



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


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

__snake_case						:int      		=     {
    '''vinvino02/glpn-kitti''': '''https://huggingface.co/vinvino02/glpn-kitti/resolve/main/config.json''',
    # See all GLPN models at https://huggingface.co/models?filter=glpn
}

class     _A       (	__UpperCAmelCase    ):
       UpperCamelCase__  :    Optional[Any]											=						'''glpn'''



       def __init__(		self							:     Any     ,		__SCREAMING_SNAKE_CASE							:     List[Any]=3     ,		__SCREAMING_SNAKE_CASE							:     Optional[Any]=4     ,		__SCREAMING_SNAKE_CASE							:     Dict=[2, 2, 2, 2]     ,		__SCREAMING_SNAKE_CASE							:     int=[8, 4, 2, 1]     ,		__SCREAMING_SNAKE_CASE							:     Optional[int]=[32, 64, 160, 256]     ,		__SCREAMING_SNAKE_CASE							:     Tuple=[7, 3, 3, 3]     ,		__SCREAMING_SNAKE_CASE							:     List[Any]=[4, 2, 2, 2]     ,		__SCREAMING_SNAKE_CASE							:     Optional[Any]=[1, 2, 5, 8]     ,		__SCREAMING_SNAKE_CASE							:     Optional[int]=[4, 4, 4, 4]     ,		__SCREAMING_SNAKE_CASE							:     Any="gelu"     ,		__SCREAMING_SNAKE_CASE							:     Union[str, Any]=0.0     ,		__SCREAMING_SNAKE_CASE							:     str=0.0     ,		__SCREAMING_SNAKE_CASE							:     Optional[Any]=0.02     ,		__SCREAMING_SNAKE_CASE							:     List[Any]=0.1     ,		__SCREAMING_SNAKE_CASE							:     int=1E-6     ,		__SCREAMING_SNAKE_CASE							:     Tuple=64     ,		__SCREAMING_SNAKE_CASE							:     Dict=10     ,		__SCREAMING_SNAKE_CASE							:     Optional[int]=-1     ,		**__SCREAMING_SNAKE_CASE							:     Dict     ,		):


           '''simple docstring'''

           super().__init__(**__SCREAMING_SNAKE_CASE)

           __a						       =				num_channels
           __a						       =				num_encoder_blocks
           __a						       =				depths
           __a						       =				sr_ratios
           __a						       =				hidden_sizes
           __a						       =				patch_sizes
           __a						       =				strides
           __a						       =				mlp_ratios
           __a						       =				num_attention_heads
           __a						       =				hidden_act
           __a						       =				hidden_dropout_prob
           __a						       =				attention_probs_dropout_prob
           __a						       =				initializer_range
           __a						       =				drop_path_rate
           __a						       =				layer_norm_eps
           __a						       =				decoder_hidden_size
           __a						       =				max_depth
           __a						       =				head_in_index










import copy
from dataclasses import dataclass
from pathlib import Path
from typing import Dict, Optional, Union

@dataclass
class     _A       :
       UpperCamelCase__  :    Optional[Union[str, Path]]											=						None
       UpperCamelCase__  :    bool											=						False
       UpperCamelCase__  :    bool											=						False
       UpperCamelCase__  :    bool											=						False
       UpperCamelCase__  :    Optional[Dict]											=						None
       UpperCamelCase__  :    Optional[str]											=						None
       UpperCamelCase__  :    bool											=						False
       UpperCamelCase__  :    bool											=						False
       UpperCamelCase__  :    bool											=						False
       UpperCamelCase__  :    bool											=						True
       UpperCamelCase__  :    Optional[int]											=						None
       UpperCamelCase__  :    int											=						1
       UpperCamelCase__  :    Optional[Union[str, bool]]											=						None
       UpperCamelCase__  :    bool											=						False
       UpperCamelCase__  :    Optional[Dict]											=						None
       UpperCamelCase__  :    Optional[str]											=						None



       def 		_lowerCamelCase			(		self							:     Union[str, Any]):


           '''simple docstring'''

           return self.__class__(**{k: copy.deepcopy(__SCREAMING_SNAKE_CASE) for k, v in self.__dict__.items()})





