

'''simple docstring'''



from collections import OrderedDict
from typing import Mapping

from packaging import version

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


UpperCAmelCase					:			Union[str, Any]       =	logging.get_logger(__name__)

UpperCAmelCase					:			Union[str, Any]       =	{
    'facebook/levit-128S': 'https://huggingface.co/facebook/levit-128S/resolve/main/config.json',
    # See all LeViT models at https://huggingface.co/models?filter=levit
}







class 		lowerCAmelCase__  ( a   ):



 """simple docstring"""



 lowerCAmelCase__       = "levit"
 def __init__(						self   :			List[str]   ,				__SCREAMING_SNAKE_CASE   :			Tuple=224   ,				__SCREAMING_SNAKE_CASE   :			Any=3   ,				__SCREAMING_SNAKE_CASE   :			Tuple=3   ,				__SCREAMING_SNAKE_CASE   :			str=2   ,				__SCREAMING_SNAKE_CASE   :			Optional[Any]=1   ,				__SCREAMING_SNAKE_CASE   :			Dict=16   ,				__SCREAMING_SNAKE_CASE   :			Tuple=[128, 256, 384]   ,				__SCREAMING_SNAKE_CASE   :			str=[4, 8, 12]   ,				__SCREAMING_SNAKE_CASE   :			Optional[int]=[4, 4, 4]   ,				__SCREAMING_SNAKE_CASE   :			Optional[int]=[16, 16, 16]   ,				__SCREAMING_SNAKE_CASE   :			int=0   ,				__SCREAMING_SNAKE_CASE   :			Optional[Any]=[2, 2, 2]   ,				__SCREAMING_SNAKE_CASE   :			Dict=[2, 2, 2]   ,				__SCREAMING_SNAKE_CASE   :			Union[str, Any]=0.02   ,				**__SCREAMING_SNAKE_CASE   :			int   ,				)    ->					List[Any]:


      """simple docstring"""




      super().__init__(**__SCREAMING_SNAKE_CASE     )
      __SCREAMING_SNAKE_CASE      = image_size
      __SCREAMING_SNAKE_CASE      = num_channels
      __SCREAMING_SNAKE_CASE      = kernel_size
      __SCREAMING_SNAKE_CASE      = stride
      __SCREAMING_SNAKE_CASE      = padding
      __SCREAMING_SNAKE_CASE      = hidden_sizes
      __SCREAMING_SNAKE_CASE      = num_attention_heads
      __SCREAMING_SNAKE_CASE      = depths
      __SCREAMING_SNAKE_CASE      = key_dim
      __SCREAMING_SNAKE_CASE      = drop_path_rate
      __SCREAMING_SNAKE_CASE      = patch_size
      __SCREAMING_SNAKE_CASE      = attention_ratio
      __SCREAMING_SNAKE_CASE      = mlp_ratio
      __SCREAMING_SNAKE_CASE      = initializer_range
      __SCREAMING_SNAKE_CASE      = [
          ["""Subsample""", key_dim[0], hidden_sizes[0] // key_dim[0], 4, 2, 2],
          ["""Subsample""", key_dim[0], hidden_sizes[1] // key_dim[0], 4, 2, 2],
      ]







class 		lowerCAmelCase__  ( a   ):



 """simple docstring"""



 lowerCAmelCase__       = version.parse("1.11"   )
 @property
 def  UpperCAmelCase__						(						self   :			Optional[Any]     )    ->					Mapping[str, Mapping[int, str]]:


      """simple docstring"""




      return OrderedDict(
          [
              ("""pixel_values""", {0: """batch""", 1: """num_channels""", 2: """height""", 3: """width"""}),
          ]     )


 @property
 def  UpperCAmelCase__						(						self   :			List[str]     )    ->					float:


      """simple docstring"""




      return 1E-4









'''simple docstring'''



import importlib
import inspect
import os
import re


# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check_config_docstrings.py
UpperCAmelCase					:			Any       =	'src/transformers'


# This is to make sure the transformers module imported is the one in the repo.
UpperCAmelCase					:			Optional[int]       =	importlib.util.spec_from_file_location(
    'transformers',
    os.path.join(PATH_TO_TRANSFORMERS, '__init__.py'),
    submodule_search_locations=[PATH_TO_TRANSFORMERS],
)
UpperCAmelCase					:			Dict       =	spec.loader.load_module()

UpperCAmelCase					:			Dict       =	transformers.models.auto.configuration_auto.CONFIG_MAPPING

# Regex pattern used to find the checkpoint mentioned in the docstring of `config_class`.
# For example, `[bert-base-uncased](https://huggingface.co/bert-base-uncased)`
UpperCAmelCase					:			Dict       =	re.compile('\[(.+?)\]\((https://huggingface\.co/.+?)\)')


UpperCAmelCase					:			Any       =	{
    'CLIPConfigMixin',
    'DecisionTransformerConfigMixin',
    'EncoderDecoderConfigMixin',
    'RagConfigMixin',
    'SpeechEncoderDecoderConfigMixin',
    'VisionEncoderDecoderConfigMixin',
    'VisionTextDualEncoderConfigMixin',
}







def   a__			(    ):




     """simple docstring"""


     __SCREAMING_SNAKE_CASE      = []

     for config_class in list(CONFIG_MAPPING.values()		):
          __SCREAMING_SNAKE_CASE      = False

          # source code of `config_class`
          __SCREAMING_SNAKE_CASE      = inspect.getsource(a__		)
          __SCREAMING_SNAKE_CASE      = _re_checkpoint.findall(a__		)

          for checkpoint in checkpoints:
               # Each `checkpoint` is a tuple of a checkpoint name and a checkpoint link.
               # For example, `('bert-base-uncased', 'https://huggingface.co/bert-base-uncased')`
               __SCREAMING_SNAKE_CASE  ,     __SCREAMING_SNAKE_CASE      = checkpoint

               # verify the checkpoint name corresponds to the checkpoint link
               __SCREAMING_SNAKE_CASE      = F'https://huggingface.co/{ckpt_name}'
               if ckpt_link == ckpt_link_from_name:
                    __SCREAMING_SNAKE_CASE      = True
                    break

          __SCREAMING_SNAKE_CASE      = config_class.__name__
          if not checkpoint_found and name not in CONFIG_CLASSES_TO_IGNORE_FOR_DOCSTRING_CHECKPOINT_CHECK:
               configs_without_checkpoint.append(a__		)

     if len(a__		) > 0:
          __SCREAMING_SNAKE_CASE      = """\n""".join(sorted(a__		)		)
          raise ValueError(F'The following configurations don\'t contain any valid checkpoint:\n{message}'		)


if __name__ == "__main__":
  check_config_docstrings_have_checkpoints()






