

"""simple docstring"""




from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


_lowercase   :	Dict												=						{
    'configuration_clap': [
        'CLAP_PRETRAINED_MODEL_ARCHIVE_LIST',
        'ClapAudioConfig',
        'ClapConfig',
        'ClapTextConfig',
    ],
    'processing_clap': ['ClapProcessor'],
}

try:
				if not is_torch_available():
								raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
				pass
else:
				_lowercase   :	Optional[int]												=						[
				    'CLAP_PRETRAINED_MODEL_ARCHIVE_LIST',
				    'ClapModel',
				    'ClapPreTrainedModel',
				    'ClapTextModel',
				    'ClapTextModelWithProjection',
				    'ClapAudioModel',
				    'ClapAudioModelWithProjection',
				]
				_lowercase   :	Union[str, Any]												=						['ClapFeatureExtractor']

if TYPE_CHECKING:
				from .configuration_clap import (
				    CLAP_PRETRAINED_MODEL_ARCHIVE_LIST,
				    ClapAudioConfig,
				    ClapConfig,
				    ClapTextConfig,
				)
				from .processing_clap import ClapProcessor

				try:
								if not is_torch_available():
												raise OptionalDependencyNotAvailable()
				except OptionalDependencyNotAvailable:
								pass
				else:
								from .feature_extraction_clap import ClapFeatureExtractor
								from .modeling_clap import (
								    CLAP_PRETRAINED_MODEL_ARCHIVE_LIST,
								    ClapAudioModel,
								    ClapAudioModelWithProjection,
								    ClapModel,
								    ClapPreTrainedModel,
								    ClapTextModel,
								    ClapTextModelWithProjection,
								)


else:
				import sys

				_lowercase   :	Optional[Any]												=						_LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)

'''simple docstring'''


from tempfile import TemporaryDirectory
from unittest import TestCase
from unittest.mock import MagicMock, patch

from transformers import AutoModel, TFAutoModel
from transformers.onnx import FeaturesManager
from transformers.testing_utils import SMALL_MODEL_IDENTIFIER, require_tf, require_torch






@require_torch
@require_tf
class     A ( UpperCAmelCase ):





							def    snake_case__    (   self					:				str						)				->						Any:
								__UpperCAmelCase      					=      SMALL_MODEL_IDENTIFIER
								__UpperCAmelCase      					=      '''pt'''
								__UpperCAmelCase      					=      '''tf'''





							def    snake_case__    (   self					:				int  ,		__a					:				int						)				->						Union[str, Any]:
								__UpperCAmelCase      					=      AutoModel.from_pretrained(self.test_model						)
								model_pt.save_pretrained(__a						)





							def    snake_case__    (   self					:				Any  ,		__a					:				Optional[int]						)				->						Tuple:
								__UpperCAmelCase      					=      TFAutoModel.from_pretrained(self.test_model  ,		from_pt=__a						)
								model_tf.save_pretrained(__a						)





							def    snake_case__    (   self					:				Dict						)				->						Dict:
								__UpperCAmelCase      					=      '''mock_framework'''

								# Framework provided - return whatever the user provides
								__UpperCAmelCase      					=      FeaturesManager.determine_framework(self.test_model  ,		__a						)
								self.assertEqual(__a  ,		__a						)

								# Local checkpoint and framework provided - return provided framework
								# PyTorch checkpoint
								with TemporaryDirectory() as local_pt_ckpt:
									self._setup_pt_ckpt(__a						)
									__UpperCAmelCase      					=      FeaturesManager.determine_framework(__a  ,		__a						)
									self.assertEqual(__a  ,		__a						)

								# TensorFlow checkpoint
								with TemporaryDirectory() as local_tf_ckpt:
									self._setup_tf_ckpt(__a						)
									__UpperCAmelCase      					=      FeaturesManager.determine_framework(__a  ,		__a						)
									self.assertEqual(__a  ,		__a						)





							def    snake_case__    (   self					:				Dict						)				->						List[str]:
								# PyTorch checkpoint
								with TemporaryDirectory() as local_pt_ckpt:
									self._setup_pt_ckpt(__a						)
									__UpperCAmelCase      					=      FeaturesManager.determine_framework(__a						)
									self.assertEqual(__a  ,		self.framework_pt						)

								# TensorFlow checkpoint
								with TemporaryDirectory() as local_tf_ckpt:
									self._setup_tf_ckpt(__a						)
									__UpperCAmelCase      					=      FeaturesManager.determine_framework(__a						)
									self.assertEqual(__a  ,		self.framework_tf						)

								# Invalid local checkpoint
								with TemporaryDirectory() as local_invalid_ckpt:
									with self.assertRaises(__a						):
										__UpperCAmelCase      					=      FeaturesManager.determine_framework(__a						)






							def    snake_case__    (   self					:				str						)				->						Union[str, Any]:
								__UpperCAmelCase      					=      MagicMock(return_value=__a						)
								with patch('''transformers.onnx.features.is_tf_available'''  ,		__a						):
									__UpperCAmelCase      					=      FeaturesManager.determine_framework(self.test_model						)
									self.assertEqual(__a  ,		self.framework_pt						)

								# PyTorch not in environment -> use TensorFlow
								__UpperCAmelCase      					=      MagicMock(return_value=__a						)
								with patch('''transformers.onnx.features.is_torch_available'''  ,		__a						):
									__UpperCAmelCase      					=      FeaturesManager.determine_framework(self.test_model						)
									self.assertEqual(__a  ,		self.framework_tf						)

								# Both in environment -> use PyTorch
								__UpperCAmelCase      					=      MagicMock(return_value=__a						)
								__UpperCAmelCase      					=      MagicMock(return_value=__a						)
								with patch('''transformers.onnx.features.is_tf_available'''  ,		__a						), patch(
								    '''transformers.onnx.features.is_torch_available'''  ,		__a						):
									__UpperCAmelCase      					=      FeaturesManager.determine_framework(self.test_model						)
									self.assertEqual(__a  ,		self.framework_pt						)

								# Both not in environment -> raise error
								__UpperCAmelCase      					=      MagicMock(return_value=__a						)
								__UpperCAmelCase      					=      MagicMock(return_value=__a						)
								with patch('''transformers.onnx.features.is_tf_available'''  ,		__a						), patch(
								    '''transformers.onnx.features.is_torch_available'''  ,		__a						):
									with self.assertRaises(__a						):
										__UpperCAmelCase      					=      FeaturesManager.determine_framework(self.test_model						)
