


import copy

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


SCREAMING_SNAKE_CASE :   List[str]							      =				logging.get_logger(__name__)






class _lowerCamelCase(		_a     ):
       lowercase_				:			Optional[Any]									=    "upernet"
       def __init__(      self,   lowerCamelCase=None,   lowerCamelCase=5_12,   lowerCamelCase=0.0_2,   lowerCamelCase=[1, 2, 3, 6],   lowerCamelCase=True,   lowerCamelCase=0.4,   lowerCamelCase=3_84,   lowerCamelCase=2_56,   lowerCamelCase=1,   lowerCamelCase=False,   lowerCamelCase=2_55,   **lowerCamelCase,   ) ->     Tuple:




           """simple docstring"""

           super().__init__(**UpperCamelCase_)

           if backbone_config is None:
               logger.info('`backbone_config` is `None`. Initializing the config with the default `ResNet` backbone.')
               _lowercase :							int   	=	CONFIG_MAPPING["resnet"](out_features=['stage1', 'stage2', 'stage3', 'stage4'])
           elif isinstance(UpperCamelCase_,   UpperCamelCase_):
               _lowercase :							Any   	=	backbone_config.get('model_type')
               _lowercase :							str   	=	CONFIG_MAPPING[backbone_model_type]
               _lowercase :							Union[str, Any]   	=	config_class.from_dict(UpperCamelCase_)

           _lowercase :							List[Any]   	=	backbone_config
           _lowercase :							Dict   	=	hidden_size
           _lowercase :							Optional[Any]   	=	initializer_range
           _lowercase :							str   	=	pool_scales
           _lowercase :							Tuple   	=	use_auxiliary_head
           _lowercase :							int   	=	auxiliary_loss_weight
           _lowercase :							List[Any]   	=	auxiliary_in_channels
           _lowercase :							Tuple   	=	auxiliary_channels
           _lowercase :							Any   	=	auxiliary_num_convs
           _lowercase :							Tuple   	=	auxiliary_concat_input
           _lowercase :							List[Any]   	=	loss_ignore_index




       def     UpperCamelCase  (      self) ->     int:




           """simple docstring"""

           _lowercase :							Optional[int]   	=	copy.deepcopy(self.__dict__)
           _lowercase :							Optional[Any]   	=	self.backbone_config.to_dict()
           _lowercase :							Any   	=	self.__class__.model_type
           return output






import pytest


SCREAMING_SNAKE_CASE :   Optional[Any]							      =				"__dummy_dataset1__"

SCREAMING_SNAKE_CASE :   int							      =				"\nimport json\nimport os\n\nimport datasets\n\n\nREPO_URL = \"https://huggingface.co/datasets/albertvillanova/tests-raw-jsonl/resolve/main/\"\nURLS = {\"train\": REPO_URL + \"wikiann-bn-train.jsonl\", \"validation\": REPO_URL + \"wikiann-bn-validation.jsonl\"}\n\n\nclass __DummyDataset1__(datasets.GeneratorBasedBuilder):\n\n    def _info(self):\n        features = datasets.Features(\n            {\n                \"tokens\": datasets.Sequence(datasets.Value(\"string\")),\n                \"ner_tags\": datasets.Sequence(\n                    datasets.features.ClassLabel(\n                        names=[\n                            \"O\",\n                            \"B-PER\",\n                            \"I-PER\",\n                            \"B-ORG\",\n                            \"I-ORG\",\n                            \"B-LOC\",\n                            \"I-LOC\",\n                        ]\n                    )\n                ),\n                \"langs\": datasets.Sequence(datasets.Value(\"string\")),\n                \"spans\": datasets.Sequence(datasets.Value(\"string\")),\n            }\n        )\n        return datasets.DatasetInfo(features=features)\n\n    def _split_generators(self, dl_manager):\n        dl_path = dl_manager.download(URLS)\n        return [\n            datasets.SplitGenerator(datasets.Split.TRAIN, gen_kwargs={\"filepath\": dl_path[\"train\"]}),\n            datasets.SplitGenerator(datasets.Split.VALIDATION, gen_kwargs={\"filepath\": dl_path[\"validation\"]}),\n        ]\n\n    def _generate_examples(self, filepath):\n        with open(filepath, \"r\", encoding=\"utf-8\") as f:\n            for i, line in enumerate(f):\n                yield i, json.loads(line)\n"



@pytest.fixture
def        UpperCamelCase_(   )					->		Dict:
    return DATASET_LOADING_SCRIPT_NAME



@pytest.fixture
def        UpperCamelCase_(   )					->		List[Any]:
    return DATASET_LOADING_SCRIPT_CODE



@pytest.fixture
def        UpperCamelCase_(   lowerCamelCase_							,				lowerCamelCase_							,				lowerCamelCase_				)					->		int:
    _lowercase :							List[str]   	=	dataset_loading_script_name
    _lowercase :							Union[str, Any]   	=	tmp_path / 'datasets' / script_name
    script_dir.mkdir(parents=lowerCamelCase_				)
    _lowercase :							Optional[int]   	=	script_dir / F'''{script_name}.py'''
    with open(lowerCamelCase_							,				'w'				) as f:
        f.write(lowerCamelCase_				)
    return str(lowerCamelCase_				)


