


import unittest
from pathlib import Path
from shutil import copyfile

from transformers import SPIECE_UNDERLINE, is_sentencepiece_available
from transformers.models.speech_to_text import SpeechaTextTokenizer
from transformers.models.speech_to_text.tokenization_speech_to_text import VOCAB_FILES_NAMES, save_json
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow

from ...test_tokenization_common import TokenizerTesterMixin


snake_case							: List[str]      =   get_tests_dir('''fixtures/test_sentencepiece.model''')

if is_sentencepiece_available():
						import sentencepiece as sp


snake_case							: Optional[int]      =   5
snake_case							: Optional[int]      =   10







@require_sentencepiece
@require_tokenizers
class  snake_case_     (lowerCamelCase_			,		unittest.TestCase   ):
					UpperCAmelCase__      :					Optional[Any]					   =    SpeechaTextTokenizer
					UpperCAmelCase__      :					Union[str, Any]					   =    False
					UpperCAmelCase__      :					Optional[int]					   =    True
					def 				lowerCamelCase__(   self     :Any   )      ->					Union[str, Any]:
												super().setUp()

												a__    =  sp.SentencePieceProcessor()
												spm_model.Load(__snake_case   )
												a__    =  ['<s>', '<pad>', '</s>', '<unk>']

												vocab += [spm_model.IdToPiece(id_   ) for id_ in range(len(__snake_case   )   )]
												a__    =  dict(zip(__snake_case    ,range(len(__snake_case   )   )   )   )

												a__    =  Path(self.tmpdirname   )
												save_json(__snake_case    ,save_dir / VOCAB_FILES_NAMES['vocab_file']   )
												if not (save_dir / VOCAB_FILES_NAMES["spm_file"]).exists():
																			copyfile(__snake_case    ,save_dir / VOCAB_FILES_NAMES['spm_file']   )

												a__    =  SpeechaTextTokenizer.from_pretrained(self.tmpdirname   )
												tokenizer.save_pretrained(self.tmpdirname   )
					def 				lowerCamelCase__(   self     :List[str]   )      ->					Union[str, Any]:
												a__    =  '<pad>'
												a__    =  1

												self.assertEqual(self.get_tokenizer()._convert_token_to_id(__snake_case   )    ,__snake_case   )
												self.assertEqual(self.get_tokenizer()._convert_id_to_token(__snake_case   )    ,__snake_case   )
					def 				lowerCamelCase__(   self     :List[str]   )      ->					Union[str, Any]:
												a__    =  list(self.get_tokenizer().get_vocab().keys()   )

												self.assertEqual(vocab_keys[0]    ,'<s>'   )
												self.assertEqual(vocab_keys[1]    ,'<pad>'   )
												self.assertEqual(vocab_keys[-1]    ,'j'   )
												self.assertEqual(len(__snake_case   )    ,10_01   )
					def 				lowerCamelCase__(   self     :Optional[Any]   )      ->					Optional[int]:
												self.assertEqual(self.get_tokenizer().vocab_size    ,10_01   )
					def 				lowerCamelCase__(   self     :List[str]   )      ->					List[Any]:
												a__    =  SpeechaTextTokenizer.from_pretrained(self.tmpdirname   )

												a__    =  tokenizer.tokenize('This is a test'   )
												self.assertListEqual(__snake_case    ,['▁This', '▁is', '▁a', '▁t', 'est']   )

												self.assertListEqual(
												    tokenizer.convert_tokens_to_ids(__snake_case   )    ,[2_89, 50, 14, 1_74, 3_86]    ,)

												a__    =  tokenizer.tokenize('I was born in 92000, and this is falsé.'   )
												self.assertListEqual(
												    __snake_case    ,[SPIECE_UNDERLINE + 'I', SPIECE_UNDERLINE + 'was', SPIECE_UNDERLINE + 'b', 'or', 'n', SPIECE_UNDERLINE + 'in', SPIECE_UNDERLINE + '', '9', '2', '0', '0', '0', ',', SPIECE_UNDERLINE + 'and', SPIECE_UNDERLINE + 'this', SPIECE_UNDERLINE + 'is', SPIECE_UNDERLINE + 'f', 'al', 's', 'é', '.']    ,)
												a__    =  tokenizer.convert_tokens_to_ids(__snake_case   )
												self.assertListEqual(__snake_case    ,[12, 25, 88, 59, 28, 23, 11, 4, 6_06, 3_51, 3_51, 3_51, 7, 16, 70, 50, 76, 84, 10, 4, 8]   )

