





'''simple docstring'''







import unittest

from transformers import AlbertTokenizer, AlbertTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow

from ...test_tokenization_common import TokenizerTesterMixin


lowerCAmelCase_					:    Dict      	=			get_tests_dir('fixtures/spiece.model')
@require_sentencepiece
@require_tokenizers
class 				__SCREAMING_SNAKE_CASE  (lowerCamelCase_       ,							unittest.TestCase      ):






				"""simple docstring"""







				__a            =AlbertTokenizer
				__a            =AlbertTokenizerFast
				__a            =True
				__a            =True
				__a            =True




				def   UpperCamelCase__   (  self     :					List[str]					):
								super().setUp()

								# We have a SentencePiece fixture for testing
								_a								= AlbertTokenizer(__a					)
								tokenizer.save_pretrained(self.tmpdirname					)




				def   UpperCamelCase__   (  self     :					Dict					,				__a     :					int					):
								_a								= "this is a test"
								_a								= "this is a test"
								return input_text, output_text




				def   UpperCamelCase__   (  self     :					Any					):
								_a								= "<pad>"
								_a								= 0

								self.assertEqual(self.get_tokenizer()._convert_token_to_id(__a					)					,				__a					)
								self.assertEqual(self.get_tokenizer()._convert_id_to_token(__a					)					,				__a					)




				def   UpperCamelCase__   (  self     :					List[Any]					):
								_a								= list(self.get_tokenizer().get_vocab().keys()					)

								self.assertEqual(vocab_keys[0]					,				"<pad>"					)
								self.assertEqual(vocab_keys[1]					,				"<unk>"					)
								self.assertEqual(vocab_keys[-1]					,				"▁eloquent"					)
								self.assertEqual(len(__a					)					,				3_00_00					)




				def   UpperCamelCase__   (  self     :					Union[str, Any]					):
								self.assertEqual(self.get_tokenizer().vocab_size					,				3_00_00					)




				def   UpperCamelCase__   (  self     :					Dict					):
								if not self.test_rust_tokenizer:
												return

								_a								= self.get_tokenizer()
								_a								= self.get_rust_tokenizer()

								_a								= "I was born in 92000, and this is falsé."

								_a								= tokenizer.tokenize(__a					)
								_a								= rust_tokenizer.tokenize(__a					)
								self.assertListEqual(__a					,				__a					)

								_a								= tokenizer.encode(__a					,				add_special_tokens=__a					)
								_a								= rust_tokenizer.encode(__a					,				add_special_tokens=__a					)
								self.assertListEqual(__a					,				__a					)

								_a								= self.get_rust_tokenizer()
								_a								= tokenizer.encode(__a					)
								_a								= rust_tokenizer.encode(__a					)
								self.assertListEqual(__a					,				__a					)




				def   UpperCamelCase__   (  self     :					Dict					):
								_a								= AlbertTokenizer(__a					,				keep_accents=__a					)

								_a								= tokenizer.tokenize("This is a test"					)
								self.assertListEqual(__a					,				["▁this", "▁is", "▁a", "▁test"]					)

								self.assertListEqual(tokenizer.convert_tokens_to_ids(__a					)					,				[48, 25, 21, 12_89]					)

								_a								= tokenizer.tokenize("I was born in 92000, and this is falsé."					)
								self.assertListEqual(
								    __a					,				["▁i", "▁was", "▁born", "▁in", "▁9", "2000", ",", "▁and", "▁this", "▁is", "▁fal", "s", "é", "."]					)
								_a								= tokenizer.convert_tokens_to_ids(__a					)
								self.assertListEqual(__a					,				[31, 23, 3_86, 19, 5_61, 30_50, 15, 17, 48, 25, 82_56, 18, 1, 9]					)

								_a								= tokenizer.convert_ids_to_tokens(__a					)
								self.assertListEqual(
								    __a					,				["▁i", "▁was", "▁born", "▁in", "▁9", "2000", ",", "▁and", "▁this", "▁is", "▁fal", "s", "<unk>", "."]					,				)




				def   UpperCamelCase__   (  self     :					int					):
								_a								= AlbertTokenizer(__a					)

								_a								= tokenizer.encode("sequence builders"					)
								_a								= tokenizer.encode("multi-sequence build"					)

