





"""simple docstring"""




from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_flax_available,
    is_sentencepiece_available,
    is_tf_available,
    is_tokenizers_available,
    is_torch_available,
)


_a									=				{"configuration_t5": ["T5_PRETRAINED_CONFIG_ARCHIVE_MAP", "T5Config", "T5OnnxConfig"]}

try:
			if not is_sentencepiece_available():
						raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
			pass
else:
			_a									=				["T5Tokenizer"]

try:
			if not is_tokenizers_available():
						raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
			pass
else:
			_a									=				["T5TokenizerFast"]

try:
			if not is_torch_available():
						raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
			pass
else:
			_a									=				[
			    "T5_PRETRAINED_MODEL_ARCHIVE_LIST",
			    "T5EncoderModel",
			    "T5ForConditionalGeneration",
			    "T5Model",
			    "T5PreTrainedModel",
			    "load_tf_weights_in_t5",
			    "T5ForQuestionAnswering",
			]

try:
			if not is_tf_available():
						raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
			pass
else:
			_a									=				[
			    "TF_T5_PRETRAINED_MODEL_ARCHIVE_LIST",
			    "TFT5EncoderModel",
			    "TFT5ForConditionalGeneration",
			    "TFT5Model",
			    "TFT5PreTrainedModel",
			]

try:
			if not is_flax_available():
						raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
			pass
else:
			_a									=				[
			    "FlaxT5EncoderModel",
			    "FlaxT5ForConditionalGeneration",
			    "FlaxT5Model",
			    "FlaxT5PreTrainedModel",
			]


if TYPE_CHECKING:
			from .configuration_ta import T5_PRETRAINED_CONFIG_ARCHIVE_MAP, TaConfig, TaOnnxConfig

			try:
						if not is_sentencepiece_available():
									raise OptionalDependencyNotAvailable()
			except OptionalDependencyNotAvailable:
						pass
			else:
						from .tokenization_ta import TaTokenizer

			try:
						if not is_tokenizers_available():
									raise OptionalDependencyNotAvailable()
			except OptionalDependencyNotAvailable:
						pass
			else:
						from .tokenization_ta_fast import TaTokenizerFast

			try:
						if not is_torch_available():
									raise OptionalDependencyNotAvailable()
			except OptionalDependencyNotAvailable:
						pass
			else:
						from .modeling_ta import (
						    T5_PRETRAINED_MODEL_ARCHIVE_LIST,
						    TaEncoderModel,
						    TaForConditionalGeneration,
						    TaForQuestionAnswering,
						    TaModel,
						    TaPreTrainedModel,
						    load_tf_weights_in_ta,
						)

			try:
						if not is_tf_available():
									raise OptionalDependencyNotAvailable()
			except OptionalDependencyNotAvailable:
						pass
			else:
						from .modeling_tf_ta import (
						    TF_T5_PRETRAINED_MODEL_ARCHIVE_LIST,
						    TFTaEncoderModel,
						    TFTaForConditionalGeneration,
						    TFTaModel,
						    TFTaPreTrainedModel,
						)

			try:
						if not is_flax_available():
									raise OptionalDependencyNotAvailable()
			except OptionalDependencyNotAvailable:
						pass
			else:
						from .modeling_flax_ta import (
						    FlaxTaEncoderModel,
						    FlaxTaForConditionalGeneration,
						    FlaxTaModel,
						    FlaxTaPreTrainedModel,
						)


else:
			import sys

			_a									=				_LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)










import os





def lowerCAmelCase__()    ->				Optional[Any]:







	'''simple docstring'''







	lowerCamelCase__        =		os.path.dirname(os.path.realpath(__snake_case							)							)
	lowerCamelCase__        =		os.path.join(__snake_case	,'''triangle.txt'''							)

	with open(__snake_case							) as f:
		lowerCamelCase__        =		f.readlines()

	lowerCamelCase__        =		[[int(__snake_case							) for y in x.rstrip('''\r\n'''							).split(''' '''							)] for x in triangle]

	for i in range(1	,len(__snake_case							)							):
		for j in range(len(a[i]							)							):
			lowerCamelCase__        =		a[i - 1][j] if j != len(a[i - 1]							) else 0
			lowerCamelCase__        =		a[i - 1][j - 1] if j > 0 else 0
			a[i][j] += max(__snake_case	,__snake_case							)
	return max(a[-1]							)


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



