from collections import OrderedDict
from typing import Mapping

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging


_SCREAMING_SNAKE_CASE     =     logging.get_logger(__name__)

_SCREAMING_SNAKE_CASE     =     {
    """nghuyong/ernie-1.0-base-zh""": """https://huggingface.co/nghuyong/ernie-1.0-base-zh/resolve/main/config.json""",
    """nghuyong/ernie-2.0-base-en""": """https://huggingface.co/nghuyong/ernie-2.0-base-en/resolve/main/config.json""",
    """nghuyong/ernie-2.0-large-en""": """https://huggingface.co/nghuyong/ernie-2.0-large-en/resolve/main/config.json""",
    """nghuyong/ernie-3.0-base-zh""": """https://huggingface.co/nghuyong/ernie-3.0-base-zh/resolve/main/config.json""",
    """nghuyong/ernie-3.0-medium-zh""": """https://huggingface.co/nghuyong/ernie-3.0-medium-zh/resolve/main/config.json""",
    """nghuyong/ernie-3.0-mini-zh""": """https://huggingface.co/nghuyong/ernie-3.0-mini-zh/resolve/main/config.json""",
    """nghuyong/ernie-3.0-micro-zh""": """https://huggingface.co/nghuyong/ernie-3.0-micro-zh/resolve/main/config.json""",
    """nghuyong/ernie-3.0-nano-zh""": """https://huggingface.co/nghuyong/ernie-3.0-nano-zh/resolve/main/config.json""",
    """nghuyong/ernie-gram-zh""": """https://huggingface.co/nghuyong/ernie-gram-zh/resolve/main/config.json""",
    """nghuyong/ernie-health-zh""": """https://huggingface.co/nghuyong/ernie-health-zh/resolve/main/config.json""",
}







class        UpperCAmelCase_					(				_a     ):
    UpperCAmelCase_      :							List[str]    			=				'ernie'




    def __init__(       self	: Dict   ,   lowerCAmelCase	: Optional[Any]=30522   ,   lowerCAmelCase	: Any=768   ,   lowerCAmelCase	: Union[str, Any]=12   ,   lowerCAmelCase	: List[Any]=12   ,   lowerCAmelCase	: Optional[int]=3072   ,   lowerCAmelCase	: List[Any]="gelu"   ,   lowerCAmelCase	: str=0.1   ,   lowerCAmelCase	: int=0.1   ,   lowerCAmelCase	: Dict=512   ,   lowerCAmelCase	: Any=2   ,   lowerCAmelCase	: Tuple=3   ,   lowerCAmelCase	: int=False   ,   lowerCAmelCase	: str=0.02   ,   lowerCAmelCase	: Any=1e-1_2   ,   lowerCAmelCase	: Optional[int]=0   ,   lowerCAmelCase	: int="absolute"   ,   lowerCAmelCase	: Optional[int]=True   ,   lowerCAmelCase	: Any=None   ,   **lowerCAmelCase	: Optional[Any]   ,   )						->			Tuple:
      super().__init__(pad_token_id=lowerCAmelCase   ,   **lowerCAmelCase )

      a__  		=  vocab_size
      a__  		=  hidden_size
      a__  		=  num_hidden_layers
      a__  		=  num_attention_heads
      a__  		=  hidden_act
      a__  		=  intermediate_size
      a__  		=  hidden_dropout_prob
      a__  		=  attention_probs_dropout_prob
      a__  		=  max_position_embeddings
      a__  		=  type_vocab_size
      a__  		=  task_type_vocab_size
      a__  		=  use_task_id
      a__  		=  initializer_range
      a__  		=  layer_norm_eps
      a__  		=  position_embedding_type
      a__  		=  use_cache
      a__  		=  classifier_dropout







class        UpperCAmelCase_					(				_a     ):




    @property
    def     __lowerCamelCase			(       self	: Dict )						->			Mapping[str, Mapping[int, str]]:
      if self.task == "multiple-choice":
        a__  		=  {0: "batch", 1: "choice", 2: "sequence"}
      else:
        a__  		=  {0: "batch", 1: "sequence"}
      return OrderedDict(
          [
              ("input_ids", dynamic_axis),
              ("attention_mask", dynamic_axis),
              ("token_type_ids", dynamic_axis),
              ("task_type_ids", dynamic_axis),
          ] )


from typing import List

import datasets
from datasets.tasks import ImageClassification

from ..folder_based_builder import folder_based_builder


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







class        UpperCAmelCase_					(				folder_based_builder.FolderBasedBuilderConfig     ):
    UpperCAmelCase_      :							bool    			=				None
    UpperCAmelCase_      :							bool    			=				None







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

_SCREAMING_SNAKE_CASE     =     [
    """.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""",
]
_SCREAMING_SNAKE_CASE     =     IMAGE_EXTENSIONS

