"""simple docstring"""







from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available


_SCREAMING_SNAKE_CASE  :		List[Any]        =      {
    '''configuration_deformable_detr''': ['''DEFORMABLE_DETR_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''DeformableDetrConfig'''],
}

try:
     if not is_vision_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     _SCREAMING_SNAKE_CASE  :		Optional[Any]        =      ['''DeformableDetrFeatureExtractor''']
     _SCREAMING_SNAKE_CASE  :		List[str]        =      ['''DeformableDetrImageProcessor''']

try:
     if not is_torch_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     _SCREAMING_SNAKE_CASE  :		Union[str, Any]        =      [
         '''DEFORMABLE_DETR_PRETRAINED_MODEL_ARCHIVE_LIST''',
         '''DeformableDetrForObjectDetection''',
         '''DeformableDetrModel''',
         '''DeformableDetrPreTrainedModel''',
     ]


if TYPE_CHECKING:
     from .configuration_deformable_detr import DEFORMABLE_DETR_PRETRAINED_CONFIG_ARCHIVE_MAP, DeformableDetrConfig

     try:
          if not is_vision_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .feature_extraction_deformable_detr import DeformableDetrFeatureExtractor
          from .image_processing_deformable_detr import DeformableDetrImageProcessor

     try:
          if not is_torch_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .modeling_deformable_detr import (
              DEFORMABLE_DETR_PRETRAINED_MODEL_ARCHIVE_LIST,
              DeformableDetrForObjectDetection,
              DeformableDetrModel,
              DeformableDetrPreTrainedModel,
          )

else:
     import sys

     _SCREAMING_SNAKE_CASE  :		Tuple        =      _LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)







"""simple docstring"""







# 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/






