


'''simple docstring'''

from typing import TYPE_CHECKING

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


__lowercase:		int    						=  {
    "configuration_bart": ["BART_PRETRAINED_CONFIG_ARCHIVE_MAP", "BartConfig", "BartOnnxConfig"],
    "tokenization_bart": ["BartTokenizer"],
}

try:
       if not is_tokenizers_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       __lowercase:		Any    						=  ["BartTokenizerFast"]

try:
       if not is_torch_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       __lowercase:		Tuple    						=  [
           "BART_PRETRAINED_MODEL_ARCHIVE_LIST",
           "BartForCausalLM",
           "BartForConditionalGeneration",
           "BartForQuestionAnswering",
           "BartForSequenceClassification",
           "BartModel",
           "BartPretrainedModel",
           "PretrainedBartModel",
       ]

try:
       if not is_tf_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       __lowercase:		List[Any]    						=  [
           "TFBartForConditionalGeneration",
           "TFBartForSequenceClassification",
           "TFBartModel",
           "TFBartPretrainedModel",
       ]

try:
       if not is_flax_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       __lowercase:		Optional[int]    						=  [
           "FlaxBartDecoderPreTrainedModel",
           "FlaxBartForCausalLM",
           "FlaxBartForConditionalGeneration",
           "FlaxBartForQuestionAnswering",
           "FlaxBartForSequenceClassification",
           "FlaxBartModel",
           "FlaxBartPreTrainedModel",
       ]

if TYPE_CHECKING:
       from .configuration_bart import BART_PRETRAINED_CONFIG_ARCHIVE_MAP, BartConfig, BartOnnxConfig
       from .tokenization_bart import BartTokenizer

       try:
              if not is_tokenizers_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .tokenization_bart_fast import BartTokenizerFast

       try:
              if not is_torch_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .modeling_bart import (
                  BART_PRETRAINED_MODEL_ARCHIVE_LIST,
                  BartForCausalLM,
                  BartForConditionalGeneration,
                  BartForQuestionAnswering,
                  BartForSequenceClassification,
                  BartModel,
                  BartPretrainedModel,
                  PretrainedBartModel,
              )

       try:
              if not is_tf_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .modeling_tf_bart import (
                  TFBartForConditionalGeneration,
                  TFBartForSequenceClassification,
                  TFBartModel,
                  TFBartPretrainedModel,
              )

       try:
              if not is_flax_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .modeling_flax_bart import (
                  FlaxBartDecoderPreTrainedModel,
                  FlaxBartForCausalLM,
                  FlaxBartForConditionalGeneration,
                  FlaxBartForQuestionAnswering,
                  FlaxBartForSequenceClassification,
                  FlaxBartModel,
                  FlaxBartPreTrainedModel,
              )

else:
       import sys

       __lowercase:		Tuple    						=  _LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)
from typing import List

import datasets
from datasets.tasks import ImageClassification

from ..folder_based_builder import folder_based_builder


UpperCAmelCase				 =   datasets.utils.logging.get_logger(__name__)






class 				_SCREAMING_SNAKE_CASE( folder_based_builder.FolderBasedBuilderConfig						):
   UpperCamelCase_					:    bool			      = None
   UpperCamelCase_					:    bool			      = None






class 				_SCREAMING_SNAKE_CASE( folder_based_builder.FolderBasedBuilder						):
   UpperCamelCase_					:    List[str]			      = datasets.Image()
   UpperCamelCase_					:    Any			      = 'image'
   UpperCamelCase_					:    str			      = ImageFolderConfig
   UpperCamelCase_					:    List[str]  # definition at the bottom of the script
   UpperCamelCase_					:    Union[str, Any]			      = ImageClassification(image_column='image'							,   label_column='label'						)

UpperCAmelCase				 =   [
    """.blp""",
    """.bmp""",
    """.dib""",
    """.bufr""",
    """.cur""",
    """.pcx""",
    """.dcx""",
    """.dds""",
    """.ps""",
    """.eps""",
    """.fit""",
    """.fits""",
    """.fli""",
    """.flc""",
    """.ftc""",
    """.ftu""",
    """.gbr""",
    """.gif""",
    """.grib""",
    """.h5""",
    """.hdf""",
    """.png""",
    """.apng""",
    """.jp2""",
    """.j2k""",
    """.jpc""",
    """.jpf""",
    """.jpx""",
    """.j2c""",
    """.icns""",
    """.ico""",
    """.im""",
    """.iim""",
    """.tif""",
    """.tiff""",
    """.jfif""",
    """.jpe""",
    """.jpg""",
    """.jpeg""",
    """.mpg""",
    """.mpeg""",
    """.msp""",
    """.pcd""",
    """.pxr""",
    """.pbm""",
    """.pgm""",
    """.ppm""",
    """.pnm""",
    """.psd""",
    """.bw""",
    """.rgb""",
    """.rgba""",
    """.sgi""",
    """.ras""",
    """.tga""",
    """.icb""",
    """.vda""",
    """.vst""",
    """.webp""",
    """.wmf""",
    """.emf""",
    """.xbm""",
    """.xpm""",
]
UpperCAmelCase				 =   IMAGE_EXTENSIONS