




import shutil
import tempfile
import unittest

from transformers import SPIECE_UNDERLINE, BatchEncoding, MBartaaTokenizer, MBartaaTokenizerFast, is_torch_available
from transformers.testing_utils import (
    get_tests_dir,
    nested_simplify,
    require_sentencepiece,
    require_tokenizers,
    require_torch,
    slow,
)

from ...test_tokenization_common import TokenizerTesterMixin


a_		:						Union[str, Any]             =    get_tests_dir('fixtures/test_sentencepiece.model')

if is_torch_available():
				from transformers.models.mbart.modeling_mbart import shift_tokens_right

a_		:						int             =    25_00_04
a_		:						Union[str, Any]             =    25_00_20

@require_sentencepiece
@require_tokenizers
class 		_snake_case  (  snake_case__   ,    unittest.TestCase					):
			_lowercase		:    Any			     =							MBartaaTokenizer
			_lowercase		:    Union[str, Any]			     =							MBartaaTokenizerFast
			_lowercase		:    List[Any]			     =							True
			_lowercase		:    List[Any]			     =							True






			def    SCREAMING_SNAKE_CASE__    (       self)      ->       Any:
						super().setUp()

						# We have a SentencePiece fixture for testing
						SCREAMING_SNAKE_CASE						= MBartaaTokenizer(lowercase_		,					src_lang='en_XX'		,					tgt_lang='ro_RO'		,					keep_accents=lowercase_)
						tokenizer.save_pretrained(self.tmpdirname)






			def    SCREAMING_SNAKE_CASE__    (       self)      ->       int:
						SCREAMING_SNAKE_CASE						= "<s>"
						SCREAMING_SNAKE_CASE						= 0

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






			def    SCREAMING_SNAKE_CASE__    (       self)      ->       List[str]:
						SCREAMING_SNAKE_CASE						= list(self.get_tokenizer().get_vocab().keys())

						self.assertEqual(vocab_keys[0]		,					'<s>')
						self.assertEqual(vocab_keys[1]		,					'<pad>')
						self.assertEqual(vocab_keys[-1]		,					'<mask>')
						self.assertEqual(len(lowercase_)		,					1054)






			def    SCREAMING_SNAKE_CASE__    (       self)      ->       Dict:
						self.assertEqual(self.get_tokenizer().vocab_size		,					1054)






			def    SCREAMING_SNAKE_CASE__    (       self)      ->       Optional[int]:
						SCREAMING_SNAKE_CASE						= MBartaaTokenizer(lowercase_		,					src_lang='en_XX'		,					tgt_lang='ro_RO'		,					keep_accents=lowercase_)

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

						self.assertListEqual(
						    tokenizer.convert_tokens_to_ids(lowercase_)		,					[value + tokenizer.fairseq_offset for value in [285, 46, 10, 170, 382]]		,					)

						SCREAMING_SNAKE_CASE						= tokenizer.tokenize('I was born in 92000, and this is falsé.')
						self.assertListEqual(
						    lowercase_		,					[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', '.']		,					)
						SCREAMING_SNAKE_CASE						= tokenizer.convert_tokens_to_ids(lowercase_)
						self.assertListEqual(
						    lowercase_		,					[
						        value + tokenizer.fairseq_offset
						        for value in [8, 21, 84, 55, 24, 19, 7, 2, 602, 347, 347, 347, 3, 12, 66, 46, 72, 80, 6, 2, 4]
						    ]		,					)

