





'''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


lowerCAmelCase					:     Tuple												={
    '''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
}

lowerCAmelCase					:     Tuple												=logging.get_logger(__name__)
class       a_   (				_lowerCAmelCase							):
     __A      =			"maskformer"
     __A      =			{"hidden_size": "mask_feature_size"}
     __A      =			["resnet", "swin"]
     __A      =			["detr"]





     def __init__( self		:					Tuple	,      lowercase		:					int = 256	,      lowercase		:					int = 256	,      lowercase		:					float = 0.1	,      lowercase		:					bool = False	,      lowercase		:					Optional[Dict] = None	,      lowercase		:					Optional[Dict] = None	,      lowercase		:					float = 0.02	,      lowercase		:					float = 1.0	,      lowercase		:					float = 1.0	,      lowercase		:					float = 1.0	,      lowercase		:					float = 20.0	,      lowercase		:					Optional[bool] = None	,      **lowercase		:					Tuple	,      ):





        """simple docstring"""




        if backbone_config is None:
           # fall back to https://huggingface.co/microsoft/swin-base-patch4-window12-384-in22k
           lowercase_			:Optional[int]    			= SwinConfig(
               image_size=384	,      in_channels=3	,      patch_size=4	,      embed_dim=128	,      depths=[2, 2, 18, 2]	,      num_heads=[4, 8, 16, 32]	,      window_size=12	,      drop_path_rate=0.3	,      out_features=["stage1", "stage2", "stage3", "stage4"]	,      )

        if isinstance(lowercase	,      lowercase						):
           lowercase_			:List[str]    			= backbone_config.pop("model_type"						)
           lowercase_			:int    			= CONFIG_MAPPING[backbone_model_type]
           lowercase_			:Optional[int]    			= config_class.from_dict(lowercase						)

        # 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_			:Tuple    			= DetrConfig()
        else:
           # verify that the decoder is supported
           lowercase_			:List[Any]    			= (
               decoder_config.pop("model_type"						) if isinstance(lowercase	,      lowercase						) 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(lowercase	,      lowercase						):
              lowercase_			:Any    			= CONFIG_MAPPING[decoder_type]
              lowercase_			:Any    			= config_class.from_dict(lowercase						)

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

        lowercase_			:Dict    			= self.decoder_config.encoder_attention_heads
        lowercase_			:Dict    			= self.decoder_config.num_hidden_layers
        super().__init__(**lowercase						)





     @classmethod
     def 							lowercase__      ( cls		:					Union[str, Any]	,      lowercase		:					PretrainedConfig	,      lowercase		:					PretrainedConfig	,      **lowercase		:					str						):





        """simple docstring"""




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







     def 							lowercase__      ( self		:					Dict						):





        """simple docstring"""




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









'''simple docstring'''


import pytest

from datasets import inspect_metric, list_metrics, load_metric
@pytest.fixture
def 							UpperCAmelCase_  (						__lowerCamelCase					:					List[str] ):
   monkeypatch.setattr("datasets.utils.deprecation_utils._emitted_deprecation_warnings"	,set() )
@pytest.fixture
def 							UpperCAmelCase_  (						__lowerCamelCase					:					Any ):
   class       a_   :





        def __init__( self		:					int	,      lowercase		:					int						):





           """simple docstring"""




           lowercase_			:Optional[Any]    			= metric_id







   class       a_   :
        __A      =			[MetricMock(_lowerCAmelCase							) for metric_id in ["accuracy", "mse", "precision", "codeparrot/apps_metric"]]





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





           """simple docstring"""




           return self._metrics







   monkeypatch.setattr("datasets.inspect.huggingface_hub"	,HfhMock() )


@pytest.mark.parametrize(
    "func, args"	,[(load_metric, ("metrics/mse",)), (list_metrics, ()), (inspect_metric, ("metrics/mse", "tmp_path"))] )
def 							UpperCAmelCase_  (						__lowerCamelCase					:					Union[str, Any]	,__lowerCamelCase					:					int	,__lowerCamelCase					:					Optional[int]	,__lowerCamelCase					:					Union[str, Any]	,__lowerCamelCase					:					Tuple ):
   if "tmp_path" in args:
      lowercase_			:Union[str, Any]    			= tuple(arg if arg != "tmp_path" else tmp_path for arg in args )
   with pytest.warns(__lowerCamelCase	,match="https://huggingface.co/docs/evaluate" ):
      func(*__lowerCamelCase )


