
from typing import TYPE_CHECKING

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


snake_case						: List[str]         =  {
    """configuration_mobilenet_v2""": [
        """MOBILENET_V2_PRETRAINED_CONFIG_ARCHIVE_MAP""",
        """MobileNetV2Config""",
        """MobileNetV2OnnxConfig""",
    ],
}

try:
							if not is_vision_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							snake_case						: Tuple         =  ["""MobileNetV2FeatureExtractor"""]
							snake_case						: Union[str, Any]         =  ["""MobileNetV2ImageProcessor"""]


try:
							if not is_torch_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							snake_case						: int         =  [
							    """MOBILENET_V2_PRETRAINED_MODEL_ARCHIVE_LIST""",
							    """MobileNetV2ForImageClassification""",
							    """MobileNetV2ForSemanticSegmentation""",
							    """MobileNetV2Model""",
							    """MobileNetV2PreTrainedModel""",
							    """load_tf_weights_in_mobilenet_v2""",
							]


if TYPE_CHECKING:
							from .configuration_mobilenet_va import (
							    MOBILENET_V2_PRETRAINED_CONFIG_ARCHIVE_MAP,
							    MobileNetVaConfig,
							    MobileNetVaOnnxConfig,
							)

							try:
														if not is_vision_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .feature_extraction_mobilenet_va import MobileNetVaFeatureExtractor
														from .image_processing_mobilenet_va import MobileNetVaImageProcessor

							try:
														if not is_torch_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .modeling_mobilenet_va import (
														    MOBILENET_V2_PRETRAINED_MODEL_ARCHIVE_LIST,
														    MobileNetVaForImageClassification,
														    MobileNetVaForSemanticSegmentation,
														    MobileNetVaModel,
														    MobileNetVaPreTrainedModel,
														    load_tf_weights_in_mobilenet_va,
														)


else:
							import sys

							snake_case						: List[str]         =  _LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)








import os

from huggingface_hub.constants import HUGGINGFACE_HUB_CACHE, hf_cache_home


lowerCamelCase_						: Optional[int]         =  HUGGINGFACE_HUB_CACHE


lowerCamelCase_						: List[str]         =  """config.json"""
lowerCamelCase_						: Any         =  """diffusion_pytorch_model.bin"""
lowerCamelCase_						: Union[str, Any]         =  """diffusion_flax_model.msgpack"""
lowerCamelCase_						: Dict         =  """model.onnx"""
lowerCamelCase_						: List[Any]         =  """diffusion_pytorch_model.safetensors"""
lowerCamelCase_						: Optional[Any]         =  """weights.pb"""
lowerCamelCase_						: Optional[Any]         =  """https://huggingface.co"""
lowerCamelCase_						: Union[str, Any]         =  default_cache_path
lowerCamelCase_						: Tuple         =  """diffusers_modules"""
lowerCamelCase_						: Optional[Any]         =  os.getenv("""HF_MODULES_CACHE""", os.path.join(hf_cache_home, """modules"""))
lowerCamelCase_						: str         =  ["""fp16""", """non-ema"""]
lowerCamelCase_						: List[Any]         =  """.self_attn"""