						SCREAMING_SNAKE_CASE						= tokenizer.convert_ids_to_tokens(lowercase_)
						self.assertListEqual(
						    lowercase_		,					[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    SCREAMING_SNAKE_CASE__    (       self)      ->       Union[str, Any]:
						# fmt: off
						SCREAMING_SNAKE_CASE						= {"input_ids": [[25_0004, 1_1062, 8_2772, 7, 15, 8_2772, 538, 5_1529, 237, 1_7198, 1290, 206, 9, 21_5175, 1314, 136, 1_7198, 1290, 206, 9, 5_6359, 42, 12_2009, 9, 1_6466, 16, 8_7344, 4537, 9, 4717, 7_8381, 6, 15_9958, 7, 15, 2_4480, 618, 4, 527, 2_2693, 5428, 4, 2777, 2_4480, 9874, 4, 4_3523, 594, 4, 803, 1_8392, 3_3189, 18, 4, 4_3523, 2_4447, 1_2399, 100, 2_4955, 8_3658, 9626, 14_4057, 15, 839, 2_2335, 16, 136, 2_4955, 8_3658, 8_3479, 15, 3_9102, 724, 16, 678, 645, 2789, 1328, 4589, 42, 12_2009, 11_5774, 23, 805, 1328, 4_6876, 7, 136, 5_3894, 1940, 4_2227, 4_1159, 1_7721, 823, 425, 4, 2_7512, 9_8722, 206, 136, 5531, 4970, 919, 1_7336, 5, 2], [25_0004, 2_0080, 618, 83, 8_2775, 47, 479, 9, 1517, 73, 5_3894, 333, 8_0581, 11_0117, 1_8811, 5256, 1295, 51, 15_2526, 297, 7986, 390, 12_4416, 538, 3_5431, 214, 98, 1_5044, 2_5737, 136, 7108, 4_3701, 23, 756, 13_5355, 7, 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], [25_0004, 581, 6_3773, 11_9455, 6, 14_7797, 8_8203, 7, 645, 70, 21, 3285, 1_0269, 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]], "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, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 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, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 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=lowercase_		,					model_name='facebook/mbart-large-50'		,					revision='d3913889c59cd5c9e456b269c376325eabad57e2'		,					)







			def    SCREAMING_SNAKE_CASE__    (       self)      ->       Optional[int]:
						if not self.test_slow_tokenizer:
									# as we don't have a slow version, we can't compare the outputs between slow and fast versions
									return

						SCREAMING_SNAKE_CASE						= (self.rust_tokenizer_class, "hf-internal-testing/tiny-random-mbart50", {})
						for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
									with self.subTest(f'''{tokenizer.__class__.__name__} ({pretrained_name})'''):
												SCREAMING_SNAKE_CASE						= self.rust_tokenizer_class.from_pretrained(lowercase_		,					**lowercase_)
												SCREAMING_SNAKE_CASE						= self.tokenizer_class.from_pretrained(lowercase_		,					**lowercase_)

												SCREAMING_SNAKE_CASE						= tempfile.mkdtemp()

												SCREAMING_SNAKE_CASE						= tokenizer_r.save_pretrained(lowercase_)
												SCREAMING_SNAKE_CASE						= tokenizer_p.save_pretrained(lowercase_)

												# Checks it save with the same files + the tokenizer.json file for the fast one
												self.assertTrue(any('tokenizer.json' in f for f in tokenizer_r_files))
												SCREAMING_SNAKE_CASE						= tuple(f for f in tokenizer_r_files if 'tokenizer.json' not in f)
												self.assertSequenceEqual(lowercase_		,					lowercase_)

												# Checks everything loads correctly in the same way
												SCREAMING_SNAKE_CASE						= tokenizer_r.from_pretrained(lowercase_)
												SCREAMING_SNAKE_CASE						= tokenizer_p.from_pretrained(lowercase_)

												# Check special tokens are set accordingly on Rust and Python
												for key in tokenizer_pp.special_tokens_map:
															self.assertTrue(hasattr(lowercase_		,					lowercase_))
															# self.assertEqual(getattr(tokenizer_rp, key), getattr(tokenizer_pp, key))
															# self.assertEqual(getattr(tokenizer_rp, key + "_id"), getattr(tokenizer_pp, key + "_id"))

												shutil.rmtree(lowercase_)

												# Save tokenizer rust, legacy_format=True
												SCREAMING_SNAKE_CASE						= tempfile.mkdtemp()

												SCREAMING_SNAKE_CASE						= tokenizer_r.save_pretrained(lowercase_		,					legacy_format=lowercase_)
												SCREAMING_SNAKE_CASE						= tokenizer_p.save_pretrained(lowercase_)

