0
						_UpperCamelCase   :						Optional[int]												=  float('-inf'				)
						for i in range(1    ,    n + 1				):
												_UpperCamelCase   :						int												=  max(
												    UpperCAmelCase_    ,    prices[i - 1] + naive_cut_rod_recursive(n - i    ,    UpperCAmelCase_				)				)

						return max_revue






def A__       (	UpperCAmelCase_    ,    UpperCAmelCase_				):
						_enforce_args(UpperCAmelCase_    ,    UpperCAmelCase_				)
						_UpperCamelCase   :						List[str]												=  [float('-inf'				) for _ in range(n + 1				)]
						return _top_down_cut_rod_recursive(UpperCAmelCase_    ,    UpperCAmelCase_    ,    UpperCAmelCase_				)






def A__       (	UpperCAmelCase_    ,    UpperCAmelCase_    ,    UpperCAmelCase_				):
						if max_rev[n] >= 0:
												return max_rev[n]
						elif n == 0:
												return 0
						else:
												_UpperCamelCase   :						Union[str, Any]												=  float('-inf'				)
												for i in range(1    ,    n + 1				):
																		_UpperCamelCase   :						Tuple												=  max(
																		    UpperCAmelCase_    ,    prices[i - 1] + _top_down_cut_rod_recursive(n - i    ,    UpperCAmelCase_    ,    UpperCAmelCase_				)    ,    )

												_UpperCamelCase   :						Tuple												=  max_revenue

						return max_rev[n]






def A__       (	UpperCAmelCase_    ,    UpperCAmelCase_				):
						_enforce_args(UpperCAmelCase_    ,    UpperCAmelCase_				)

						# length(max_rev) = n + 1, to accommodate for the revenue obtainable from a rod of
						# length 0.
						_UpperCamelCase   :						Dict												=  [float('-inf'				) for _ in range(n + 1				)]
						_UpperCamelCase   :						Dict												=  0

						for i in range(1    ,    n + 1				):
												_UpperCamelCase   :						Tuple												=  max_rev[i]
												for j in range(1    ,    i + 1				):
																		_UpperCamelCase   :						Dict												=  max(UpperCAmelCase_    ,    prices[j - 1] + max_rev[i - j]				)

												_UpperCamelCase   :						Optional[Any]												=  max_revenue_i

						return max_rev[n]






def A__       (	UpperCAmelCase_    ,    UpperCAmelCase_				):
						if n < 0:
												_UpperCamelCase   :						List[Any]												=  f'n must be greater than or equal to 0. Got n = {n}'
												raise ValueError(UpperCAmelCase_				)

						if n > len(UpperCAmelCase_				):
												_UpperCamelCase   :						int												=  (
												    'Each integral piece of rod must have a corresponding price. '
												    f'Got n = {n} but length of prices = {len(UpperCAmelCase_				)}'
												)
												raise ValueError(UpperCAmelCase_				)






def A__       (	):
						_UpperCamelCase   :						Dict												=  [6, 1_0, 1_2, 1_5, 2_0, 2_3]
						_UpperCamelCase   :						Union[str, Any]												=  len(UpperCAmelCase_				)

						# the best revenue comes from cutting the rod into 6 pieces, each
						# of length 1 resulting in a revenue of 6 * 6 = 36.
						_UpperCamelCase   :						Dict												=  3_6

						_UpperCamelCase   :						List[str]												=  top_down_cut_rod(UpperCAmelCase_    ,    UpperCAmelCase_				)
						_UpperCamelCase   :						List[str]												=  bottom_up_cut_rod(UpperCAmelCase_    ,    UpperCAmelCase_				)
						_UpperCamelCase   :						List[Any]												=  naive_cut_rod_recursive(UpperCAmelCase_    ,    UpperCAmelCase_				)

						assert expected_max_revenue == max_rev_top_down
						assert max_rev_top_down == max_rev_bottom_up
						assert max_rev_bottom_up == max_rev_naive


if __name__ == "__main__":
					main()







