

from collections import OrderedDict
from typing import Mapping

from packaging import version

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging


lowerCamelCase      				=     logging.get_logger(__name__)

lowerCamelCase      				=     {
    '''google/mobilenet_v1_1.0_224''': '''https://huggingface.co/google/mobilenet_v1_1.0_224/resolve/main/config.json''',
    '''google/mobilenet_v1_0.75_192''': '''https://huggingface.co/google/mobilenet_v1_0.75_192/resolve/main/config.json''',
    # See all MobileNetV1 models at https://huggingface.co/models?filter=mobilenet_v1
}





class     snake_case_			(				__A							):


							"""simple docstring"""





							__UpperCAmelCase       ="""mobilenet_v1"""




							def __init__( self					,						_A=3					,						_A=2_2_4					,						_A=1.0					,						_A=8					,						_A="relu6"					,						_A=True					,						_A=0.999					,						_A=0.02					,						_A=0.001					,						**_A					,						):
												super().__init__(**_A							)

												if depth_multiplier <= 0:
																	raise ValueError('depth_multiplier must be greater than zero.'							)

												__lowerCAmelCase					=							num_channels
												__lowerCAmelCase					=							image_size
												__lowerCAmelCase					=							depth_multiplier
												__lowerCAmelCase					=							min_depth
												__lowerCAmelCase					=							hidden_act
												__lowerCAmelCase					=							tf_padding
												__lowerCAmelCase					=							classifier_dropout_prob
												__lowerCAmelCase					=							initializer_range
												__lowerCAmelCase					=							layer_norm_eps





class     snake_case_			(				__A							):


							"""simple docstring"""





							__UpperCAmelCase       =version.parse("""1.11"""							)




							@property
							def        A__  ( self							):
												return OrderedDict([('pixel_values', {0: 'batch'})]							)




							@property
							def        A__  ( self							):





												if self.task == "image-classification":
																	return OrderedDict([('logits', {0: 'batch'})]							)
												else:
																	return OrderedDict([('last_hidden_state', {0: 'batch'}), ('pooler_output', {0: 'batch'})]							)




							@property
							def        A__  ( self							):
												return 1e-4









from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_flax_available,
    is_tf_available,
    is_torch_available,
)


lowerCamelCase      				=     {'''configuration_unispeech''': ['''UNISPEECH_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''UniSpeechConfig''']}

try:
		if not is_torch_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		lowerCamelCase      				=     [
		    '''UNISPEECH_PRETRAINED_MODEL_ARCHIVE_LIST''',
		    '''UniSpeechForCTC''',
		    '''UniSpeechForPreTraining''',
		    '''UniSpeechForSequenceClassification''',
		    '''UniSpeechModel''',
		    '''UniSpeechPreTrainedModel''',
		]

if TYPE_CHECKING:
		from .configuration_unispeech import UNISPEECH_PRETRAINED_CONFIG_ARCHIVE_MAP, UniSpeechConfig

		try:
				if not is_torch_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .modeling_unispeech import (
				    UNISPEECH_PRETRAINED_MODEL_ARCHIVE_LIST,
				    UniSpeechForCTC,
				    UniSpeechForPreTraining,
				    UniSpeechForSequenceClassification,
				    UniSpeechModel,
				    UniSpeechPreTrainedModel,
				)

else:
		import sys

		lowerCamelCase      				=     _LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)






