'''simple docstring'''




import copy
from typing import Dict

from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto.configuration_auto import CONFIG_MAPPING
from ..bit import BitConfig


__SCREAMING_SNAKE_CASE :  Tuple  =						logging.get_logger(__name__)

__SCREAMING_SNAKE_CASE :  Any  =						{
    'google/vit-hybrid-base-bit-384': 'https://huggingface.co/vit-hybrid-base-bit-384/resolve/main/config.json',
    # See all ViT hybrid models at https://huggingface.co/models?filter=vit
}

class 			lowerCamelCase_			(snake_case__					):
      '''simple docstring'''

      __UpperCamelCase:						Optional[int]      			=		"vit-hybrid"




      def __init__( self		:       List[Any]		,      A		:       Optional[Any]=None		,      A		:       Tuple=768		,      A		:       List[str]=12		,      A		:       int=12		,      A		:       Optional[Any]=3072		,      A		:       List[Any]="gelu"		,      A		:       Union[str, Any]=0.0		,      A		:       Optional[Any]=0.0		,      A		:       List[str]=0.02		,      A		:       Dict=1E-12		,      A		:       List[str]=224		,      A		:       Union[str, Any]=1		,      A		:       List[Any]=3		,      A		:       Optional[int]=[1, 1024, 24, 24]		,      A		:       str=True		,      **A		:       Tuple		,      ):
             super().__init__(**A )

             if backbone_config is None:
                    logger.info("`backbone_config` is `None`. Initializing the config with a `BiT` backbone." )
                    _UpperCAmelCase  :						Dict							   =					{
                        '''global_padding''': '''same''',
                        '''layer_type''': '''bottleneck''',
                        '''depths''': [3, 4, 9],
                        '''out_features''': ['''stage3'''],
                        '''embedding_dynamic_padding''': True,
                    }

             if isinstance(A		,      A ):
                    if "model_type" in backbone_config:
                           _UpperCAmelCase  :						List[str]							   =					CONFIG_MAPPING[backbone_config['''model_type''']]
                    else:
                           logger.info(
                               "`model_type` is not found in `backbone_config`. Use `Bit` as the backbone configuration class." )
                           _UpperCAmelCase  :						int							   =					BitConfig
                    _UpperCAmelCase  :						List[Any]							   =					backbone_config_class(**A )

             _UpperCAmelCase  :						Tuple							   =					backbone_featmap_shape
             _UpperCAmelCase  :						Tuple							   =					backbone_config
             _UpperCAmelCase  :						Tuple							   =					hidden_size
             _UpperCAmelCase  :						Dict							   =					num_hidden_layers
             _UpperCAmelCase  :						Optional[int]							   =					num_attention_heads
             _UpperCAmelCase  :						str							   =					intermediate_size
             _UpperCAmelCase  :						Tuple							   =					hidden_act
             _UpperCAmelCase  :						Dict							   =					hidden_dropout_prob
             _UpperCAmelCase  :						str							   =					attention_probs_dropout_prob
             _UpperCAmelCase  :						int							   =					initializer_range
             _UpperCAmelCase  :						Tuple							   =					layer_norm_eps
             _UpperCAmelCase  :						List[str]							   =					image_size
             _UpperCAmelCase  :						Union[str, Any]							   =					patch_size
             _UpperCAmelCase  :						List[Any]							   =					num_channels
             _UpperCAmelCase  :						Any							   =					qkv_bias





      def   _A			( self		:       List[Any] ):
             _UpperCAmelCase  :						Tuple							   =					copy.deepcopy(self.__dict__ )
             _UpperCAmelCase  :						List[str]							   =					self.backbone_config.to_dict()
             _UpperCAmelCase  :						List[Any]							   =					self.__class__.model_type
             return output


'''simple docstring'''




import platform
from argparse import ArgumentParser

import huggingface_hub
import pandas
import pyarrow

from datasets import __version__ as version
from datasets.commands import BaseDatasetsCLICommand

def 			UpperCamelCase_							(      _UpperCAmelCase						:   List[str]					)					->					Union[str, Any]:


       """simple docstring"""







       return EnvironmentCommand()


class 			lowerCamelCase_			(snake_case__					):
      '''simple docstring'''

      @staticmethod
      def   _A			( A		:       ArgumentParser ):
             _UpperCAmelCase  :						List[str]							   =					parser.add_parser("env"		,      help="Print relevant system environment info." )
             download_parser.set_defaults(func=A )




      def   _A			( self		:       List[str] ):
             _UpperCAmelCase  :						str							   =					{
                 "`datasets` version": version,
                 "Platform": platform.platform(),
                 "Python version": platform.python_version(),
                 "Huggingface_hub version": huggingface_hub.__version__,
                 "PyArrow version": pyarrow.__version__,
                 "Pandas version": pandas.__version__,
             }

             print("\nCopy-and-paste the text below in your GitHub issue.\n" )
             print(self.format_dict(A ) )

             return info





      @staticmethod
      def   _A			( A		:       Tuple ):
             return "\n".join([F"""- {prop}: {val}""" for prop, val in d.items()] ) + "\n"

