






'''simple docstring'''




import math

def 					__lowercase						(			__lowercase = 100       )       ->						int:

      '''simple docstring'''


      _A			     =	sum(i * i for i in range(1   ,  n + 1       )       )
      _A			     =	int(math.pow(sum(range(1   ,  n + 1       )       )   ,  2       )       )
      return square_of_sum - sum_of_squares


if __name__ == "__main__":
    print(F"""{solution() = }""")









"""simple docstring"""


from typing import TYPE_CHECKING

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


A     :   Tuple			    =			{
    "configuration_blenderbot": [
        "BLENDERBOT_PRETRAINED_CONFIG_ARCHIVE_MAP",
        "BlenderbotConfig",
        "BlenderbotOnnxConfig",
    ],
    "tokenization_blenderbot": ["BlenderbotTokenizer"],
}

try:
	if not is_tokenizers_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	A     :   Dict			    =			["BlenderbotTokenizerFast"]

try:
	if not is_torch_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	A     :   str			    =			[
	    "BLENDERBOT_PRETRAINED_MODEL_ARCHIVE_LIST",
	    "BlenderbotForCausalLM",
	    "BlenderbotForConditionalGeneration",
	    "BlenderbotModel",
	    "BlenderbotPreTrainedModel",
	]


try:
	if not is_tf_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	A     :   List[str]			    =			[
	    "TFBlenderbotForConditionalGeneration",
	    "TFBlenderbotModel",
	    "TFBlenderbotPreTrainedModel",
	]


try:
	if not is_flax_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	A     :   List[str]			    =			[
	    "FlaxBlenderbotForConditionalGeneration",
	    "FlaxBlenderbotModel",
	    "FlaxBlenderbotPreTrainedModel",
	]


if TYPE_CHECKING:
	from .configuration_blenderbot import (
	    BLENDERBOT_PRETRAINED_CONFIG_ARCHIVE_MAP,
	    BlenderbotConfig,
	    BlenderbotOnnxConfig,
	)
	from .tokenization_blenderbot import BlenderbotTokenizer

	try:
		if not is_tokenizers_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .tokenization_blenderbot_fast import BlenderbotTokenizerFast

	try:
		if not is_torch_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .modeling_blenderbot import (
		    BLENDERBOT_PRETRAINED_MODEL_ARCHIVE_LIST,
		    BlenderbotForCausalLM,
		    BlenderbotForConditionalGeneration,
		    BlenderbotModel,
		    BlenderbotPreTrainedModel,
		)

	try:
		if not is_tf_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .modeling_tf_blenderbot import (
		    TFBlenderbotForConditionalGeneration,
		    TFBlenderbotModel,
		    TFBlenderbotPreTrainedModel,
		)

	try:
		if not is_flax_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .modeling_flax_blenderbot import (
		    FlaxBlenderbotForConditionalGeneration,
		    FlaxBlenderbotModel,
		    FlaxBlenderbotPreTrainedModel,
		)

else:
	import sys

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




