






from typing import TYPE_CHECKING

# rely on isort to merge the imports
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


__UpperCAmelCase							:   Optional[Any]							=  {
    "configuration_autoformer": [
        "AUTOFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP",
        "AutoformerConfig",
    ],
}

try:
	if not is_torch_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	__UpperCAmelCase							:   str							=  [
	    "AUTOFORMER_PRETRAINED_MODEL_ARCHIVE_LIST",
	    "AutoformerForPrediction",
	    "AutoformerModel",
	    "AutoformerPreTrainedModel",
	]


if TYPE_CHECKING:
	from .configuration_autoformer import (
	    AUTOFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP,
	    AutoformerConfig,
	)

	try:
		if not is_torch_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .modeling_autoformer import (
		    AUTOFORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
		    AutoformerForPrediction,
		    AutoformerModel,
		    AutoformerPreTrainedModel,
		)

else:
	import sys

	__UpperCAmelCase							:   Optional[int]							=  _LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)









import pytest


__UpperCAmelCase							:   int							=  "__dummy_dataset1__"

__UpperCAmelCase							:   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 					lowercase_ (    )     -> Optional[Any]:





				'''simple docstring'''


				return DATASET_LOADING_SCRIPT_NAME





@pytest.fixture
def 					lowercase_ (    )     -> Optional[int]:





				'''simple docstring'''


				return DATASET_LOADING_SCRIPT_CODE





@pytest.fixture
def 					lowercase_ (    __snake_case     :							Optional[int]	,	__snake_case     :							List[Any]	,	__snake_case     :							Any      )     -> Dict:





				'''simple docstring'''


				snake_case__      :Optional[Any]         =   dataset_loading_script_name
				snake_case__      :Optional[Any]         =   tmp_path / "datasets" / script_name
				script_dir.mkdir(parents=__snake_case      )
				snake_case__      :List[Any]         =   script_dir / F'{script_name}.py'
				with open(__snake_case	,	"w"      ) as f:
								f.write(__snake_case      )
				return str(__snake_case      )