



'''simple docstring'''






import os
import tempfile
import unittest

from transformers.models.marian.convert_marian_tatoeba_to_pytorch import DEFAULT_REPO, TatoebaConverter
from transformers.testing_utils import slow
from transformers.utils import cached_property

@unittest.skipUnless(os.path.exists(lowerCamelCase__     )		,			"""Tatoeba directory does not exist."""     )
class 							a__( unittest.TestCase     ):







    @cached_property
    def       lowercase_	(				self			:  Optional[int]     ):
      a						: List[Any]					       =					tempfile.mkdtemp()
      return TatoebaConverter(save_dir=__snake_case     )







    @slow
    def       lowercase_	(				self			:  int     ):
      self.resolver.convert_models(['heb-eng']     )







    @slow
    def       lowercase_	(				self			:  List[str]     ):
      a						: Optional[int]					       =					self.resolver.write_model_card('opus-mt-he-en'						,      dry_run=__snake_case     )
      assert mmeta["long_pair"] == "heb-eng"




'''simple docstring'''






from typing import TYPE_CHECKING

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


lowerCAmelCase: Any							=						{
    'configuration_poolformer': [
        'POOLFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP',
        'PoolFormerConfig',
        'PoolFormerOnnxConfig',
    ]
}

try:
     if not is_vision_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     lowerCAmelCase: List[str]							=						['PoolFormerFeatureExtractor']
     lowerCAmelCase: Tuple							=						['PoolFormerImageProcessor']

try:
     if not is_torch_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     lowerCAmelCase: str							=						[
         'POOLFORMER_PRETRAINED_MODEL_ARCHIVE_LIST',
         'PoolFormerForImageClassification',
         'PoolFormerModel',
         'PoolFormerPreTrainedModel',
     ]


if TYPE_CHECKING:
     from .configuration_poolformer import (
         POOLFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP,
         PoolFormerConfig,
         PoolFormerOnnxConfig,
     )

     try:
          if not is_vision_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .feature_extraction_poolformer import PoolFormerFeatureExtractor
          from .image_processing_poolformer import PoolFormerImageProcessor

     try:
          if not is_torch_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .modeling_poolformer import (
              POOLFORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
              PoolFormerForImageClassification,
              PoolFormerModel,
              PoolFormerPreTrainedModel,
          )


else:
     import sys

     lowerCAmelCase: Dict							=						_LazyModule(__name__, globals()['__file__'], _import_structure)