'''simple docstring'''
import copy
from typing import Dict, Optional

from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING
from ..detr import DetrConfig
from ..swin import SwinConfig


UpperCamelCase__ =			{
    'facebook/maskformer-swin-base-ade': (
        'https://huggingface.co/facebook/maskformer-swin-base-ade/blob/main/config.json'
    )
    # See all MaskFormer models at https://huggingface.co/models?filter=maskformer
}

UpperCamelCase__ =			logging.get_logger(__name__)


class        _UpperCAmelCase						(		snake_case			):
    __lowerCamelCase:   str		       =    'maskformer'
    __lowerCamelCase:   str		       =    {'hidden_size': 'mask_feature_size'}
    __lowerCamelCase:   Optional[int]		       =    ['resnet', 'swin']
    __lowerCamelCase:   Any		       =    ['detr']




    def __init__(			self  :       str  ,     a  :       int = 2_5_6  ,     a  :       int = 2_5_6  ,     a  :       float = 0.1  ,     a  :       bool = False  ,     a  :       Optional[Dict] = None  ,     a  :       Optional[Dict] = None  ,     a  :       float = 0.02  ,     a  :       float = 1.0  ,     a  :       float = 1.0  ,     a  :       float = 1.0  ,     a  :       float = 20.0  ,     a  :       Optional[bool] = None  ,     **a  :       List[str]  ,     ):






       '''simple docstring'''






       if backbone_config is None:
          # fall back to https://huggingface.co/microsoft/swin-base-patch4-window12-384-in22k
          lowercase_	:    int           =     SwinConfig(
              image_size=3_8_4  ,     in_channels=3  ,     patch_size=4  ,     embed_dim=1_2_8  ,     depths=[2, 2, 1_8, 2]  ,     num_heads=[4, 8, 1_6, 3_2]  ,     window_size=1_2  ,     drop_path_rate=0.3  ,     out_features=["stage1", "stage2", "stage3", "stage4"]  ,     )

       if isinstance(__A  ,     __A			):
          lowercase_	:    Optional[Any]           =     backbone_config.pop("model_type"			)
          lowercase_	:    str           =     CONFIG_MAPPING[backbone_model_type]
          lowercase_	:    Union[str, Any]           =     config_class.from_dict(__A			)

       # verify that the backbone is supported
       if backbone_config.model_type not in self.backbones_supported:
          logger.warning_once(
              f"""Backbone {backbone_config.model_type} is not a supported model and may not be compatible with MaskFormer. """
              f"""Supported model types: {",".join(self.backbones_supported			)}"""			)

       if decoder_config is None:
          # fall back to https://huggingface.co/facebook/detr-resnet-50
          lowercase_	:    Optional[Any]           =     DetrConfig()
       else:
          # verify that the decoder is supported
          lowercase_	:    Dict           =     (
              decoder_config.pop("model_type"			) if isinstance(__A  ,     __A			) else decoder_config.model_type
          )
          if decoder_type not in self.decoders_supported:
             raise ValueError(
                 f"""Transformer Decoder {decoder_type} not supported, please use one of"""
                 f""" {",".join(self.decoders_supported			)}"""			)
          if isinstance(__A  ,     __A			):
             lowercase_	:    str           =     CONFIG_MAPPING[decoder_type]
             lowercase_	:    List[str]           =     config_class.from_dict(__A			)

       lowercase_	:    Tuple           =     backbone_config
       lowercase_	:    str           =     decoder_config
       # main feature dimension for the model
       lowercase_	:    Dict           =     fpn_feature_size
       lowercase_	:    Any           =     mask_feature_size
       # initializer
       lowercase_	:    Optional[int]           =     init_std
       lowercase_	:    str           =     init_xavier_std
       # Hungarian matcher && loss
       lowercase_	:    Optional[int]           =     cross_entropy_weight
       lowercase_	:    Union[str, Any]           =     dice_weight
       lowercase_	:    Optional[Any]           =     mask_weight
       lowercase_	:    Any           =     use_auxiliary_loss
       lowercase_	:    List[Any]           =     no_object_weight
       lowercase_	:    List[Any]           =     output_auxiliary_logits

       lowercase_	:    int           =     self.decoder_config.encoder_attention_heads
       lowercase_	:    Optional[Any]           =     self.decoder_config.num_hidden_layers
       super().__init__(**__A			)




    @classmethod
    def 				lowerCAmelCase__				(			cls  :       Any  ,     a  :       PretrainedConfig  ,     a  :       PretrainedConfig  ,     **a  :       Optional[int]			):






       '''simple docstring'''






       return cls(
           backbone_config=__A  ,     decoder_config=__A  ,     **__A  ,     )





    def 				lowerCAmelCase__				(			self  :       Any			):






       '''simple docstring'''






       lowercase_	:    Any           =     copy.deepcopy(self.__dict__			)
       lowercase_	:    Dict           =     self.backbone_config.to_dict()
       lowercase_	:    Union[str, Any]           =     self.decoder_config.to_dict()
       lowercase_	:    Tuple           =     self.__class__.model_type
       return output












'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging


UpperCamelCase__ =			logging.get_logger(__name__)

UpperCamelCase__ =			{
    'abeja/gpt-neox-japanese-2.7b': 'https://huggingface.co/abeja/gpt-neox-japanese-2.7b/resolve/main/config.json',
}


class        _UpperCAmelCase						(		snake_case			):
    __lowerCamelCase:   List[Any]		       =    'gpt_neox_japanese'




    def __init__(			self  :       List[str]  ,     a  :       List[Any]=3_2_0_0_0  ,     a  :       Union[str, Any]=2_5_6_0  ,     a  :       Optional[Any]=3_2  ,     a  :       Any=3_2  ,     a  :       str=4  ,     a  :       Optional[int]="gelu"  ,     a  :       Optional[Any]=1.00  ,     a  :       Dict=1_0_0_0_0  ,     a  :       List[Any]=2_0_4_8  ,     a  :       Dict=0.02  ,     a  :       int=1e-5  ,     a  :       Optional[int]=True  ,     a  :       Union[str, Any]=3_1_9_9_6  ,     a  :       List[Any]=3_1_9_9_9  ,     a  :       List[str]=0.1  ,     a  :       Dict=0.0  ,     **a  :       Union[str, Any]  ,     ):






       '''simple docstring'''






       super().__init__(bos_token_id=a  ,     eos_token_id=a  ,     **a			)
       lowercase_	:    int           =     vocab_size
       lowercase_	:    int           =     max_position_embeddings
       lowercase_	:    List[str]           =     hidden_size
       lowercase_	:    Any           =     num_hidden_layers
       lowercase_	:    Any           =     num_attention_heads
       lowercase_	:    List[Any]           =     intermediate_multiple_size
       lowercase_	:    List[str]           =     hidden_act
       lowercase_	:    Optional[int]           =     rotary_pct
       lowercase_	:    Tuple           =     rotary_emb_base
       lowercase_	:    Optional[Any]           =     initializer_range
       lowercase_	:    List[str]           =     layer_norm_eps
       lowercase_	:    List[str]           =     use_cache
       lowercase_	:    Any           =     attention_dropout
       lowercase_	:    List[Any]           =     hidden_dropout




