



'''simple docstring'''

import copy
from typing import Dict, List, Optional

from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING


UpperCAmelCase     		=   {
    'facebook/mask2former-swin-small-coco-instance': (
        'https://huggingface.co/facebook/mask2former-swin-small-coco-instance/blob/main/config.json'
    )
    # See all Mask2Former models at https://huggingface.co/models?filter=mask2former
}

UpperCAmelCase     		=   logging.get_logger(__name__)

class __snake_case(				_lowerCAmelCase ):


      '''simple docstring'''



      UpperCAmelCase							:   Dict									=		"mask2former"
      UpperCAmelCase							:   Union[str, Any]									=		["swin"]
      UpperCAmelCase							:   Optional[Any]									=		{"hidden_size": "hidden_dim"}


      def __init__( self     ,	A_ = None     ,	A_ = 256     ,	A_ = 256     ,	A_ = 256     ,	A_ = 1024     ,	A_ = "relu"     ,	A_ = 6     ,	A_ = 10     ,	A_ = 8     ,	A_ = 0.0     ,	A_ = 2048     ,	A_ = False     ,	A_ = False     ,	A_ = 4     ,	A_ = 255     ,	A_ = 100     ,	A_ = 0.1     ,	A_ = 2.0     ,	A_ = 5.0     ,	A_ = 5.0     ,	A_ = 1_2544     ,	A_ = 3.0     ,	A_ = 0.7_5     ,	A_ = 0.0_2     ,	A_ = 1.0     ,	A_ = True     ,	A_ = [4, 8, 16, 32]     ,	A_ = None     ,	**A_     ,	)     ->     List[Any]:
       if backbone_config is None:
        logger.info("""`backbone_config` is `None`. Initializing the config with the default `Swin` backbone."""				)
        lowerCAmelCase   =     CONFIG_MAPPING["""swin"""](
            image_size=224     ,	in_channels=3     ,	patch_size=4     ,	embed_dim=96     ,	depths=[2, 2, 18, 2]     ,	num_heads=[3, 6, 12, 24]     ,	window_size=7     ,	drop_path_rate=0.3     ,	use_absolute_embeddings=A_     ,	out_features=["""stage1""", """stage2""", """stage3""", """stage4"""]     ,	)

       if isinstance(A_     ,	A_				):
        lowerCAmelCase   =     backbone_config.pop("""model_type"""				)
        lowerCAmelCase   =     CONFIG_MAPPING[backbone_model_type]
        lowerCAmelCase   =     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 Mask2Former. '
            f'Supported model types: {",".join(self.backbones_supported				)}'				)

       lowerCAmelCase   =     backbone_config
       lowerCAmelCase   =     feature_size
       lowerCAmelCase   =     mask_feature_size
       lowerCAmelCase   =     hidden_dim
       lowerCAmelCase   =     encoder_feedforward_dim
       lowerCAmelCase   =     activation_function
       lowerCAmelCase   =     encoder_layers
       lowerCAmelCase   =     decoder_layers
       lowerCAmelCase   =     num_attention_heads
       lowerCAmelCase   =     dropout
       lowerCAmelCase   =     dim_feedforward
       lowerCAmelCase   =     pre_norm
       lowerCAmelCase   =     enforce_input_projection
       lowerCAmelCase   =     common_stride
       lowerCAmelCase   =     ignore_value
       lowerCAmelCase   =     num_queries
       lowerCAmelCase   =     no_object_weight
       lowerCAmelCase   =     class_weight
       lowerCAmelCase   =     mask_weight
       lowerCAmelCase   =     dice_weight
       lowerCAmelCase   =     train_num_points
       lowerCAmelCase   =     oversample_ratio
       lowerCAmelCase   =     importance_sample_ratio
       lowerCAmelCase   =     init_std
       lowerCAmelCase   =     init_xavier_std
       lowerCAmelCase   =     use_auxiliary_loss
       lowerCAmelCase   =     feature_strides
       lowerCAmelCase   =     output_auxiliary_logits
       lowerCAmelCase   =     decoder_layers

       super().__init__(**A_				)


