






# this script builds a small sample spm file tests/fixtures/test_sentencepiece_no_bos.model, with features needed by pegasus

# 1. pip install sentencepiece
#
# 2. wget https://raw.githubusercontent.com/google/sentencepiece/master/data/botchan.txt

# 3. build
import sentencepiece as spm

# pegasus:
# 1. no bos
# 2. eos_id is 1
# 3. unk_id is 2
# build a sample spm file accordingly
spm.SentencePieceTrainer.train(
    '''--input=botchan.txt --model_prefix=test_sentencepiece_no_bos --bos_id=-1 --unk_id=2  --eos_id=1  --vocab_size=1000'''
)

# 4. now update the fixture
# mv test_sentencepiece_no_bos.model ../../tests/fixtures/








from typing import TYPE_CHECKING

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


UpperCAmelCase_					:		int           = {
    '''configuration_unispeech_sat''': ['''UNISPEECH_SAT_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''UniSpeechSatConfig'''],
}

try:
	if not is_torch_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	UpperCAmelCase_					:		Tuple           = [
	    '''UNISPEECH_SAT_PRETRAINED_MODEL_ARCHIVE_LIST''',
	    '''UniSpeechSatForAudioFrameClassification''',
	    '''UniSpeechSatForCTC''',
	    '''UniSpeechSatForPreTraining''',
	    '''UniSpeechSatForSequenceClassification''',
	    '''UniSpeechSatForXVector''',
	    '''UniSpeechSatModel''',
	    '''UniSpeechSatPreTrainedModel''',
	]

if TYPE_CHECKING:
	from .configuration_unispeech_sat import UNISPEECH_SAT_PRETRAINED_CONFIG_ARCHIVE_MAP, UniSpeechSatConfig

	try:
		if not is_torch_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .modeling_unispeech_sat import (
		    UNISPEECH_SAT_PRETRAINED_MODEL_ARCHIVE_LIST,
		    UniSpeechSatForAudioFrameClassification,
		    UniSpeechSatForCTC,
		    UniSpeechSatForPreTraining,
		    UniSpeechSatForSequenceClassification,
		    UniSpeechSatForXVector,
		    UniSpeechSatModel,
		    UniSpeechSatPreTrainedModel,
		)

else:
	import sys

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