



from typing import TYPE_CHECKING

from ...file_utils import _LazyModule, is_tokenizers_available, is_torch_available
from ...utils import OptionalDependencyNotAvailable


__snake_case						:List[str]						=					{'''configuration_gpt_neox''': ['''GPT_NEOX_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''GPTNeoXConfig''']}

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

try:
 if not is_torch_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 __snake_case						:Optional[Any]						=					[
     '''GPT_NEOX_PRETRAINED_MODEL_ARCHIVE_LIST''',
     '''GPTNeoXForCausalLM''',
     '''GPTNeoXForQuestionAnswering''',
     '''GPTNeoXForSequenceClassification''',
     '''GPTNeoXForTokenClassification''',
     '''GPTNeoXLayer''',
     '''GPTNeoXModel''',
     '''GPTNeoXPreTrainedModel''',
 ]


if TYPE_CHECKING:
 from .configuration_gpt_neox import GPT_NEOX_PRETRAINED_CONFIG_ARCHIVE_MAP, GPTNeoXConfig

 try:
  if not is_tokenizers_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .tokenization_gpt_neox_fast import GPTNeoXTokenizerFast

 try:
  if not is_torch_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .modeling_gpt_neox import (
      GPT_NEOX_PRETRAINED_MODEL_ARCHIVE_LIST,
      GPTNeoXForCausalLM,
      GPTNeoXForQuestionAnswering,
      GPTNeoXForSequenceClassification,
      GPTNeoXForTokenClassification,
      GPTNeoXLayer,
      GPTNeoXModel,
      GPTNeoXPreTrainedModel,
  )


else:
 import sys

 __snake_case						:Optional[int]						=					_LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)










def 					__snake_case     (      _UpperCAmelCase = 1000000    ):
    __a							=    limit + 1
    __a							=    [0] * limit
    for first_term in range(1       ,			_UpperCAmelCase    ):
        for n in range(_UpperCAmelCase       ,			_UpperCAmelCase       ,			_UpperCAmelCase    ):
            __a							=    first_term + n / first_term
            if common_difference % 4:  # d must be divisble by 4
                continue
            else:
                common_difference /= 4
                if (
                    first_term > common_difference
                    and first_term < 4 * common_difference
                ):  # since x,y,z are positive integers
                    frequency[n] += 1  # so z>0 and a>d ,also 4d<a

    __a							=    sum(1 for x in frequency[1:limit] if x == 10    )

    return count


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





