
'''simple docstring'''





from typing import List

import datasets
from datasets.tasks import ImageClassification

from ..folder_based_builder import folder_based_builder


a__		: Union[str, Any]  							=							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__     :     Optional[Any]    					=       datasets.Image()
 UpperCAmelCase__     :     List[Any]    					=       'image'
 UpperCAmelCase__     :     Dict    					=       ImageFolderConfig
 UpperCAmelCase__     :     List[str]  # definition at the bottom of the script
 UpperCAmelCase__     :     str    					=       ImageClassification(image_column='image'   ,  label_column='label')
a__		: Optional[int]  							=							[
    ".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",
]
a__		: List[str]  							=							IMAGE_EXTENSIONS







from typing import Mapping

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


lowerCAmelCase__      		=					logging.get_logger(__name__)

lowerCAmelCase__      		=					{
    'google/long-t5-local-base': 'https://huggingface.co/google/long-t5-local-base/blob/main/config.json',
    'google/long-t5-local-large': 'https://huggingface.co/google/long-t5-local-large/blob/main/config.json',
    'google/long-t5-tglobal-base': 'https://huggingface.co/google/long-t5-tglobal-base/blob/main/config.json',
    'google/long-t5-tglobal-large': 'https://huggingface.co/google/long-t5-tglobal-large/blob/main/config.json',
}
class 							a_					(		SCREAMING_SNAKE_CASE		):






 '''simple docstring'''






 UpperCAmelCase_      					=   'longt5'
 UpperCAmelCase_      					=   ['past_key_values']
 UpperCAmelCase_      					=   {'hidden_size': 'd_model', 'num_attention_heads': 'num_heads', 'num_hidden_layers': 'num_layers'}




 def __init__(     self   :    Optional[Any]     ,       lowercase__   :    Union[str, Any]=32_128     ,       lowercase__   :    Union[str, Any]=512     ,       lowercase__   :    List[Any]=64     ,       lowercase__   :    Tuple=2_048     ,       lowercase__   :    List[Any]=6     ,       lowercase__   :    Any=None     ,       lowercase__   :    List[str]=8     ,       lowercase__   :    str=127     ,       lowercase__   :    Any=16     ,       lowercase__   :    str=32     ,       lowercase__   :    str=128     ,       lowercase__   :    Union[str, Any]=0.1     ,       lowercase__   :    List[Any]=1e-6     ,       lowercase__   :    Optional[Any]=1.0     ,       lowercase__   :    str="relu"     ,       lowercase__   :    List[str]=True     ,       lowercase__   :    Any="local"     ,       lowercase__   :    str=True     ,       lowercase__   :    Union[str, Any]=0     ,       lowercase__   :    Optional[int]=1     ,       **lowercase__   :    str     ,       ):







        '''simple docstring'''



        lowerCAmelCase__	      =   vocab_size
        lowerCAmelCase__	      =   d_model
        lowerCAmelCase__	      =   d_kv
        lowerCAmelCase__	      =   d_ff
        lowerCAmelCase__	      =   num_layers
        # default = symmetry
        lowerCAmelCase__	      =   num_decoder_layers if num_decoder_layers is not None else self.num_layers
        lowerCAmelCase__	      =   num_heads
        lowerCAmelCase__	      =   local_radius
        lowerCAmelCase__	      =   global_block_size
        lowerCAmelCase__	      =   relative_attention_num_buckets
        lowerCAmelCase__	      =   relative_attention_max_distance
        lowerCAmelCase__	      =   dropout_rate
        lowerCAmelCase__	      =   layer_norm_epsilon
        lowerCAmelCase__	      =   initializer_factor
        lowerCAmelCase__	      =   feed_forward_proj
        lowerCAmelCase__	      =   encoder_attention_type
        lowerCAmelCase__	      =   use_cache

        lowerCAmelCase__	      =   self.feed_forward_proj.split('-')
        lowerCAmelCase__	      =   act_info[-1]
        lowerCAmelCase__	      =   act_info[0] == 'gated'

        if len(lowercase__) > 1 and act_info[0] != "gated" or len(lowercase__) > 2:
               raise ValueError(
                   F"""`feed_forward_proj`: {feed_forward_proj} is not a valid activation function of the dense layer."""
                   'Please make sure `feed_forward_proj` is of the format `gated-{ACT_FN}` or `{ACT_FN}`, e.g. '
                   '\'gated-gelu\' or \'relu\'')

        # for backwards compatibility
        if feed_forward_proj == "gated-gelu":
               lowerCAmelCase__	      =   'gelu_new'

        super().__init__(
            pad_token_id=lowercase__     ,       eos_token_id=lowercase__     ,       is_encoder_decoder=lowercase__     ,       **lowercase__     ,       )






class 							a_					(		SCREAMING_SNAKE_CASE		):






 '''simple docstring'''






 @property
 def 						__snake_case		(     self   :    str):







        '''simple docstring'''



        lowerCAmelCase__	      =   {
            'input_ids': {0: 'batch', 1: 'encoder_sequence'},
            'attention_mask': {0: 'batch', 1: 'encoder_sequence'},
        }
        if self.use_past:
               lowerCAmelCase__	      =   'past_encoder_sequence + sequence'
               lowerCAmelCase__	      =   {0: 'batch'}
               lowerCAmelCase__	      =   {0: 'batch', 1: 'past_decoder_sequence + sequence'}
        else:
               lowerCAmelCase__	      =   {0: 'batch', 1: 'decoder_sequence'}
               lowerCAmelCase__	      =   {0: 'batch', 1: 'decoder_sequence'}

        if self.use_past:
               self.fill_with_past_key_values_(lowercase__     ,       direction='inputs')

        return common_inputs




 @property
 def 						__snake_case		(     self   :    Any):







        '''simple docstring'''



        return 13
