'''simple docstring'''




import warnings
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


_A								=   logging.get_logger(__name__)

_A								=   {
    'nvidia/segformer-b0-finetuned-ade-512-512': (
        'https://huggingface.co/nvidia/segformer-b0-finetuned-ade-512-512/resolve/main/config.json'
    ),
    # See all SegFormer models at https://huggingface.co/models?filter=segformer
}


class       UpperCAmelCase__  (       _snake_case			):






   """simple docstring"""
   A							:       Tuple     =    '''segformer'''
   def __init__(self       ,				_a=3       ,				_a=4       ,				_a=[2, 2, 2, 2]       ,				_a=[8, 4, 2, 1]       ,				_a=[32, 64, 160, 256]       ,				_a=[7, 3, 3, 3]       ,				_a=[4, 2, 2, 2]       ,				_a=[1, 2, 5, 8]       ,				_a=[4, 4, 4, 4]       ,				_a="gelu"       ,				_a=0.0       ,				_a=0.0       ,				_a=0.1       ,				_a=0.02       ,				_a=0.1       ,				_a=1e-6       ,				_a=256       ,				_a=255       ,				**_a       ,				)    ->     Optional[int]:
        super().__init__(**_a				)

        if "reshape_last_stage" in kwargs and kwargs["reshape_last_stage"] is False:
             warnings.warn(
                 'Reshape_last_stage is set to False in this config. This argument is deprecated and will soon be'
                 ' removed, as the behaviour will default to that of reshape_last_stage = True.'       ,				_a       ,				)

        lowercase_					:       List[Any]     				=					num_channels
        lowercase_					:       Union[str, Any]     				=					num_encoder_blocks
        lowercase_					:       Dict     				=					depths
        lowercase_					:       Any     				=					sr_ratios
        lowercase_					:       Union[str, Any]     				=					hidden_sizes
        lowercase_					:       Tuple     				=					patch_sizes
        lowercase_					:       Union[str, Any]     				=					strides
        lowercase_					:       List[Any]     				=					mlp_ratios
        lowercase_					:       Optional[Any]     				=					num_attention_heads
        lowercase_					:       Optional[int]     				=					hidden_act
        lowercase_					:       Optional[int]     				=					hidden_dropout_prob
        lowercase_					:       Optional[int]     				=					attention_probs_dropout_prob
        lowercase_					:       Optional[Any]     				=					classifier_dropout_prob
        lowercase_					:       Dict     				=					initializer_range
        lowercase_					:       Tuple     				=					drop_path_rate
        lowercase_					:       int     				=					layer_norm_eps
        lowercase_					:       List[Any]     				=					decoder_hidden_size
        lowercase_					:       int     				=					kwargs.get('reshape_last_stage'       ,				_a				)
        lowercase_					:       List[Any]     				=					semantic_loss_ignore_index



class       UpperCAmelCase__  (       _snake_case			):






   """simple docstring"""
   A							:       List[str]     =    version.parse('''1.11'''			)
   @property
   def 		_lowerCamelCase (self				)    ->     Mapping[str, Mapping[int, str]]:
        return OrderedDict(
            [
                ('pixel_values', {0: 'batch', 1: 'num_channels', 2: 'height', 3: 'width'}),
            ]				)
   @property
   def 		_lowerCamelCase (self				)    ->     float:
        return 1e-4





   @property
   def 		_lowerCamelCase (self				)    ->     int:
        return 12





'''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


_A								=   {
    '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
}

_A								=   logging.get_logger(__name__)


class       UpperCAmelCase__  (       _snake_case			):






   """simple docstring"""
   A							:       List[str]     =    '''maskformer'''
   A							:       List[str]     =    {'''hidden_size''': '''mask_feature_size'''}
   A							:       Dict     =    ['''resnet''', '''swin''']
   A							:       Optional[Any]     =    ['''detr''']
   def __init__(self       ,				_a = 256       ,				_a = 256       ,				_a = 0.1       ,				_a = False       ,				_a = None       ,				_a = None       ,				_a = 0.02       ,				_a = 1.0       ,				_a = 1.0       ,				_a = 1.0       ,				_a = 20.0       ,				_a = None       ,				**_a       ,				)    ->     int:
        if backbone_config is None:
             # fall back to https://huggingface.co/microsoft/swin-base-patch4-window12-384-in22k
             lowercase_					:       List[Any]     				=					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(_a       ,				_a				):
             lowercase_					:       Dict     				=					backbone_config.pop('model_type'				)
             lowercase_					:       Tuple     				=					CONFIG_MAPPING[backbone_model_type]
             lowercase_					:       Tuple     				=					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_					:       str     				=					DetrConfig()
        else:
             # verify that the decoder is supported
             lowercase_					:       List[Any]     				=					(
                 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_					:       List[Any]     				=					CONFIG_MAPPING[decoder_type]
                  lowercase_					:       Tuple     				=					config_class.from_dict(_a				)

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

        lowercase_					:       List[Any]     				=					self.decoder_config.encoder_attention_heads
        lowercase_					:       Tuple     				=					self.decoder_config.num_hidden_layers
        super().__init__(**_a				)
   @classmethod
   def 		_lowerCamelCase (cls       ,				_a       ,				_a       ,				**_a				)    ->     Union[str, Any]:
        return cls(
            backbone_config=_a       ,				decoder_config=_a       ,				**_a       ,				)





   def 		_lowerCamelCase (self				)    ->     Dict[str, any]:
        lowercase_					:       Optional[int]     				=					copy.deepcopy(self.__dict__				)
        lowercase_					:       Union[str, Any]     				=					self.backbone_config.to_dict()
        lowercase_					:       Optional[Any]     				=					self.decoder_config.to_dict()
        lowercase_					:       Dict     				=					self.__class__.model_type
        return output