												# Checks it save with the same files
												self.assertSequenceEqual(lowercase_		,					lowercase_)

												# Checks everything loads correctly in the same way
												SCREAMING_SNAKE_CASE						= tokenizer_r.from_pretrained(lowercase_)
												SCREAMING_SNAKE_CASE						= tokenizer_p.from_pretrained(lowercase_)

												# Check special tokens are set accordingly on Rust and Python
												for key in tokenizer_pp.special_tokens_map:
															self.assertTrue(hasattr(lowercase_		,					lowercase_))

												shutil.rmtree(lowercase_)

												# Save tokenizer rust, legacy_format=False
												SCREAMING_SNAKE_CASE						= tempfile.mkdtemp()

												SCREAMING_SNAKE_CASE						= tokenizer_r.save_pretrained(lowercase_		,					legacy_format=lowercase_)
												SCREAMING_SNAKE_CASE						= tokenizer_p.save_pretrained(lowercase_)

												# Checks it saved the tokenizer.json file
												self.assertTrue(any('tokenizer.json' in f for f in tokenizer_r_files))

												# Checks everything loads correctly in the same way
												SCREAMING_SNAKE_CASE						= tokenizer_r.from_pretrained(lowercase_)
												SCREAMING_SNAKE_CASE						= tokenizer_p.from_pretrained(lowercase_)

												# Check special tokens are set accordingly on Rust and Python
												for key in tokenizer_pp.special_tokens_map:
															self.assertTrue(hasattr(lowercase_		,					lowercase_))

												shutil.rmtree(lowercase_)



@require_torch
@require_sentencepiece
@require_tokenizers
class 		_snake_case  (  unittest.TestCase					):
			_lowercase		:    List[Any]			     =							'''facebook/mbart-large-50-one-to-many-mmt'''
			_lowercase		:    List[str]			     =							[
			    ''' UN Chief Says There Is No Military Solution in Syria''',
			    ''' Secretary-General Ban Ki-moon says his response to Russia\'s stepped up military support for Syria is that \"there is no military solution\" to the nearly five-year conflict and more weapons will only worsen the violence and misery for millions of people.''',
			]
			_lowercase		:    Optional[int]			     =							[
			    '''Şeful ONU declară că nu există o soluţie militară în Siria''',
			    '''Secretarul General Ban Ki-moon declară că răspunsul său la intensificarea sprijinului militar al Rusiei'''
			    ''' pentru Siria este că \"nu există o soluţie militară\" la conflictul de aproape cinci ani şi că noi arme nu vor'''
			    ''' face decât să înrăutăţească violenţele şi mizeria pentru milioane de oameni.''',
			]
			_lowercase		:    Optional[Any]			     =							[EN_CODE, 82_74, 12_78_73, 2_59_16, 7, 86_22, 20_71, 4_38, 6_74_85, 53, 18_78_95, 23, 5_17_12, 2]






			@classmethod
			def    SCREAMING_SNAKE_CASE__    (       cls)      ->       int:
						SCREAMING_SNAKE_CASE						= MBartaaTokenizer.from_pretrained(
						    cls.checkpoint_name		,					src_lang='en_XX'		,					tgt_lang='ro_RO')
						SCREAMING_SNAKE_CASE						= 1
						return cls






			def    SCREAMING_SNAKE_CASE__    (       self)      ->       int:
						self.assertEqual(self.tokenizer.fairseq_tokens_to_ids['ar_AR']		,					25_0001)
						self.assertEqual(self.tokenizer.fairseq_tokens_to_ids['en_EN']		,					25_0004)
						self.assertEqual(self.tokenizer.fairseq_tokens_to_ids['ro_RO']		,					25_0020)
						self.assertEqual(self.tokenizer.fairseq_tokens_to_ids['mr_IN']		,					25_0038)






			def    SCREAMING_SNAKE_CASE__    (       self)      ->       List[str]:
						SCREAMING_SNAKE_CASE						= self.tokenizer.batch_encode_plus(self.src_text).input_ids[0]
						self.assertListEqual(self.expected_src_tokens		,					lowercase_)






