
import PIL.Image
import PIL.ImageOps
from packaging import version
from PIL import Image


if version.parse(version.parse(PIL.__version__).base_version) >= version.parse('9.1.0'):
      lowercase__          ={
          'linear': PIL.Image.Resampling.BILINEAR,
          'bilinear': PIL.Image.Resampling.BILINEAR,
          'bicubic': PIL.Image.Resampling.BICUBIC,
          'lanczos': PIL.Image.Resampling.LANCZOS,
          'nearest': PIL.Image.Resampling.NEAREST,
      }
else:
      lowercase__          ={
          'linear': PIL.Image.LINEAR,
          'bilinear': PIL.Image.BILINEAR,
          'bicubic': PIL.Image.BICUBIC,
          'lanczos': PIL.Image.LANCZOS,
          'nearest': PIL.Image.NEAREST,
      }




def        __UpperCamelCase					(    lowerCAmelCase__							:    Union[str, Any]  ):
 __a			:  int		    =  (images / 2 + 0.5).clamp(0  ,       1  )
 __a			:  Tuple		    =  images.cpu().permute(0  ,       2  ,       3  ,       1  ).float().numpy()
 __a			:  Any		    =  numpy_to_pil(lowerCAmelCase__  )
 return images




def        __UpperCamelCase					(    lowerCAmelCase__							:    List[Any]  ):
 if images.ndim == 3:
  __a			:  Any		    =  images[None, ...]
 __a			:  Optional[int]		    =  (images * 2_5_5).round().astype('''uint8'''  )
 if images.shape[-1] == 1:
  # special case for grayscale (single channel) images
  __a			:  Tuple		    =  [Image.fromarray(image.squeeze()  ,       mode='''L'''  ) for image in images]
 else:
  __a			:  Optional[int]		    =  [Image.fromarray(lowerCAmelCase__  ) for image in images]

 return pil_images


from typing import TYPE_CHECKING

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


lowercase__          ={
    'configuration_data2vec_audio': ['DATA2VEC_AUDIO_PRETRAINED_CONFIG_ARCHIVE_MAP', 'Data2VecAudioConfig'],
    'configuration_data2vec_text': [
        'DATA2VEC_TEXT_PRETRAINED_CONFIG_ARCHIVE_MAP',
        'Data2VecTextConfig',
        'Data2VecTextOnnxConfig',
    ],
    'configuration_data2vec_vision': [
        'DATA2VEC_VISION_PRETRAINED_CONFIG_ARCHIVE_MAP',
        'Data2VecVisionConfig',
        'Data2VecVisionOnnxConfig',
    ],
}

try:
      if not is_torch_available():
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      pass
else:
      lowercase__          =[
          'DATA2VEC_AUDIO_PRETRAINED_MODEL_ARCHIVE_LIST',
          'Data2VecAudioForAudioFrameClassification',
          'Data2VecAudioForCTC',
          'Data2VecAudioForSequenceClassification',
          'Data2VecAudioForXVector',
          'Data2VecAudioModel',
          'Data2VecAudioPreTrainedModel',
      ]
      lowercase__          =[
          'DATA2VEC_TEXT_PRETRAINED_MODEL_ARCHIVE_LIST',
          'Data2VecTextForCausalLM',
          'Data2VecTextForMaskedLM',
          'Data2VecTextForMultipleChoice',
          'Data2VecTextForQuestionAnswering',
          'Data2VecTextForSequenceClassification',
          'Data2VecTextForTokenClassification',
          'Data2VecTextModel',
          'Data2VecTextPreTrainedModel',
      ]
      lowercase__          =[
          'DATA2VEC_VISION_PRETRAINED_MODEL_ARCHIVE_LIST',
          'Data2VecVisionForImageClassification',
          'Data2VecVisionForMaskedImageModeling',
          'Data2VecVisionForSemanticSegmentation',
          'Data2VecVisionModel',
          'Data2VecVisionPreTrainedModel',
      ]

if is_tf_available():
      lowercase__          =[
          'TFData2VecVisionForImageClassification',
          'TFData2VecVisionForSemanticSegmentation',
          'TFData2VecVisionModel',
          'TFData2VecVisionPreTrainedModel',
      ]

if TYPE_CHECKING:
      from .configuration_dataavec_audio import DATA2VEC_AUDIO_PRETRAINED_CONFIG_ARCHIVE_MAP, DataaVecAudioConfig
      from .configuration_dataavec_text import (
          DATA2VEC_TEXT_PRETRAINED_CONFIG_ARCHIVE_MAP,
          DataaVecTextConfig,
          DataaVecTextOnnxConfig,
      )
      from .configuration_dataavec_vision import (
          DATA2VEC_VISION_PRETRAINED_CONFIG_ARCHIVE_MAP,
          DataaVecVisionConfig,
          DataaVecVisionOnnxConfig,
      )

      try:
            if not is_torch_available():
                  raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
            pass
      else:
            from .modeling_dataavec_audio import (
                DATA2VEC_AUDIO_PRETRAINED_MODEL_ARCHIVE_LIST,
                DataaVecAudioForAudioFrameClassification,
                DataaVecAudioForCTC,
                DataaVecAudioForSequenceClassification,
                DataaVecAudioForXVector,
                DataaVecAudioModel,
                DataaVecAudioPreTrainedModel,
            )
            from .modeling_dataavec_text import (
                DATA2VEC_TEXT_PRETRAINED_MODEL_ARCHIVE_LIST,
                DataaVecTextForCausalLM,
                DataaVecTextForMaskedLM,
                DataaVecTextForMultipleChoice,
                DataaVecTextForQuestionAnswering,
                DataaVecTextForSequenceClassification,
                DataaVecTextForTokenClassification,
                DataaVecTextModel,
                DataaVecTextPreTrainedModel,
            )
            from .modeling_dataavec_vision import (
                DATA2VEC_VISION_PRETRAINED_MODEL_ARCHIVE_LIST,
                DataaVecVisionForImageClassification,
                DataaVecVisionForMaskedImageModeling,
                DataaVecVisionForSemanticSegmentation,
                DataaVecVisionModel,
                DataaVecVisionPreTrainedModel,
            )
      if is_tf_available():
            from .modeling_tf_dataavec_vision import (
                TFDataaVecVisionForImageClassification,
                TFDataaVecVisionForSemanticSegmentation,
                TFDataaVecVisionModel,
                TFDataaVecVisionPreTrainedModel,
            )

else:
      import sys

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