from __future__ import annotations

import collections
import pprint
from pathlib import Path




def     UpperCamelCase						(	__lowercase						:			str     ):
		'''simple docstring'''




		return "".join(sorted(__lowercase     )     )




def     UpperCamelCase						(	__lowercase						:			str     ):
		'''simple docstring'''




		return word_by_signature[signature(__lowercase     )]


_UpperCAmelCase            =		Path(__file__).parent.joinpath("""words.txt""").read_text(encoding="""utf-8""")
_UpperCAmelCase            =		sorted({word.strip().lower() for word in data.splitlines()})

_UpperCAmelCase            =		collections.defaultdict(list)
for word in word_list:
	word_by_signature[signature(word)].append(word)

if __name__ == "__main__":
	_UpperCAmelCase            =		{word: anagram(word) for word in word_list if len(anagram(word)) > 1}

	with open("""anagrams.txt""", """w""") as file:
		file.write("""all_anagrams = \n """)
		file.write(pprint.pformat(all_anagrams))







from typing import TYPE_CHECKING

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


_UpperCAmelCase            =		{
    """configuration_autoformer""": [
        """AUTOFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP""",
        """AutoformerConfig""",
    ],
}

try:
	if not is_torch_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	_UpperCAmelCase            =		[
	    """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            =		_LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)






