





'''simple docstring'''

from typing import TYPE_CHECKING

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


lowercase__						:      Tuple	=    {
    'configuration_squeezebert': [
        'SQUEEZEBERT_PRETRAINED_CONFIG_ARCHIVE_MAP',
        'SqueezeBertConfig',
        'SqueezeBertOnnxConfig',
    ],
    'tokenization_squeezebert': ['SqueezeBertTokenizer'],
}

try:
			if not is_tokenizers_available():
						raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
			pass
else:
			lowercase__						:      List[str]	=    ['SqueezeBertTokenizerFast']

try:
			if not is_torch_available():
						raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
			pass
else:
			lowercase__						:      Dict	=    [
			    'SQUEEZEBERT_PRETRAINED_MODEL_ARCHIVE_LIST',
			    'SqueezeBertForMaskedLM',
			    'SqueezeBertForMultipleChoice',
			    'SqueezeBertForQuestionAnswering',
			    'SqueezeBertForSequenceClassification',
			    'SqueezeBertForTokenClassification',
			    'SqueezeBertModel',
			    'SqueezeBertModule',
			    'SqueezeBertPreTrainedModel',
			]


if TYPE_CHECKING:
			from .configuration_squeezebert import (
			    SQUEEZEBERT_PRETRAINED_CONFIG_ARCHIVE_MAP,
			    SqueezeBertConfig,
			    SqueezeBertOnnxConfig,
			)
			from .tokenization_squeezebert import SqueezeBertTokenizer

			try:
						if not is_tokenizers_available():
									raise OptionalDependencyNotAvailable()
			except OptionalDependencyNotAvailable:
						pass
			else:
						from .tokenization_squeezebert_fast import SqueezeBertTokenizerFast

			try:
						if not is_torch_available():
									raise OptionalDependencyNotAvailable()
			except OptionalDependencyNotAvailable:
						pass
			else:
						from .modeling_squeezebert import (
						    SQUEEZEBERT_PRETRAINED_MODEL_ARCHIVE_LIST,
						    SqueezeBertForMaskedLM,
						    SqueezeBertForMultipleChoice,
						    SqueezeBertForQuestionAnswering,
						    SqueezeBertForSequenceClassification,
						    SqueezeBertForTokenClassification,
						    SqueezeBertModel,
						    SqueezeBertModule,
						    SqueezeBertPreTrainedModel,
						)

else:
			import sys

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










'''simple docstring'''

import unittest

from diffusers.pipelines.pipeline_utils import is_safetensors_compatible
class     __lowerCAmelCase					(   unittest.TestCase			):






       """simple docstring"""





       def snake_case__						(							self       :		Tuple					)   ->					int:

            '''simple docstring'''




            _UpperCamelCase       =	[
                '''safety_checker/pytorch_model.bin''',
                '''safety_checker/model.safetensors''',
                '''vae/diffusion_pytorch_model.bin''',
                '''vae/diffusion_pytorch_model.safetensors''',
                '''text_encoder/pytorch_model.bin''',
                '''text_encoder/model.safetensors''',
                '''unet/diffusion_pytorch_model.bin''',
                '''unet/diffusion_pytorch_model.safetensors''',
            ]
            self.assertTrue(is_safetensors_compatible(lowerCAmelCase__					)					)





       def snake_case__						(							self       :		int					)   ->					Tuple:

            '''simple docstring'''




            _UpperCamelCase       =	[
                '''unet/diffusion_pytorch_model.bin''',
                '''unet/diffusion_pytorch_model.safetensors''',
            ]
            self.assertTrue(is_safetensors_compatible(lowerCAmelCase__					)					)





       def snake_case__						(							self       :		Optional[Any]					)   ->					List[str]:

            '''simple docstring'''




            _UpperCamelCase       =	[
                '''safety_checker/pytorch_model.bin''',
                '''safety_checker/model.safetensors''',
                '''vae/diffusion_pytorch_model.bin''',
                '''vae/diffusion_pytorch_model.safetensors''',
                '''text_encoder/pytorch_model.bin''',
                '''text_encoder/model.safetensors''',
                '''unet/diffusion_pytorch_model.bin''',
                # Removed: 'unet/diffusion_pytorch_model.safetensors',
            ]
            self.assertFalse(is_safetensors_compatible(lowerCAmelCase__					)					)





       def snake_case__						(							self       :		List[Any]					)   ->					List[Any]:

            '''simple docstring'''




            _UpperCamelCase       =	[
                '''text_encoder/pytorch_model.bin''',
                '''text_encoder/model.safetensors''',
            ]
            self.assertTrue(is_safetensors_compatible(lowerCAmelCase__					)					)





       def snake_case__						(							self       :		Dict					)   ->					Dict:

            '''simple docstring'''




