



'''simple docstring'''

import unittest
from pathlib import Path
from tempfile import TemporaryDirectory

from transformers import AutoConfig, TFAutoModel, is_tensorflow_text_available, is_tf_available
from transformers.models.bert.tokenization_bert import BertTokenizer
from transformers.testing_utils import require_tensorflow_text, require_tf, slow


if is_tf_available():
				import tensorflow as tf

if is_tensorflow_text_available():
				from transformers.models.bert import TFBertTokenizer


UpperCAmelCase      						=       ['bert-base-uncased', 'bert-base-cased']
UpperCAmelCase      						=       'hf-internal-testing/tiny-bert-tf-only'

if is_tf_available():

				class __snake_case( tf.keras.Model   ):


										'''simple docstring'''



										def __init__(   self      ,			A_ )      ->      List[str]:
											super().__init__()
											lowerCAmelCase       =      tokenizer
											lowerCAmelCase       =      AutoConfig.from_pretrained(lowercase_ )
											lowerCAmelCase       =      TFAutoModel.from_config(lowercase_ )




										def 							__snake_case       (   self      ,			A_ )      ->      Optional[int]:
											lowerCAmelCase       =      self.tokenizer(lowercase_ )
											lowerCAmelCase       =      self.bert(**lowercase_ )
											return out["pooler_output"]

@require_tf
@require_tensorflow_text
class __snake_case( unittest.TestCase   ):


						'''simple docstring'''



						def 							__snake_case       (   self )      ->      Dict:
							super().setUp()

							lowerCAmelCase       =      [
							    BertTokenizer.from_pretrained(lowercase_ ) for checkpoint in (TOKENIZER_CHECKPOINTS * 2)
							]  # repeat for when fast_bert_tokenizer=false
							lowerCAmelCase       =      [TFBertTokenizer.from_pretrained(lowercase_ ) for checkpoint in TOKENIZER_CHECKPOINTS] + [
							    TFBertTokenizer.from_pretrained(lowercase_      ,			use_fast_bert_tokenizer=lowercase_ )
							    for checkpoint in TOKENIZER_CHECKPOINTS
							]
							assert len(self.tokenizers ) == len(self.tf_tokenizers )

							lowerCAmelCase       =      [
							    """This is a straightforward English test sentence.""",
							    """This one has some weird characters\rto\nsee\r\nif  those\u00E9break things.""",
							    """Now we\'re going to add some Chinese: 一 二 三 一二三""",
							    """And some much more rare Chinese: 齉 堃 齉堃""",
							    """Je vais aussi écrire en français pour tester les accents""",
							    """Classical Irish also has some unusual characters, so in they go: Gaelaċ, ꝼ""",
							]
							lowerCAmelCase       =      list(zip(self.test_sentences      ,			self.test_sentences[::-1] ) )


						def 							__snake_case       (   self )      ->      List[str]:
							for tokenizer, tf_tokenizer in zip(self.tokenizers      ,			self.tf_tokenizers ):
								for test_inputs in (self.test_sentences, self.paired_sentences):
									lowerCAmelCase       =      tokenizer(lowercase_      ,			return_tensors="""tf"""      ,			padding="""longest""" )
									lowerCAmelCase       =      tf_tokenizer(lowercase_ )

									for key in python_outputs.keys():
										self.assertTrue(tf.reduce_all(python_outputs[key].shape == tf_outputs[key].shape ) )
										self.assertTrue(tf.reduce_all(tf.cast(python_outputs[key]      ,			tf.intaa ) == tf_outputs[key] ) )


						@slow
						def 							__snake_case       (   self )      ->      Union[str, Any]:
							for tf_tokenizer in self.tf_tokenizers:
								lowerCAmelCase       =      tf_tokenizer(self.paired_sentences )
								lowerCAmelCase       =      tf_tokenizer(
								    text=[sentence[0] for sentence in self.paired_sentences]      ,			text_pair=[sentence[1] for sentence in self.paired_sentences]      ,			)
								for key in merged_outputs.keys():
									self.assertTrue(tf.reduce_all(tf.cast(merged_outputs[key]      ,			tf.intaa ) == separated_outputs[key] ) )


						@slow
						def 							__snake_case       (   self )      ->      Union[str, Any]:
							for tf_tokenizer in self.tf_tokenizers:
								lowerCAmelCase       =      tf.function(lowercase_ )
								for test_inputs in (self.test_sentences, self.paired_sentences):
									lowerCAmelCase       =      tf.constant(lowercase_ )
									lowerCAmelCase       =      compiled_tokenizer(lowercase_ )
									lowerCAmelCase       =      tf_tokenizer(lowercase_ )

									for key in eager_outputs.keys():
										self.assertTrue(tf.reduce_all(eager_outputs[key] == compiled_outputs[key] ) )




						@slow
						def 							__snake_case       (   self )      ->      Union[str, Any]:
							for tf_tokenizer in self.tf_tokenizers:
								lowerCAmelCase       =      ModelToSave(tokenizer=lowercase_ )
								lowerCAmelCase       =      tf.convert_to_tensor(self.test_sentences )
								lowerCAmelCase       =      model(lowercase_ )  # Build model with some sample inputs
								with TemporaryDirectory() as tempdir:
									lowerCAmelCase       =      Path(lowercase_ ) / """saved.model"""
									model.save(lowercase_ )
									lowerCAmelCase       =      tf.keras.models.load_model(lowercase_ )
								lowerCAmelCase       =      loaded_model(lowercase_ )
								# We may see small differences because the loaded model is compiled, so we need an epsilon for the test
								self.assertLessEqual(tf.reduce_max(tf.abs(out - loaded_output ) )      ,			1e-5 )



from __future__ import annotations

_lowerCAmelCase:						str   				=       '#'




class       lowercase_					:





				def __init__(				self)  -> None:
											a__      ={}





				def 						__UpperCamelCase    (				self       ,  lowercase_)  -> None:
											a__      =self._trie
											for char in text:
																		if char not in trie:
																									a__      ={}
																		a__      =trie[char]
											a__      =True





				def 						__UpperCamelCase    (				self       ,  lowercase_)  -> tuple | list:
											a__      =self._trie
											for char in prefix:
																		if char in trie:
																									a__      =trie[char]
																		else:
																									return []
											return self._elements(lowercase_)





				def 						__UpperCamelCase    (				self       ,  lowercase_)  -> tuple:
											a__      =[]
											for c, v in d.items():
																		a__      =[' '] if c == END else [(c + s) for s in self._elements(lowercase_)]
																		result.extend(lowercase_)
											return tuple(lowercase_)







_lowerCAmelCase:						Optional[int]   				=       Trie()
_lowerCAmelCase:						List[str]   				=       ('depart', 'detergent', 'daring', 'dog', 'deer', 'deal')
for word in words:
	trie.insert_word(word)






def   _lowercase(					__a				:						str     ):
							a__      =trie.find_word(__a     )
							return tuple(string + word for word in suffixes     )






def   _lowercase(					):
							print(autocomplete_using_trie('de'     )     )


if __name__ == "__main__":
	import doctest

	doctest.testmod()
	main()

