





'''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        _UpperCAmelCase				(		unittest.TestCase  ):
		@slow
		def     lowerCamelCase__     (    self     ):



					'''simple docstring'''

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

											__lowerCAmelCase   		=							FlaxAutoModel.from_pretrained(__SCREAMING_SNAKE_CASE     )
											self.assertIsNotNone(__SCREAMING_SNAKE_CASE     )
											self.assertIsInstance(__SCREAMING_SNAKE_CASE,__SCREAMING_SNAKE_CASE     )
		@slow
		def     lowerCamelCase__     (    self     ):



					'''simple docstring'''

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

											__lowerCAmelCase   		=							FlaxAutoModel.from_pretrained(__SCREAMING_SNAKE_CASE     )
											self.assertIsNotNone(__SCREAMING_SNAKE_CASE     )
											self.assertIsInstance(__SCREAMING_SNAKE_CASE,__SCREAMING_SNAKE_CASE     )
		@slow
		def     lowerCamelCase__     (    self     ):



					'''simple docstring'''

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

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

								eval(**__SCREAMING_SNAKE_CASE     ).block_until_ready()
		@slow
		def     lowerCamelCase__     (    self     ):



					'''simple docstring'''

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

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

								eval(**__SCREAMING_SNAKE_CASE     ).block_until_ready()
		def     lowerCamelCase__     (    self     ):



					'''simple docstring'''

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



					'''simple docstring'''

					with self.assertRaisesRegex(
					    __SCREAMING_SNAKE_CASE,R"""aaaaaa is not a valid git identifier \(branch name, tag name or commit id\)"""     ):
								__lowerCAmelCase   		=							FlaxAutoModel.from_pretrained(__SCREAMING_SNAKE_CASE,revision="""aaaaaa"""     )
		def     lowerCamelCase__     (    self     ):



					'''simple docstring'''

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







		def     lowerCamelCase__     (    self     ):



					'''simple docstring'''

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





'''simple docstring'''
import string
from math import logaa







def       a_				(	UpperCamelCase_						,  UpperCamelCase_ ):
							A_			    =		document.translate(
							    str.maketrans(""						,  ""						,  string.punctuation ) ).replace("\n"						,  "" )
							A_			    =		document_without_punctuation.split(" " )  # word tokenization
							return len([word for word in tokenize_document if word.lower() == term.lower()] )







def       a_				(	UpperCamelCase_						,  UpperCamelCase_ ):
							A_			    =		corpus.lower().translate(
							    str.maketrans(""						,  ""						,  string.punctuation ) )  # strip all punctuation and replace it with ''
							A_			    =		corpus_without_punctuation.split("\n" )
							A_			    =		term.lower()
							return (len([doc for doc in docs if term in doc] ), len(UpperCamelCase_ ))







def       a_				(	UpperCamelCase_						,  UpperCamelCase_						,  UpperCamelCase_=False ):
							if smoothing:
														if n == 0:
																					raise ValueError("log10(0) is undefined." )
														return round(1 + logaa(n / (1 + df) )						,  3 )

							if df == 0:
														raise ZeroDivisionError("df must be > 0" )
							elif n == 0:
														raise ValueError("log10(0) is undefined." )
							return round(logaa(n / df )						,  3 )







def       a_				(	UpperCamelCase_						,  UpperCamelCase_ ):
							return round(tf * idf						,  3 )





