




'''simple docstring'''




from ...configuration_utils import PretrainedConfig
from ...utils import logging


a_      :		str							      =       logging.get_logger(__name__)

a_      :		Optional[int]							      =       {
    'caidas/swin2sr-classicalsr-x2-64': (
        'https://huggingface.co/caidas/swin2sr-classicalsr-x2-64/resolve/main/config.json'
    ),
}


class   __UpperCamelCase       ( _lowerCamelCase				):
       lowercase	:    int      						='swin2sr'

       lowercase	:    Any      						={
           'hidden_size': 'embed_dim',
           'num_attention_heads': 'num_heads',
           'num_hidden_layers': 'num_layers',
       }






       def __init__(							self,		lowerCAmelCase=64,		lowerCAmelCase=1,		lowerCAmelCase=3,		lowerCAmelCase=180,		lowerCAmelCase=[6, 6, 6, 6, 6, 6],		lowerCAmelCase=[6, 6, 6, 6, 6, 6],		lowerCAmelCase=8,		lowerCAmelCase=2.0,		lowerCAmelCase=True,		lowerCAmelCase=0.0,		lowerCAmelCase=0.0,		lowerCAmelCase=0.1,		lowerCAmelCase="gelu",		lowerCAmelCase=False,		lowerCAmelCase=0.0_2,		lowerCAmelCase=1e-5,		lowerCAmelCase=2,		lowerCAmelCase=1.0,		lowerCAmelCase="1conv",		lowerCAmelCase="pixelshuffle",		**lowerCAmelCase,		):



              """simple docstring"""







              super().__init__(**_UpperCamelCase  )

              lowerCamelCase_							=image_size
              lowerCamelCase_							=patch_size
              lowerCamelCase_							=num_channels
              lowerCamelCase_							=embed_dim
              lowerCamelCase_							=depths
              lowerCamelCase_							=len(_UpperCamelCase  )
              lowerCamelCase_							=num_heads
              lowerCamelCase_							=window_size
              lowerCamelCase_							=mlp_ratio
              lowerCamelCase_							=qkv_bias
              lowerCamelCase_							=hidden_dropout_prob
              lowerCamelCase_							=attention_probs_dropout_prob
              lowerCamelCase_							=drop_path_rate
              lowerCamelCase_							=hidden_act
              lowerCamelCase_							=use_absolute_embeddings
              lowerCamelCase_							=layer_norm_eps
              lowerCamelCase_							=initializer_range
              lowerCamelCase_							=upscale
              lowerCamelCase_							=img_range
              lowerCamelCase_							=resi_connection
              lowerCamelCase_							=upsampler











from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


snake_case__					:							Optional[Any]													=     {'configuration_ibert': ['IBERT_PRETRAINED_CONFIG_ARCHIVE_MAP', 'IBertConfig', 'IBertOnnxConfig']}

try:
       if not is_torch_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       snake_case__					:							List[str]													=     [
           'IBERT_PRETRAINED_MODEL_ARCHIVE_LIST',
           'IBertForMaskedLM',
           'IBertForMultipleChoice',
           'IBertForQuestionAnswering',
           'IBertForSequenceClassification',
           'IBertForTokenClassification',
           'IBertModel',
           'IBertPreTrainedModel',
       ]

if TYPE_CHECKING:
       from .configuration_ibert import IBERT_PRETRAINED_CONFIG_ARCHIVE_MAP, IBertConfig, IBertOnnxConfig

       try:
              if not is_torch_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .modeling_ibert import (
                  IBERT_PRETRAINED_MODEL_ARCHIVE_LIST,
                  IBertForMaskedLM,
                  IBertForMultipleChoice,
                  IBertForQuestionAnswering,
                  IBertForSequenceClassification,
                  IBertForTokenClassification,
                  IBertModel,
                  IBertPreTrainedModel,
              )

else:
       import sys

       snake_case__					:							Dict													=     _LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)