												a__    =  tokenizer.convert_ids_to_tokens(__snake_case   )
												self.assertListEqual(
												    __snake_case    ,[SPIECE_UNDERLINE + 'I', SPIECE_UNDERLINE + 'was', SPIECE_UNDERLINE + 'b', 'or', 'n', SPIECE_UNDERLINE + 'in', SPIECE_UNDERLINE + '', '<unk>', '2', '0', '0', '0', ',', SPIECE_UNDERLINE + 'and', SPIECE_UNDERLINE + 'this', SPIECE_UNDERLINE + 'is', SPIECE_UNDERLINE + 'f', 'al', 's', '<unk>', '.']    ,)



					@slow
					def 				lowerCamelCase__(   self     :Any   )      ->					List[Any]:
												# fmt: off
												a__    =  {'input_ids': [[37_91, 7_97, 31, 11, 64, 7_97, 31, 24_29, 4_33, 12, 11_76, 12, 20, 7_86, 9_15, 1_42, 24_13, 2_40, 37, 32_38, 7_97, 31, 11, 35, 93, 9_15, 1_42, 24_13, 2_40, 37, 55_40, 5_67, 12_76, 93, 37, 6_10, 40, 62, 4_55, 6_57, 10_42, 1_23, 7_80, 1_77, 37, 3_09, 2_41, 12_98, 5_14, 20, 2_92, 27_37, 1_14, 24_69, 2_41, 85, 64, 3_02, 5_48, 5_28, 4_23, 4, 5_09, 4_06, 4_23, 37, 6_01, 4, 7_77, 3_02, 5_48, 5_28, 4_23, 2_84, 4, 33_88, 5_11, 4_59, 4, 35_55, 40, 3_21, 3_02, 7_05, 4, 33_88, 5_11, 5_83, 3_26, 5, 5, 5, 62, 33_10, 5_60, 1_77, 26_80, 2_17, 15_08, 32, 31, 8_53, 4_18, 64, 5_83, 5_11, 16_05, 62, 35, 93, 5_60, 1_77, 26_80, 2_17, 15_08, 15_21, 64, 5_83, 5_11, 5_19, 62, 20, 15_15, 7_64, 20, 1_49, 2_61, 56_25, 79_72, 20, 55_40, 5_67, 12_76, 93, 39_25, 16_75, 11, 15, 8_02, 79_72, 5_76, 2_17, 15_08, 11, 35, 93, 12_53, 24_41, 15, 2_89, 6_52, 31, 4_16, 3_21, 38_42, 1_15, 40, 9_11, 8, 4_76, 6_19, 4, 3_80, 1_42, 4_23, 3_35, 2_40, 35, 93, 2_64, 8, 11, 3_35, 5_69, 4_20, 1_63, 5, 2], [2_60, 5_48, 5_28, 4_23, 20, 4_51, 20, 26_81, 11_53, 34_34, 20, 55_40, 37, 5_67, 1_26, 12_53, 24_41, 33_76, 4_49, 2_10, 4_31, 15_63, 1_77, 7_67, 55_40, 11, 12_03, 4_72, 11, 29_53, 6_85, 2_85, 3_64, 7_06, 11_53, 20, 67_99, 20, 28_69, 20, 44_64, 1_26, 40, 24_29, 20, 10_40, 8_66, 26_64, 4_18, 20, 3_18, 20, 17_26, 1_86, 20, 2_65, 5_22, 35, 93, 21_91, 46_34, 20, 10_40, 12, 67_99, 15, 2_28, 23_56, 1_42, 31, 11, 5, 2, 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], [25_75, 26_66, 6_84, 15_82, 11_76, 12, 6_27, 1_49, 6_19, 20, 49_02, 5_63, 11, 20, 1_49, 2_61, 34_20, 23_56, 1_74, 1_42, 47_14, 1_31, 5, 2, 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, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1]], '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, 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, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 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, 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, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 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=__snake_case    ,model_name='facebook/s2t-small-mustc-en-de-st'    ,revision='a14f04cf0776c02f62a8cb800cf7909e15ea23ad'    ,)







@require_sentencepiece
class  snake_case_     (unittest.TestCase   ):
					UpperCAmelCase__      :					Optional[Any]					   =    '''valhalla/s2t_mustc_multilinguial_medium'''

