"""simple docstring"""







from typing import TYPE_CHECKING

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


lowerCamelCase      : Dict       ={
    'configuration_open_llama': ['OPEN_LLAMA_PRETRAINED_CONFIG_ARCHIVE_MAP', 'OpenLlamaConfig'],
}

try:
       if not is_sentencepiece_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       lowerCamelCase      : Any       =['LlamaTokenizer']

try:
       if not is_tokenizers_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       lowerCamelCase      : Any       =['LlamaTokenizerFast']

try:
       if not is_torch_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       lowerCamelCase      : Union[str, Any]       =[
           'OpenLlamaForCausalLM',
           'OpenLlamaModel',
           'OpenLlamaPreTrainedModel',
           'OpenLlamaForSequenceClassification',
       ]


if TYPE_CHECKING:
       from .configuration_open_llama import OPEN_LLAMA_PRETRAINED_CONFIG_ARCHIVE_MAP, OpenLlamaConfig

       try:
              if not is_sentencepiece_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from transformers import LlamaTokenizer

       try:
              if not is_tokenizers_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from transformers import LlamaTokenizerFast

       try:
              if not is_torch_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .modeling_open_llama import (
                  OpenLlamaForCausalLM,
                  OpenLlamaForSequenceClassification,
                  OpenLlamaModel,
                  OpenLlamaPreTrainedModel,
              )


else:
       import sys

       lowerCamelCase      : Any       =_LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)











"""simple docstring"""







from itertools import combinations, product





def 							SCREAMING_SNAKE_CASE							(   lowerCamelCase_			,  lowerCamelCase_			,  lowerCamelCase_			,  lowerCamelCase_):
					if xa == ya == 0 or xa == ya == 0:
										return False
					a__ 							=	xa * xa + ya * ya
					a__ 							=	xa * xa + ya * ya
					a__ 							=	(xa - xa) * (xa - xa) + (ya - ya) * (ya - ya)
					return (
					    a_square + b_square == c_square
					    or a_square + c_square == b_square
					    or b_square + c_square == a_square
					)





def 							SCREAMING_SNAKE_CASE							(   lowerCamelCase_ = 50):
					return sum(
					    1
					    for pta, pta in combinations(product(range(limit + 1)			,  repeat=2)			,  2)
					    if is_right(*lowerCamelCase_			,  *lowerCamelCase_))


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


