"""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   lowerCAmelCase_    (			unittest.TestCase					):



				"""simple docstring"""

				@cached_property
				def 		snake_case (				self    ):






										"""simple docstring"""

										snake_case								=			tempfile.mkdtemp()
										return TatoebaConverter(save_dir=lowerCAmelCase    )

				@slow
				def 		snake_case (				self    ):






										"""simple docstring"""

										self.resolver.convert_models(['heb-eng']    )

				@slow
				def 		snake_case (				self    ):






										"""simple docstring"""

										snake_case					,snake_case								=			self.resolver.write_model_card('opus-mt-he-en'		,    dry_run=lowerCAmelCase    )
										assert mmeta["long_pair"] == "heb-eng"



"""simple docstring"""
from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


SCREAMING_SNAKE_CASE__      						=  {"configuration_sew": ["SEW_PRETRAINED_CONFIG_ARCHIVE_MAP", "SEWConfig"]}

try:
					if not is_torch_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					SCREAMING_SNAKE_CASE__      						=  [
					    "SEW_PRETRAINED_MODEL_ARCHIVE_LIST",
					    "SEWForCTC",
					    "SEWForSequenceClassification",
					    "SEWModel",
					    "SEWPreTrainedModel",
					]

if TYPE_CHECKING:
					from .configuration_sew import SEW_PRETRAINED_CONFIG_ARCHIVE_MAP, SEWConfig

					try:
										if not is_torch_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .modeling_sew import (
										    SEW_PRETRAINED_MODEL_ARCHIVE_LIST,
										    SEWForCTC,
										    SEWForSequenceClassification,
										    SEWModel,
										    SEWPreTrainedModel,
										)


else:
					import sys

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