					UpperCAmelCase__      :					str					   =    '''C\'est trop cool'''
					UpperCAmelCase__      :					Optional[Any]					   =    '''Esto es genial'''
					@classmethod
					def 				lowerCamelCase__(   cls     :Any   )      ->					str:
												a__    =  SpeechaTextTokenizer.from_pretrained(cls.checkpoint_name   )
												return cls
					def 				lowerCamelCase__(   self     :Optional[Any]   )      ->					str:
												self.assertEqual(self.tokenizer.lang_code_to_id['pt']    ,4   )
												self.assertEqual(self.tokenizer.lang_code_to_id['ru']    ,6   )
												self.assertEqual(self.tokenizer.lang_code_to_id['it']    ,9   )
												self.assertEqual(self.tokenizer.lang_code_to_id['de']    ,11   )
					def 				lowerCamelCase__(   self     :Any   )      ->					str:
												self.assertEqual(self.tokenizer.vocab_size    ,1_00_00   )
					def 				lowerCamelCase__(   self     :Any   )      ->					List[str]:
												self.assertIn(__snake_case    ,self.tokenizer.all_special_ids   )
												a__    =  [ES_CODE, 4, 16_01, 47, 76_47, 2]
												a__    =  self.tokenizer.decode(__snake_case    ,skip_special_tokens=__snake_case   )
												a__    =  self.tokenizer.decode(generated_ids[1:]    ,skip_special_tokens=__snake_case   )
												self.assertEqual(__snake_case    ,__snake_case   )
												self.assertNotIn(self.tokenizer.eos_token    ,__snake_case   )
					def 				lowerCamelCase__(   self     :Tuple   )      ->					int:
												a__    =  'fr'
												a__    =  self.tokenizer(self.french_text   ).input_ids
												self.assertEqual(encoded[0]    ,__snake_case   )
												self.assertEqual(encoded[-1]    ,self.tokenizer.eos_token_id   )



					def 				lowerCamelCase__(   self     :Any   )      ->					Optional[int]:
												a__    =  'fr'
												self.assertListEqual(self.tokenizer.prefix_tokens    ,[FR_CODE]   )

												a__    =  'es'
												self.assertListEqual(self.tokenizer.prefix_tokens    ,[ES_CODE]   )








from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_tf_available,
    is_torch_available,
    is_vision_available,
)


snake_case							: Any      =   {
    '''configuration_mobilevit''': ['''MOBILEVIT_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''MobileViTConfig''', '''MobileViTOnnxConfig'''],
}

try:
						if not is_vision_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						snake_case							: Union[str, Any]      =   ['''MobileViTFeatureExtractor''']
						snake_case							: int      =   ['''MobileViTImageProcessor''']

try:
						if not is_torch_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						snake_case							: Dict      =   [
						    '''MOBILEVIT_PRETRAINED_MODEL_ARCHIVE_LIST''',
						    '''MobileViTForImageClassification''',
						    '''MobileViTForSemanticSegmentation''',
						    '''MobileViTModel''',
						    '''MobileViTPreTrainedModel''',
						]

try:
						if not is_tf_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						snake_case							: Tuple      =   [
						    '''TF_MOBILEVIT_PRETRAINED_MODEL_ARCHIVE_LIST''',
						    '''TFMobileViTForImageClassification''',
						    '''TFMobileViTForSemanticSegmentation''',
						    '''TFMobileViTModel''',
						    '''TFMobileViTPreTrainedModel''',
						]

if TYPE_CHECKING:
						from .configuration_mobilevit import MOBILEVIT_PRETRAINED_CONFIG_ARCHIVE_MAP, MobileViTConfig, MobileViTOnnxConfig

						try:
												if not is_vision_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .feature_extraction_mobilevit import MobileViTFeatureExtractor
												from .image_processing_mobilevit import MobileViTImageProcessor

						try:
												if not is_torch_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .modeling_mobilevit import (
												    MOBILEVIT_PRETRAINED_MODEL_ARCHIVE_LIST,
												    MobileViTForImageClassification,
												    MobileViTForSemanticSegmentation,
												    MobileViTModel,
												    MobileViTPreTrainedModel,
												)

						try:
												if not is_tf_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .modeling_tf_mobilevit import (
												    TF_MOBILEVIT_PRETRAINED_MODEL_ARCHIVE_LIST,
												    TFMobileViTForImageClassification,
												    TFMobileViTForSemanticSegmentation,
												    TFMobileViTModel,
												    TFMobileViTPreTrainedModel,
												)


else:
						import sys

						snake_case							: Optional[int]      =   _LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)