      @classmethod
      def     __snake_case   ( cls     ,	A_     ,	**A_				)     ->     Tuple:
       return cls(
           backbone_config=A_     ,	**A_     ,	)




      def     __snake_case   ( self				)     ->     Dict[str, any]:
       lowerCAmelCase   =     copy.deepcopy(self.__dict__				)
       lowerCAmelCase   =     self.backbone_config.to_dict()
       lowerCAmelCase   =     self.__class__.model_type
       return output




'''simple docstring'''

import pytest

import datasets


# Import fixture modules as plugins
UpperCAmelCase     		=   ['tests.fixtures.files', 'tests.fixtures.hub', 'tests.fixtures.fsspec']






def 		_snake_case		( _SCREAMING_SNAKE_CASE					:						str							,		_SCREAMING_SNAKE_CASE					:						int							)      ->						Optional[int]:







	"""simple docstring"""
	# Mark tests as "unit" by default if not marked as "integration" (or already marked as "unit")
	for item in items:
		if any(marker in item.keywords for marker in ["""integration""", """unit"""]							):
			continue
		item.add_marker(pytest.mark.unit							)






def 		_snake_case		( _SCREAMING_SNAKE_CASE					:						List[str]							)      ->						Any:







	"""simple docstring"""
	config.addinivalue_line("""markers"""							,		"""torchaudio_latest: mark test to run with torchaudio>=0.12"""							)






@pytest.fixture(autouse=_SCREAMING_SNAKE_CASE							)
def 		_snake_case		( _SCREAMING_SNAKE_CASE					:						Dict							,		_SCREAMING_SNAKE_CASE					:						Dict							)      ->						str:







	"""simple docstring"""
	# test_hf_cache_home = tmp_path_factory.mktemp("cache")  # TODO: why a cache dir per test function does not work?
	lowerCAmelCase   =     tmp_path_factory.getbasetemp() / """cache"""
	lowerCAmelCase   =     test_hf_cache_home / """datasets"""
	lowerCAmelCase   =     test_hf_cache_home / """metrics"""
	lowerCAmelCase   =     test_hf_cache_home / """modules"""
	monkeypatch.setattr("""datasets.config.HF_DATASETS_CACHE"""							,		str(_SCREAMING_SNAKE_CASE							)							)
	monkeypatch.setattr("""datasets.config.HF_METRICS_CACHE"""							,		str(_SCREAMING_SNAKE_CASE							)							)
	monkeypatch.setattr("""datasets.config.HF_MODULES_CACHE"""							,		str(_SCREAMING_SNAKE_CASE							)							)
	lowerCAmelCase   =     test_hf_datasets_cache / """downloads"""
	monkeypatch.setattr("""datasets.config.DOWNLOADED_DATASETS_PATH"""							,		str(_SCREAMING_SNAKE_CASE							)							)
	lowerCAmelCase   =     test_hf_datasets_cache / """downloads""" / """extracted"""
	monkeypatch.setattr("""datasets.config.EXTRACTED_DATASETS_PATH"""							,		str(_SCREAMING_SNAKE_CASE							)							)






@pytest.fixture(autouse=_SCREAMING_SNAKE_CASE							,		scope="""session"""							)
def 		_snake_case		( )      ->						Optional[Any]:







	"""simple docstring"""
	datasets.disable_progress_bar()






@pytest.fixture(autouse=_SCREAMING_SNAKE_CASE							)
def 		_snake_case		( _SCREAMING_SNAKE_CASE					:						Any							)      ->						Optional[int]:







	"""simple docstring"""
	# don't take tests into account when counting downloads
	monkeypatch.setattr("""datasets.config.HF_UPDATE_DOWNLOAD_COUNTS"""							,		_SCREAMING_SNAKE_CASE							)






@pytest.fixture
def 		_snake_case		( _SCREAMING_SNAKE_CASE					:						List[str]							)      ->						str:







	"""simple docstring"""
	# Required to suppress RemovedIn20Warning when feature(s) are not compatible with SQLAlchemy 2.0
	# To be removed once SQLAlchemy 2.0 supported
	monkeypatch.setattr("""sqlalchemy.util.deprecations.SILENCE_UBER_WARNING"""							,		_SCREAMING_SNAKE_CASE							)