"""simple docstring"""




from typing import TYPE_CHECKING

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


__lowerCamelCase											=  {
    "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:
				__lowerCamelCase											=  ["SpeechT5Tokenizer"]

try:
				if not is_torch_available():
								raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
				pass
else:
				__lowerCamelCase											=  [
				    "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

				__lowerCamelCase											=  _LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)






"""simple docstring"""




import os
import unittest

from transformers.models.cpmant.tokenization_cpmant import VOCAB_FILES_NAMES, CpmAntTokenizer
from transformers.testing_utils import require_jieba, tooslow

from ...test_tokenization_common import TokenizerTesterMixin
@require_jieba
class     UpperCamelCase__(			__A		,						unittest.TestCase ):
						lowerCAmelCase__  :						Optional[int]													=		CpmAntTokenizer
						lowerCAmelCase__  :						List[str]													=		False





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

													A__	     =							[
													    '<d>',
													    '</d>',
													    '<s>',
													    '</s>',
													    '</_>',
													    '<unk>',
													    '<pad>',
													    '</n>',
													    '我',
													    '是',
													    'C',
													    'P',
													    'M',
													    'A',
													    'n',
													    't',
													]
													A__	     =							os.path.join(self.tmpdirname		,VOCAB_FILES_NAMES['vocab_file']     )
													with open(self.vocab_file		,'w'		,encoding='utf-8'     ) as vocab_writer:
																				vocab_writer.write(''.join([x + '\n' for x in vocab_tokens]     )     )





						@tooslow
						def 				snake_case__	(       self     )					->				List[Any]:
													A__	     =							CpmAntTokenizer.from_pretrained('openbmb/cpm-ant-10b'     )
													A__	     =							'今天天气真好！'
													A__	     =							['今天', '天气', '真', '好', '！']
													A__	     =							tokenizer.tokenize(__UpperCAmelCase     )
													self.assertListEqual(__UpperCAmelCase		,__UpperCAmelCase     )
													A__	     =							'今天天气真好！'
													A__	     =							[tokenizer.bos_token] + tokens

													A__	     =							[6, 98_02, 1_49_62, 20_82, 8_31, 2_44]
													self.assertListEqual(tokenizer.convert_tokens_to_ids(__UpperCAmelCase     )		,__UpperCAmelCase     )

													A__	     =							tokenizer.decode(__UpperCAmelCase     )
													self.assertEqual(__UpperCAmelCase		,__UpperCAmelCase     )





