
from typing import TYPE_CHECKING

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


UpperCAmelCase	      = {
    '''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:
	UpperCAmelCase	      = ['''SpeechT5Tokenizer''']

try:
	if not is_torch_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	UpperCAmelCase	      = [
	    '''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

	UpperCAmelCase	      = _LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)



import pprint

import requests

UpperCAmelCase	      = '''https://zenquotes.io/api'''






def 							UpperCAmelCase_		(							):
	return requests.get(API_ENDPOINT_URL + '/today'							).json()






def 							UpperCAmelCase_		(							):
	return requests.get(API_ENDPOINT_URL + '/random'							).json()


if __name__ == "__main__":
	UpperCAmelCase	      = random_quotes()
	pprint.pprint(response)

