



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


__snake_case    :		Tuple  =logging.get_logger(__name__)

__snake_case    :		Tuple  ={
    '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 	lowerCamelCase__      (							lowerCamelCase__):




		'''simple docstring'''



		snake_case_     ="""mobilenet_v1"""



		def __init__(self		,__lowerCamelCase=3		,__lowerCamelCase=2_24		,__lowerCamelCase=1.0		,__lowerCamelCase=8		,__lowerCamelCase="relu6"		,__lowerCamelCase=True		,__lowerCamelCase=0.999		,__lowerCamelCase=0.02		,__lowerCamelCase=0.001		,**__lowerCamelCase		,)					->      List[Any]:

						"""simple docstring"""






						super().__init__(**__lowerCamelCase			)

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

						lowerCAmelCase__					:    Any												=					num_channels
						lowerCAmelCase__					:    Optional[Any]												=					image_size
						lowerCAmelCase__					:    Optional[int]												=					depth_multiplier
						lowerCAmelCase__					:    Optional[int]												=					min_depth
						lowerCAmelCase__					:    int												=					hidden_act
						lowerCAmelCase__					:    List[Any]												=					tf_padding
						lowerCAmelCase__					:    List[str]												=					classifier_dropout_prob
						lowerCAmelCase__					:    List[Any]												=					initializer_range
						lowerCAmelCase__					:    Optional[int]												=					layer_norm_eps



class 	lowerCamelCase__      (							lowerCamelCase__):




		'''simple docstring'''



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



		@property
		def 		lowerCAmelCase__				(self			)					->      Mapping[str, Mapping[int, str]]:

						"""simple docstring"""






						return OrderedDict([('''pixel_values''', {0: '''batch'''})]			)



		@property
		def 		lowerCAmelCase__				(self			)					->      Mapping[str, Mapping[int, str]]:

						"""simple docstring"""






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



		@property
		def 		lowerCAmelCase__				(self			)					->      float:

						"""simple docstring"""






						return 1e-4






from typing import TYPE_CHECKING

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


__snake_case    :		Any  ={
    'configuration_blenderbot_small': [
        'BLENDERBOT_SMALL_PRETRAINED_CONFIG_ARCHIVE_MAP',
        'BlenderbotSmallConfig',
        'BlenderbotSmallOnnxConfig',
    ],
    'tokenization_blenderbot_small': ['BlenderbotSmallTokenizer'],
}

try:
							if not is_tokenizers_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							__snake_case    :		Union[str, Any]  =['BlenderbotSmallTokenizerFast']

try:
							if not is_torch_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							__snake_case    :		List[str]  =[
							    'BLENDERBOT_SMALL_PRETRAINED_MODEL_ARCHIVE_LIST',
							    'BlenderbotSmallForCausalLM',
							    'BlenderbotSmallForConditionalGeneration',
							    'BlenderbotSmallModel',
							    'BlenderbotSmallPreTrainedModel',
							]

try:
							if not is_tf_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							__snake_case    :		str  =[
							    'TFBlenderbotSmallForConditionalGeneration',
							    'TFBlenderbotSmallModel',
							    'TFBlenderbotSmallPreTrainedModel',
							]

try:
							if not is_flax_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							__snake_case    :		Dict  =[
							    'FlaxBlenderbotSmallForConditionalGeneration',
							    'FlaxBlenderbotSmallModel',
							    'FlaxBlenderbotSmallPreTrainedModel',
							]

if TYPE_CHECKING:
							from .configuration_blenderbot_small import (
							    BLENDERBOT_SMALL_PRETRAINED_CONFIG_ARCHIVE_MAP,
							    BlenderbotSmallConfig,
							    BlenderbotSmallOnnxConfig,
							)
							from .tokenization_blenderbot_small import BlenderbotSmallTokenizer

							try:
														if not is_tokenizers_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .tokenization_blenderbot_small_fast import BlenderbotSmallTokenizerFast

							try:
														if not is_torch_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .modeling_blenderbot_small import (
														    BLENDERBOT_SMALL_PRETRAINED_MODEL_ARCHIVE_LIST,
														    BlenderbotSmallForCausalLM,
														    BlenderbotSmallForConditionalGeneration,
														    BlenderbotSmallModel,
														    BlenderbotSmallPreTrainedModel,
														)

							try:
														if not is_tf_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .modeling_tf_blenderbot_small import (
														    TFBlenderbotSmallForConditionalGeneration,
														    TFBlenderbotSmallModel,
														    TFBlenderbotSmallPreTrainedModel,
														)

							try:
														if not is_flax_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .modeling_flax_blenderbot_small import (
														    FlaxBlenderbotSmallForConditionalGeneration,
														    FlaxBlenderbotSmallModel,
														    FlaxBlenderbotSmallPreTrainedModel,
														)

else:
							import sys

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

