


from typing import Optional, Union

import torch
from torch import nn

from ...configuration_utils import ConfigMixin, register_to_config
from ...models.modeling_utils import ModelMixin


class   a__	(						lowerCAmelCase_						,       lowerCAmelCase_    ):

       @register_to_config
       def __init__(   self      :     Union[str, Any]      ,							lowerCamelCase_      :     int = 7_6_8      ,							):
            super().__init__()

            a_    :     List[str]										=    nn.Parameter(torch.zeros(1      ,							lowerCamelCase_    )    )
            a_    :     Any										=    nn.Parameter(torch.ones(1      ,							lowerCamelCase_    )    )

       def 						UpperCAmelCase(   self      :     Optional[int]      ,							lowerCamelCase_      :     Optional[Union[str, torch.device]] = None      ,							lowerCamelCase_      :     Optional[torch.dtype] = None      ,							):
            a_    :     Any										=    nn.Parameter(self.mean.to(lowerCamelCase_    ).to(lowerCamelCase_    )    )
            a_    :     str										=    nn.Parameter(self.std.to(lowerCamelCase_    ).to(lowerCamelCase_    )    )
            return self

       def 						UpperCAmelCase(   self      :     int      ,							lowerCamelCase_      :     int    ):
            a_    :     List[Any]										=    (embeds - self.mean) * 1.0 / self.std
            return embeds

       def 						UpperCAmelCase(   self      :     Dict      ,							lowerCamelCase_      :     str    ):
            a_    :     List[Any]										=    (embeds * self.std) + self.mean
            return embeds







from typing import TYPE_CHECKING

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


__lowerCamelCase        =     {'''configuration_vit''': ['''VIT_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''ViTConfig''', '''ViTOnnxConfig''']}

try:
       if not is_vision_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       __lowerCamelCase        =     ['''ViTFeatureExtractor''']
       __lowerCamelCase        =     ['''ViTImageProcessor''']

try:
       if not is_torch_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       __lowerCamelCase        =     [
           '''VIT_PRETRAINED_MODEL_ARCHIVE_LIST''',
           '''ViTForImageClassification''',
           '''ViTForMaskedImageModeling''',
           '''ViTModel''',
           '''ViTPreTrainedModel''',
       ]

try:
       if not is_tf_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       __lowerCamelCase        =     [
           '''TFViTForImageClassification''',
           '''TFViTModel''',
           '''TFViTPreTrainedModel''',
       ]

try:
       if not is_flax_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       __lowerCamelCase        =     [
           '''FlaxViTForImageClassification''',
           '''FlaxViTModel''',
           '''FlaxViTPreTrainedModel''',
       ]

if TYPE_CHECKING:
       from .configuration_vit import VIT_PRETRAINED_CONFIG_ARCHIVE_MAP, ViTConfig, ViTOnnxConfig

       try:
              if not is_vision_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .feature_extraction_vit import ViTFeatureExtractor
              from .image_processing_vit import ViTImageProcessor

       try:
              if not is_torch_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .modeling_vit import (
                  VIT_PRETRAINED_MODEL_ARCHIVE_LIST,
                  ViTForImageClassification,
                  ViTForMaskedImageModeling,
                  ViTModel,
                  ViTPreTrainedModel,
              )

       try:
              if not is_tf_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .modeling_tf_vit import TFViTForImageClassification, TFViTModel, TFViTPreTrainedModel

       try:
              if not is_flax_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .modeling_flax_vit import FlaxViTForImageClassification, FlaxViTModel, FlaxViTPreTrainedModel


else:
       import sys

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



