


from typing import TYPE_CHECKING

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


__UpperCamelCase       :       Optional[Any]						       =				{
    "configuration_gpt_neox_japanese": ["GPT_NEOX_JAPANESE_PRETRAINED_CONFIG_ARCHIVE_MAP", "GPTNeoXJapaneseConfig"],
    "tokenization_gpt_neox_japanese": ["GPTNeoXJapaneseTokenizer"],
}

try:
       if not is_torch_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       __UpperCamelCase       :       Dict						       =				[
           "GPT_NEOX_JAPANESE_PRETRAINED_MODEL_ARCHIVE_LIST",
           "GPTNeoXJapaneseForCausalLM",
           "GPTNeoXJapaneseLayer",
           "GPTNeoXJapaneseModel",
           "GPTNeoXJapanesePreTrainedModel",
       ]


if TYPE_CHECKING:
       from .configuration_gpt_neox_japanese import GPT_NEOX_JAPANESE_PRETRAINED_CONFIG_ARCHIVE_MAP, GPTNeoXJapaneseConfig
       from .tokenization_gpt_neox_japanese import GPTNeoXJapaneseTokenizer

       try:
              if not is_torch_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .modeling_gpt_neox_japanese import (
                  GPT_NEOX_JAPANESE_PRETRAINED_MODEL_ARCHIVE_LIST,
                  GPTNeoXJapaneseForCausalLM,
                  GPTNeoXJapaneseLayer,
                  GPTNeoXJapaneseModel,
                  GPTNeoXJapanesePreTrainedModel,
              )


else:
       import sys

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






from typing import TYPE_CHECKING

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


__UpperCamelCase       :       Dict						       =				{
    "configuration_mobilevit": ["MOBILEVIT_PRETRAINED_CONFIG_ARCHIVE_MAP", "MobileViTConfig", "MobileViTOnnxConfig"],
}

try:
       if not is_vision_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       __UpperCamelCase       :       str						       =				["MobileViTFeatureExtractor"]
       __UpperCamelCase       :       Optional[Any]						       =				["MobileViTImageProcessor"]

try:
       if not is_torch_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       __UpperCamelCase       :       Union[str, Any]						       =				[
           "MOBILEVIT_PRETRAINED_MODEL_ARCHIVE_LIST",
           "MobileViTForImageClassification",
           "MobileViTForSemanticSegmentation",
           "MobileViTModel",
           "MobileViTPreTrainedModel",
       ]

try:
       if not is_tf_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       __UpperCamelCase       :       Optional[int]						       =				[
           "TF_MOBILEVIT_PRETRAINED_MODEL_ARCHIVE_LIST",
           "TFMobileViTForImageClassification",
           "TFMobileViTForSemanticSegmentation",
           "TFMobileViTModel",
           "TFMobileViTPreTrainedModel",
       ]

if TYPE_CHECKING:
       from .configuration_mobilevit import MOBILEVIT_PRETRAINED_CONFIG_ARCHIVE_MAP, MobileViTConfig, MobileViTOnnxConfig

       try:
              if not is_vision_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .feature_extraction_mobilevit import MobileViTFeatureExtractor
              from .image_processing_mobilevit import MobileViTImageProcessor

       try:
              if not is_torch_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .modeling_mobilevit import (
                  MOBILEVIT_PRETRAINED_MODEL_ARCHIVE_LIST,
                  MobileViTForImageClassification,
                  MobileViTForSemanticSegmentation,
                  MobileViTModel,
                  MobileViTPreTrainedModel,
              )

       try:
              if not is_tf_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .modeling_tf_mobilevit import (
                  TF_MOBILEVIT_PRETRAINED_MODEL_ARCHIVE_LIST,
                  TFMobileViTForImageClassification,
                  TFMobileViTForSemanticSegmentation,
                  TFMobileViTModel,
                  TFMobileViTPreTrainedModel,
              )


else:
       import sys

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


