


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(UpperCAmelCase__							)			,  '''Tatoeba directory does not exist.'''							)
class 							A   (	unittest.TestCase							):
					'''simple docstring'''






					@cached_property
					def   lowerCamelCase__					(self   :						Union[str, Any]		)						->       Optional[int]:




							"""simple docstring"""


							lowercase__					      =		tempfile.mkdtemp()
							return TatoebaConverter(save_dir=_UpperCAmelCase		)

					@slow
					def   lowerCamelCase__					(self   :						List[str]		)						->       Union[str, Any]:




							"""simple docstring"""


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


					@slow
					def   lowerCamelCase__					(self   :						str		)						->       int:




							"""simple docstring"""


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





from typing import TYPE_CHECKING

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


A	:		Dict    =       {'configuration_glpn': ['GLPN_PRETRAINED_CONFIG_ARCHIVE_MAP', 'GLPNConfig']}

try:
	if not is_vision_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	A	:		Tuple    =       ['GLPNFeatureExtractor']
	A	:		List[str]    =       ['GLPNImageProcessor']

try:
	if not is_torch_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	A	:		Optional[int]    =       [
	    'GLPN_PRETRAINED_MODEL_ARCHIVE_LIST',
	    'GLPNForDepthEstimation',
	    'GLPNLayer',
	    'GLPNModel',
	    'GLPNPreTrainedModel',
	]


if TYPE_CHECKING:
	from .configuration_glpn import GLPN_PRETRAINED_CONFIG_ARCHIVE_MAP, GLPNConfig

	try:
		if not is_vision_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .feature_extraction_glpn import GLPNFeatureExtractor
		from .image_processing_glpn import GLPNImageProcessor

	try:
		if not is_torch_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .modeling_glpn import (
		    GLPN_PRETRAINED_MODEL_ARCHIVE_LIST,
		    GLPNForDepthEstimation,
		    GLPNLayer,
		    GLPNModel,
		    GLPNPreTrainedModel,
		)


else:
	import sys

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