			def    SCREAMING_SNAKE_CASE__    (       self)      ->       List[str]:
						self.assertIn(lowercase_		,					self.tokenizer.all_special_ids)
						SCREAMING_SNAKE_CASE						= [RO_CODE, 884, 9019, 96, 9, 916, 8_6792, 36, 1_8743, 1_5596, 5, 2]
						SCREAMING_SNAKE_CASE						= self.tokenizer.decode(lowercase_		,					skip_special_tokens=lowercase_)
						SCREAMING_SNAKE_CASE						= self.tokenizer.decode(generated_ids[1:]		,					skip_special_tokens=lowercase_)
						self.assertEqual(lowercase_		,					lowercase_)
						self.assertNotIn(self.tokenizer.eos_token		,					lowercase_)






			def    SCREAMING_SNAKE_CASE__    (       self)      ->       str:
						SCREAMING_SNAKE_CASE						= ["this is gunna be a long sentence " * 20]
						assert isinstance(src_text[0]		,					lowercase_)
						SCREAMING_SNAKE_CASE						= 10
						SCREAMING_SNAKE_CASE						= self.tokenizer(lowercase_		,					max_length=lowercase_		,					truncation=lowercase_).input_ids[0]
						self.assertEqual(ids[0]		,					lowercase_)
						self.assertEqual(ids[-1]		,					2)
						self.assertEqual(len(lowercase_)		,					lowercase_)






			def    SCREAMING_SNAKE_CASE__    (       self)      ->       int:
						self.assertListEqual(self.tokenizer.convert_tokens_to_ids(['<mask>', 'ar_AR'])		,					[25_0053, 25_0001])






			def    SCREAMING_SNAKE_CASE__    (       self)      ->       List[str]:
						SCREAMING_SNAKE_CASE						= tempfile.mkdtemp()
						SCREAMING_SNAKE_CASE						= self.tokenizer.fairseq_tokens_to_ids
						self.tokenizer.save_pretrained(lowercase_)
						SCREAMING_SNAKE_CASE						= MBartaaTokenizer.from_pretrained(lowercase_)
						self.assertDictEqual(new_tok.fairseq_tokens_to_ids		,					lowercase_)






			@require_torch
			def    SCREAMING_SNAKE_CASE__    (       self)      ->       int:
						SCREAMING_SNAKE_CASE						= self.tokenizer(self.src_text		,					text_target=self.tgt_text		,					padding=lowercase_		,					return_tensors='pt')
						SCREAMING_SNAKE_CASE						= shift_tokens_right(batch['labels']		,					self.tokenizer.pad_token_id)

						# fairseq batch: https://gist.github.com/sshleifer/cba08bc2109361a74ac3760a7e30e4f4
						assert batch.input_ids[1][0] == EN_CODE
						assert batch.input_ids[1][-1] == 2
						assert batch.labels[1][0] == RO_CODE
						assert batch.labels[1][-1] == 2
						assert batch.decoder_input_ids[1][:2].tolist() == [2, RO_CODE]






			@require_torch
			def    SCREAMING_SNAKE_CASE__    (       self)      ->       List[Any]:
						SCREAMING_SNAKE_CASE						= self.tokenizer(
						    self.src_text		,					text_target=self.tgt_text		,					padding=lowercase_		,					truncation=lowercase_		,					max_length=len(self.expected_src_tokens)		,					return_tensors='pt'		,					)
						SCREAMING_SNAKE_CASE						= shift_tokens_right(batch['labels']		,					self.tokenizer.pad_token_id)

						self.assertIsInstance(lowercase_		,					lowercase_)

						self.assertEqual((2, 14)		,					batch.input_ids.shape)
						self.assertEqual((2, 14)		,					batch.attention_mask.shape)
						SCREAMING_SNAKE_CASE						= batch.input_ids.tolist()[0]
						self.assertListEqual(self.expected_src_tokens		,					lowercase_)
						self.assertEqual(2		,					batch.decoder_input_ids[0, 0])  # decoder_start_token_id
						# Test that special tokens are reset
						self.assertEqual(self.tokenizer.prefix_tokens		,					[EN_CODE])
						self.assertEqual(self.tokenizer.suffix_tokens		,					[self.tokenizer.eos_token_id])