'''simple docstring'''
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 				lowercase__      (				unittest.TestCase  ):





	@slow
	def       UpperCamelCase_    (					self   :							Union[str, Any]					):







							'''simple docstring'''
							for model_name in ["bert-base-cased", "bert-large-uncased"]:
													with self.subTest(lowerCamelCase__					):
																			_UpperCamelCase   :						Optional[int]												=  AutoConfig.from_pretrained(lowerCamelCase__					)
																			self.assertIsNotNone(lowerCamelCase__					)
																			self.assertIsInstance(lowerCamelCase__					,lowerCamelCase__					)

																			_UpperCamelCase   :						Dict												=  FlaxAutoModel.from_pretrained(lowerCamelCase__					)
																			self.assertIsNotNone(lowerCamelCase__					)
																			self.assertIsInstance(lowerCamelCase__					,lowerCamelCase__					)





	@slow
	def       UpperCamelCase_    (					self   :							List[Any]					):







							'''simple docstring'''
							for model_name in ["roberta-base", "roberta-large"]:
													with self.subTest(lowerCamelCase__					):
																			_UpperCamelCase   :						Any												=  AutoConfig.from_pretrained(lowerCamelCase__					)
																			self.assertIsNotNone(lowerCamelCase__					)
																			self.assertIsInstance(lowerCamelCase__					,lowerCamelCase__					)

																			_UpperCamelCase   :						Any												=  FlaxAutoModel.from_pretrained(lowerCamelCase__					)
																			self.assertIsNotNone(lowerCamelCase__					)
																			self.assertIsInstance(lowerCamelCase__					,lowerCamelCase__					)





	@slow
	def       UpperCamelCase_    (					self   :							Union[str, Any]					):







							'''simple docstring'''
							for model_name in ["bert-base-cased", "bert-large-uncased"]:
													_UpperCamelCase   :						Optional[int]												=  AutoTokenizer.from_pretrained(lowerCamelCase__					)
													_UpperCamelCase   :						List[Any]												=  FlaxBertModel.from_pretrained(lowerCamelCase__					)
													_UpperCamelCase   :						Optional[int]												=  tokenizer('Do you support jax jitted function?'					,return_tensors=TensorType.JAX					)

													@jax.jit
													def eval(**lowerCamelCase__   :							Union[str, Any]					):
																			return model(**lowerCamelCase__					)

													eval(**lowerCamelCase__					).block_until_ready()





	@slow
	def       UpperCamelCase_    (					self   :							Dict					):







							'''simple docstring'''
							for model_name in ["roberta-base", "roberta-large"]:
													_UpperCamelCase   :						Optional[int]												=  AutoTokenizer.from_pretrained(lowerCamelCase__					)
													_UpperCamelCase   :						Tuple												=  FlaxRobertaModel.from_pretrained(lowerCamelCase__					)
													_UpperCamelCase   :						Optional[Any]												=  tokenizer('Do you support jax jitted function?'					,return_tensors=TensorType.JAX					)

													@jax.jit
													def eval(**lowerCamelCase__   :							Union[str, Any]					):
																			return model(**lowerCamelCase__					)

													eval(**lowerCamelCase__					).block_until_ready()





	def       UpperCamelCase_    (					self   :							Union[str, Any]					):







							'''simple docstring'''
							with self.assertRaisesRegex(
							    lowerCamelCase__					,'bert-base is not a local folder and is not a valid model identifier'					):
													_UpperCamelCase   :						int												=  FlaxAutoModel.from_pretrained('bert-base'					)





	def       UpperCamelCase_    (					self   :							str					):







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





	def       UpperCamelCase_    (					self   :							List[str]					):







							'''simple docstring'''
							with self.assertRaisesRegex(
							    lowerCamelCase__					,'hf-internal-testing/config-no-model does not appear to have a file named flax_model.msgpack'					,):
													_UpperCamelCase   :						List[Any]												=  FlaxAutoModel.from_pretrained('hf-internal-testing/config-no-model'					)





	def       UpperCamelCase_    (					self   :							List[str]					):







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


