
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


_UpperCAmelCase      :				List[Any]          = logging.get_logger(__name__)

_UpperCAmelCase      :				Union[str, Any]          = {
    "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        lowercase      (	_UpperCAmelCase     ):
		__lowercase : Dict			  =       '''mobilenet_v1'''



		def __init__(				self       ,   A_=3       ,   A_=224       ,   A_=1.0       ,   A_=8       ,   A_="relu6"       ,   A_=True       ,   A_=0.999       ,   A_=0.02       ,   A_=0.001       ,   **A_       ,   )						->      Optional[int]:
				"""simple docstring"""
				super().__init__(**A_ )

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

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






class        lowercase      (	_UpperCAmelCase     ):
		__lowercase : List[str]			  =       version.parse("1.11"     )



		@property
		def __UpperCamelCase				(				self )						->      Mapping[str, Mapping[int, str]]:
				"""simple docstring"""
				return OrderedDict([('pixel_values', {0: 'batch'})] )



		@property
		def __UpperCamelCase				(				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 __UpperCamelCase				(				self )						->      float:
				"""simple docstring"""
				return 1e-4


from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


_UpperCAmelCase      :				Union[str, Any]          = {
    "configuration_git": ["GIT_PRETRAINED_CONFIG_ARCHIVE_MAP", "GitConfig", "GitVisionConfig"],
    "processing_git": ["GitProcessor"],
}

try:
					if not is_torch_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					_UpperCAmelCase      :				Dict          = [
					    "GIT_PRETRAINED_MODEL_ARCHIVE_LIST",
					    "GitForCausalLM",
					    "GitModel",
					    "GitPreTrainedModel",
					    "GitVisionModel",
					]

if TYPE_CHECKING:
					from .configuration_git import GIT_PRETRAINED_CONFIG_ARCHIVE_MAP, GitConfig, GitVisionConfig
					from .processing_git import GitProcessor

					try:
										if not is_torch_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .modeling_git import (
										    GIT_PRETRAINED_MODEL_ARCHIVE_LIST,
										    GitForCausalLM,
										    GitModel,
										    GitPreTrainedModel,
										    GitVisionModel,
										)

else:
					import sys

					_UpperCAmelCase      :				int          = _LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)