			def    SCREAMING_SNAKE_CASE__    (       self)      ->       Optional[int]:
						SCREAMING_SNAKE_CASE						= self.tokenizer(self.src_text		,					padding=lowercase_		,					truncation=lowercase_		,					max_length=3		,					return_tensors='pt')
						SCREAMING_SNAKE_CASE						= self.tokenizer(
						    text_target=self.tgt_text		,					padding=lowercase_		,					truncation=lowercase_		,					max_length=10		,					return_tensors='pt')
						SCREAMING_SNAKE_CASE						= targets["input_ids"]
						SCREAMING_SNAKE_CASE						= shift_tokens_right(lowercase_		,					self.tokenizer.pad_token_id)

						self.assertEqual(batch.input_ids.shape[1]		,					3)
						self.assertEqual(batch.decoder_input_ids.shape[1]		,					10)







			@require_torch
			def    SCREAMING_SNAKE_CASE__    (       self)      ->       List[str]:
						SCREAMING_SNAKE_CASE						= self.tokenizer._build_translation_inputs(
						    'A test'		,					return_tensors='pt'		,					src_lang='en_XX'		,					tgt_lang='ar_AR')

						self.assertEqual(
						    nested_simplify(lowercase_)		,					{
						        # en_XX, A, test, EOS
						        'input_ids': [[25_0004, 62, 3034, 2]],
						        'attention_mask': [[1, 1, 1, 1]],
						        # ar_AR
						        'forced_bos_token_id': 25_0001,
						    }		,					)












from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_sentencepiece_available,
    is_torch_available,
)


a_		:						int             =    {
    'configuration_speecht5': [
        'SPEECHT5_PRETRAINED_CONFIG_ARCHIVE_MAP',
        'SPEECHT5_PRETRAINED_HIFIGAN_CONFIG_ARCHIVE_MAP',
        'SpeechT5Config',
        'SpeechT5HifiGanConfig',
    ],
    'feature_extraction_speecht5': ['SpeechT5FeatureExtractor'],
    'processing_speecht5': ['SpeechT5Processor'],
}

try:
				if not is_sentencepiece_available():
								raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
				pass
else:
				a_		:						Optional[Any]             =    ['SpeechT5Tokenizer']

try:
				if not is_torch_available():
								raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
				pass
else:
				a_		:						Optional[int]             =    [
				    'SPEECHT5_PRETRAINED_MODEL_ARCHIVE_LIST',
				    'SpeechT5ForSpeechToText',
				    'SpeechT5ForSpeechToSpeech',
				    'SpeechT5ForTextToSpeech',
				    'SpeechT5Model',
				    'SpeechT5PreTrainedModel',
				    'SpeechT5HifiGan',
				]

if TYPE_CHECKING:
				from .configuration_speechta import (
				    SPEECHT5_PRETRAINED_CONFIG_ARCHIVE_MAP,
				    SPEECHT5_PRETRAINED_HIFIGAN_CONFIG_ARCHIVE_MAP,
				    SpeechTaConfig,
				    SpeechTaHifiGanConfig,
				)
				from .feature_extraction_speechta import SpeechTaFeatureExtractor
				from .processing_speechta import SpeechTaProcessor

				try:
								if not is_sentencepiece_available():
												raise OptionalDependencyNotAvailable()
				except OptionalDependencyNotAvailable:
								pass
				else:
								from .tokenization_speechta import SpeechTaTokenizer

				try:
								if not is_torch_available():
												raise OptionalDependencyNotAvailable()
				except OptionalDependencyNotAvailable:
								pass
				else:
								from .modeling_speechta import (
								    SPEECHT5_PRETRAINED_MODEL_ARCHIVE_LIST,
								    SpeechTaForSpeechToSpeech,
								    SpeechTaForSpeechToText,
								    SpeechTaForTextToSpeech,
								    SpeechTaHifiGan,
								    SpeechTaModel,
								    SpeechTaPreTrainedModel,
								)

else:
				import sys

				a_		:						Dict             =    _LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)