								_a								= tokenizer.build_inputs_with_special_tokens(__a					)
								_a								= tokenizer.build_inputs_with_special_tokens(__a					,				__a					)

								assert encoded_sentence == [tokenizer.cls_token_id] + text + [tokenizer.sep_token_id]
								assert encoded_pair == [tokenizer.cls_token_id] + text + [tokenizer.sep_token_id] + text_a + [
								    tokenizer.sep_token_id
								]




				@slow
				def   UpperCamelCase__   (  self     :					str					):
								# fmt: off
								_a								= {"attention_mask": [[1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]], "input_ids": [[2, 2_19_70, 13, 5, 60_92, 1_67, 28, 71_03, 21_53, 6_73, 8, 70_28, 1_20_51, 18, 17, 71_03, 21_53, 6_73, 8, 35_15, 1_86_84, 8, 44_61, 6, 19_27, 2_97, 8, 1_20_60, 26_07, 18, 13, 5, 44_61, 15, 1_05_38, 38, 8, 1_35, 15, 8_22, 58, 15, 9_93, 1_03_63, 15, 14_60, 80_05, 44_61, 15, 9_93, 2_55, 23_28, 9, 9, 9, 6, 26, 11_12, 8_16, 32_60, 13, 5, 1_03, 23_77, 6, 17, 11_12, 8_16, 27_82, 13, 5, 1_03, 1_06_41, 6, 29, 84, 25_12, 24_30, 7_82, 1_86_84, 27_61, 19, 8_08, 24_30, 25_56, 17, 8_55, 14_80, 94_77, 40_91, 1_28, 1_17_12, 15, 71_03, 21_53, 6_73, 17, 2_48_83, 99_90, 9, 3], [2, 1_15_02, 25, 10_06, 20, 7_82, 8, 1_18_09, 8_55, 17_32, 1_93_93, 1_86_67, 37, 3_67, 2_10_18, 69, 18_54, 34, 1_18_60, 1_91_24, 27, 1_56, 2_25, 17, 1_93, 41_41, 19, 65, 91_24, 9, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [2, 14, 22_31, 8_86, 23_85, 1_76_59, 84, 14, 1_67_92, 19_52, 9, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]], "token_type_ids": [[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]]}  # noqa: E501
								# fmt: on

								self.tokenizer_integration_test_util(
								    expected_encoding=__a					,				model_name="albert-base-v2"					,				revision="6b6560eaf5ff2e250b00c50f380c5389a9c2d82e"					,				)







'''simple docstring'''







from typing import TYPE_CHECKING

from ...file_utils import _LazyModule, is_tokenizers_available, is_torch_available
from ...utils import OptionalDependencyNotAvailable


lowerCAmelCase_					:    int      	=			{'configuration_gpt_neox': ['GPT_NEOX_PRETRAINED_CONFIG_ARCHIVE_MAP', 'GPTNeoXConfig']}

try:
					if not is_tokenizers_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					lowerCAmelCase_					:    Optional[int]      	=			['GPTNeoXTokenizerFast']

try:
					if not is_torch_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					lowerCAmelCase_					:    List[str]      	=			[
					    'GPT_NEOX_PRETRAINED_MODEL_ARCHIVE_LIST',
					    'GPTNeoXForCausalLM',
					    'GPTNeoXForQuestionAnswering',
					    'GPTNeoXForSequenceClassification',
					    'GPTNeoXForTokenClassification',
					    'GPTNeoXLayer',
					    'GPTNeoXModel',
					    'GPTNeoXPreTrainedModel',
					]


if TYPE_CHECKING:
					from .configuration_gpt_neox import GPT_NEOX_PRETRAINED_CONFIG_ARCHIVE_MAP, GPTNeoXConfig

					try:
										if not is_tokenizers_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .tokenization_gpt_neox_fast import GPTNeoXTokenizerFast

					try:
										if not is_torch_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .modeling_gpt_neox import (
										    GPT_NEOX_PRETRAINED_MODEL_ARCHIVE_LIST,
										    GPTNeoXForCausalLM,
										    GPTNeoXForQuestionAnswering,
										    GPTNeoXForSequenceClassification,
										    GPTNeoXForTokenClassification,
										    GPTNeoXLayer,
										    GPTNeoXModel,
										    GPTNeoXPreTrainedModel,
										)


else:
					import sys

					lowerCAmelCase_					:    List[str]      	=			_LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)