            _UpperCamelCase       =	[
                '''safety_checker/pytorch_model.bin''',
                '''safety_checker/model.safetensors''',
                '''vae/diffusion_pytorch_model.bin''',
                '''vae/diffusion_pytorch_model.safetensors''',
                '''text_encoder/pytorch_model.bin''',
                # Removed: 'text_encoder/model.safetensors',
                '''unet/diffusion_pytorch_model.bin''',
                '''unet/diffusion_pytorch_model.safetensors''',
            ]
            self.assertFalse(is_safetensors_compatible(lowerCAmelCase__					)					)





       def snake_case__						(							self       :		Any					)   ->					Optional[int]:

            '''simple docstring'''




            _UpperCamelCase       =	[
                '''safety_checker/pytorch_model.fp16.bin''',
                '''safety_checker/model.fp16.safetensors''',
                '''vae/diffusion_pytorch_model.fp16.bin''',
                '''vae/diffusion_pytorch_model.fp16.safetensors''',
                '''text_encoder/pytorch_model.fp16.bin''',
                '''text_encoder/model.fp16.safetensors''',
                '''unet/diffusion_pytorch_model.fp16.bin''',
                '''unet/diffusion_pytorch_model.fp16.safetensors''',
            ]
            _UpperCamelCase       =	'''fp16'''
            self.assertTrue(is_safetensors_compatible(lowerCAmelCase__	,			variant=lowerCAmelCase__					)					)





       def snake_case__						(							self       :		Optional[Any]					)   ->					Dict:

            '''simple docstring'''




            _UpperCamelCase       =	[
                '''unet/diffusion_pytorch_model.fp16.bin''',
                '''unet/diffusion_pytorch_model.fp16.safetensors''',
            ]
            _UpperCamelCase       =	'''fp16'''
            self.assertTrue(is_safetensors_compatible(lowerCAmelCase__	,			variant=lowerCAmelCase__					)					)





       def snake_case__						(							self       :		Tuple					)   ->					Optional[Any]:

            '''simple docstring'''




            _UpperCamelCase       =	[
                '''unet/diffusion_pytorch_model.bin''',
                '''unet/diffusion_pytorch_model.safetensors''',
            ]
            _UpperCamelCase       =	'''fp16'''
            self.assertTrue(is_safetensors_compatible(lowerCAmelCase__	,			variant=lowerCAmelCase__					)					)





       def snake_case__						(							self       :		Tuple					)   ->					Union[str, Any]:

            '''simple docstring'''




            _UpperCamelCase       =	[
                '''safety_checker/pytorch_model.fp16.bin''',
                '''safety_checker/model.fp16.safetensors''',
                '''vae/diffusion_pytorch_model.fp16.bin''',
                '''vae/diffusion_pytorch_model.fp16.safetensors''',
                '''text_encoder/pytorch_model.fp16.bin''',
                '''text_encoder/model.fp16.safetensors''',
                '''unet/diffusion_pytorch_model.fp16.bin''',
                # Removed: 'unet/diffusion_pytorch_model.fp16.safetensors',
            ]
            _UpperCamelCase       =	'''fp16'''
            self.assertFalse(is_safetensors_compatible(lowerCAmelCase__	,			variant=lowerCAmelCase__					)					)





       def snake_case__						(							self       :		Optional[int]					)   ->					Dict:

            '''simple docstring'''




            _UpperCamelCase       =	[
                '''text_encoder/pytorch_model.fp16.bin''',
                '''text_encoder/model.fp16.safetensors''',
            ]
            _UpperCamelCase       =	'''fp16'''
            self.assertTrue(is_safetensors_compatible(lowerCAmelCase__	,			variant=lowerCAmelCase__					)					)





       def snake_case__						(							self       :		Optional[Any]					)   ->					str:

            '''simple docstring'''




            _UpperCamelCase       =	[
                '''text_encoder/pytorch_model.bin''',
                '''text_encoder/model.safetensors''',
            ]
            _UpperCamelCase       =	'''fp16'''
            self.assertTrue(is_safetensors_compatible(lowerCAmelCase__	,			variant=lowerCAmelCase__					)					)







       def snake_case__						(							self       :		List[str]					)   ->					Optional[int]:

            '''simple docstring'''




            _UpperCamelCase       =	[
                '''safety_checker/pytorch_model.fp16.bin''',
                '''safety_checker/model.fp16.safetensors''',
                '''vae/diffusion_pytorch_model.fp16.bin''',
                '''vae/diffusion_pytorch_model.fp16.safetensors''',
                '''text_encoder/pytorch_model.fp16.bin''',
                # 'text_encoder/model.fp16.safetensors',
                '''unet/diffusion_pytorch_model.fp16.bin''',
                '''unet/diffusion_pytorch_model.fp16.safetensors''',
            ]
            _UpperCamelCase       =	'''fp16'''
            self.assertFalse(is_safetensors_compatible(lowerCAmelCase__	,			variant=lowerCAmelCase__					)					)



