





from dataclasses import dataclass
from typing import List, Optional, Union

import numpy as np
import PIL

from ...utils import BaseOutput, OptionalDependencyNotAvailable, is_torch_available, is_transformers_available
from .timesteps import (
    fastaa_timesteps,
    smartaa_timesteps,
    smartaa_timesteps,
    smartaaa_timesteps,
    smartaaa_timesteps,
    superaa_timesteps,
    superaa_timesteps,
    superaaa_timesteps,
)



@dataclass
class 				_UpperCAmelCase    (    _UpperCamelCase    ):

  """simple docstring"""


  a_        = 42
  a_        = 42
  a_        = 42


try:
     if not (is_transformers_available() and is_torch_available()):
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     from ...utils.dummy_torch_and_transformers_objects import *  # noqa F403
else:
     from .pipeline_if import IFPipeline
     from .pipeline_if_imgaimg import IFImgaImgPipeline
     from .pipeline_if_imgaimg_superresolution import IFImgaImgSuperResolutionPipeline
     from .pipeline_if_inpainting import IFInpaintingPipeline
     from .pipeline_if_inpainting_superresolution import IFInpaintingSuperResolutionPipeline
     from .pipeline_if_superresolution import IFSuperResolutionPipeline
     from .safety_checker import IFSafetyChecker
     from .watermark import IFWatermarker








from typing import TYPE_CHECKING

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


_snake_case  :    Union[str, Any]						    =  {
    'configuration_layoutlmv3': [
        'LAYOUTLMV3_PRETRAINED_CONFIG_ARCHIVE_MAP',
        'LayoutLMv3Config',
        'LayoutLMv3OnnxConfig',
    ],
    'processing_layoutlmv3': ['LayoutLMv3Processor'],
    'tokenization_layoutlmv3': ['LayoutLMv3Tokenizer'],
}

try:
     if not is_tokenizers_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     _snake_case  :    Union[str, Any]						    =  ['LayoutLMv3TokenizerFast']

try:
     if not is_torch_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     _snake_case  :    List[str]						    =  [
         'LAYOUTLMV3_PRETRAINED_MODEL_ARCHIVE_LIST',
         'LayoutLMv3ForQuestionAnswering',
         'LayoutLMv3ForSequenceClassification',
         'LayoutLMv3ForTokenClassification',
         'LayoutLMv3Model',
         'LayoutLMv3PreTrainedModel',
     ]

try:
     if not is_tf_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     _snake_case  :    Optional[Any]						    =  [
         'TF_LAYOUTLMV3_PRETRAINED_MODEL_ARCHIVE_LIST',
         'TFLayoutLMv3ForQuestionAnswering',
         'TFLayoutLMv3ForSequenceClassification',
         'TFLayoutLMv3ForTokenClassification',
         'TFLayoutLMv3Model',
         'TFLayoutLMv3PreTrainedModel',
     ]

try:
     if not is_vision_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     _snake_case  :    Tuple						    =  ['LayoutLMv3FeatureExtractor']
     _snake_case  :    str						    =  ['LayoutLMv3ImageProcessor']


if TYPE_CHECKING:
     from .configuration_layoutlmva import (
         LAYOUTLMV3_PRETRAINED_CONFIG_ARCHIVE_MAP,
         LayoutLMvaConfig,
         LayoutLMvaOnnxConfig,
     )
     from .processing_layoutlmva import LayoutLMvaProcessor
     from .tokenization_layoutlmva import LayoutLMvaTokenizer

     try:
          if not is_tokenizers_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .tokenization_layoutlmva_fast import LayoutLMvaTokenizerFast

     try:
          if not is_torch_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .modeling_layoutlmva import (
              LAYOUTLMV3_PRETRAINED_MODEL_ARCHIVE_LIST,
              LayoutLMvaForQuestionAnswering,
              LayoutLMvaForSequenceClassification,
              LayoutLMvaForTokenClassification,
              LayoutLMvaModel,
              LayoutLMvaPreTrainedModel,
          )

     try:
          if not is_tf_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .modeling_tf_layoutlmva import (
              TF_LAYOUTLMV3_PRETRAINED_MODEL_ARCHIVE_LIST,
              TFLayoutLMvaForQuestionAnswering,
              TFLayoutLMvaForSequenceClassification,
              TFLayoutLMvaForTokenClassification,
              TFLayoutLMvaModel,
              TFLayoutLMvaPreTrainedModel,
          )

     try:
          if not is_vision_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .feature_extraction_layoutlmva import LayoutLMvaFeatureExtractor
          from .image_processing_layoutlmva import LayoutLMvaImageProcessor

else:
     import sys

     _snake_case  :    Any						    =  _LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)

