





"""simple docstring"""


from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available


__magic_name__       :					Optional[Any]						=			{
    """configuration_rag""": ["""RagConfig"""],
    """retrieval_rag""": ["""RagRetriever"""],
    """tokenization_rag""": ["""RagTokenizer"""],
}

try:
		if not is_torch_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		__magic_name__       :					str						=			[
		    """RagModel""",
		    """RagPreTrainedModel""",
		    """RagSequenceForGeneration""",
		    """RagTokenForGeneration""",
		]

try:
		if not is_tf_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		__magic_name__       :					List[Any]						=			[
		    """TFRagModel""",
		    """TFRagPreTrainedModel""",
		    """TFRagSequenceForGeneration""",
		    """TFRagTokenForGeneration""",
		]


if TYPE_CHECKING:
		from .configuration_rag import RagConfig
		from .retrieval_rag import RagRetriever
		from .tokenization_rag import RagTokenizer

		try:
				if not is_torch_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .modeling_rag import RagModel, RagPreTrainedModel, RagSequenceForGeneration, RagTokenForGeneration

		try:
				if not is_tf_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .modeling_tf_rag import (
				    TFRagModel,
				    TFRagPreTrainedModel,
				    TFRagSequenceForGeneration,
				    TFRagTokenForGeneration,
				)

else:
		import sys

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





import os

# Precomputes a list of the 100 first triangular numbers
A		: List[Any]								=     [int(0.5 * n * (n + 1)) for n in range(1, 101)]




def 	UpperCamelCase__  (     )  ->     str:
						_lowercase					       =					os.path.dirname(os.path.realpath(SCREAMING_SNAKE_CASE_       )       )
						_lowercase					       =					os.path.join(SCREAMING_SNAKE_CASE_		,   """words.txt"""       )

						_lowercase					       =					""""""
						with open(SCREAMING_SNAKE_CASE_       ) as f:
												_lowercase					       =					f.readline()

						_lowercase					       =					[word.strip("""\""""       ) for word in words.strip("""\r\n"""       ).split(""","""       )]
						_lowercase					       =					[
						    word
						    for word in [sum(ord(SCREAMING_SNAKE_CASE_       ) - 64 for x in word       ) for word in words]
						    if word in TRIANGULAR_NUMBERS
						]
						return len(SCREAMING_SNAKE_CASE_       )


if __name__ == "__main__":
		print(solution())