'''simple docstring'''






import importlib.util
import os
import platform
from argparse import ArgumentParser

import huggingface_hub

from .. import __version__ as version
from ..utils import (
    is_accelerate_available,
    is_flax_available,
    is_safetensors_available,
    is_tf_available,
    is_torch_available,
)
from . import BaseTransformersCLICommand






def   __UpperCAmelCase     (    a_:			List[str]				):
   return EnvironmentCommand()






def   __UpperCAmelCase     (    a_:			List[Any]				):
   return EnvironmentCommand(args.accelerate_config_file				)






class        A__				(			SCREAMING_SNAKE_CASE__  ):





   """simple docstring"""





   @staticmethod
   def      _lowerCAmelCase						(					lowerCAmelCase__	:						Tuple     )			->       Any:







      """simple docstring"""




      _UpperCAmelCase				:      Any				=  parser.add_parser("env"     )
      download_parser.set_defaults(func=__lowerCamelCase     )
      download_parser.add_argument(
          "--accelerate-config_file"		,	default=__lowerCamelCase		,	help="The accelerate config file to use for the default values in the launching script."		,	)
      download_parser.set_defaults(func=__lowerCamelCase     )




   def __init__(					self	:						Tuple		,	lowerCAmelCase__	:						Optional[int]		,	*lowerCAmelCase__	:						str     )			->       Union[str, Any]:







      """simple docstring"""




      _UpperCAmelCase				:      List[str]				=  accelerate_config_file




   def      _lowerCAmelCase						(					self	:						str     )			->       Any:







      """simple docstring"""




      _UpperCAmelCase				:      Dict				=  '''not installed'''
      if is_safetensors_available():
         import safetensors

         _UpperCAmelCase				:      Union[str, Any]				=  safetensors.__version__
      elif importlib.util.find_spec("safetensors"     ) is not None:
         import safetensors

         _UpperCAmelCase				:      Dict				=  F"""{safetensors.__version__} but is ignored because of PyTorch version too old."""

      _UpperCAmelCase				:      List[str]				=  '''not installed'''
      _UpperCAmelCase				:      Any				=  '''not found'''
      if is_accelerate_available():
         import accelerate
         from accelerate.commands.config import default_config_file, load_config_from_file

         _UpperCAmelCase				:      Dict				=  accelerate.__version__
         # Get the default from the config file.
         if self._accelerate_config_file is not None or os.path.isfile(__lowerCamelCase     ):
            _UpperCAmelCase				:      Optional[int]				=  load_config_from_file(self._accelerate_config_file     ).to_dict()

         _UpperCAmelCase				:      int				=  (
             '''\n'''.join([F"""\t- {prop}: {val}""" for prop, val in accelerate_config.items()]     )
             if isinstance(__lowerCamelCase		,	__lowerCamelCase     )
             else F"""\t{accelerate_config}"""
         )

      _UpperCAmelCase				:      Optional[int]				=  '''not installed'''
      _UpperCAmelCase				:      Optional[int]				=  '''NA'''
      if is_torch_available():
         import torch

         _UpperCAmelCase				:      int				=  torch.__version__
         _UpperCAmelCase				:      Tuple				=  torch.cuda.is_available()

      _UpperCAmelCase				:      Tuple				=  '''not installed'''
      _UpperCAmelCase				:      Tuple				=  '''NA'''
      if is_tf_available():
         import tensorflow as tf

         _UpperCAmelCase				:      str				=  tf.__version__
         try:
            # deprecated in v2.1
            _UpperCAmelCase				:      Optional[int]				=  tf.test.is_gpu_available()
         except AttributeError:
            # returns list of devices, convert to bool
            _UpperCAmelCase				:      str				=  bool(tf.config.list_physical_devices("GPU"     )     )

      _UpperCAmelCase				:      int				=  '''not installed'''
      _UpperCAmelCase				:      List[Any]				=  '''not installed'''
      _UpperCAmelCase				:      List[Any]				=  '''not installed'''
      _UpperCAmelCase				:      Dict				=  '''NA'''
      if is_flax_available():
         import flax
         import jax
         import jaxlib

         _UpperCAmelCase				:      Dict				=  flax.__version__
         _UpperCAmelCase				:      str				=  jax.__version__
         _UpperCAmelCase				:      Tuple				=  jaxlib.__version__
         _UpperCAmelCase				:      List[Any]				=  jax.lib.xla_bridge.get_backend().platform

      _UpperCAmelCase				:      List[str]				=  {
          '''`transformers` version''': version,
          '''Platform''': platform.platform(),
          '''Python version''': platform.python_version(),
          '''Huggingface_hub version''': huggingface_hub.__version__,
          '''Safetensors version''': F"""{safetensors_version}""",
          '''Accelerate version''': F"""{accelerate_version}""",
          '''Accelerate config''': F"""{accelerate_config_str}""",
          '''PyTorch version (GPU?)''': F"""{pt_version} ({pt_cuda_available})""",
          '''Tensorflow version (GPU?)''': F"""{tf_version} ({tf_cuda_available})""",
          '''Flax version (CPU?/GPU?/TPU?)''': F"""{flax_version} ({jax_backend})""",
          '''Jax version''': F"""{jax_version}""",
          '''JaxLib version''': F"""{jaxlib_version}""",
          '''Using GPU in script?''': '''<fill in>''',
          '''Using distributed or parallel set-up in script?''': '''<fill in>''',
      }

      print("\nCopy-and-paste the text below in your GitHub issue and FILL OUT the two last points.\n"     )
      print(self.format_dict(__lowerCamelCase     )     )

      return info




   @staticmethod
   def      _lowerCAmelCase						(					lowerCAmelCase__	:						Dict     )			->       List[str]:







      """simple docstring"""




      return "\n".join([F"""- {prop}: {val}""" for prop, val in d.items()]     ) + "\n"






"""simple docstring"""



from collections import defaultdict
from math import gcd







def 						__lowercase	(  snake_case_    :    int = 1500000		)  ->int:



    '''simple docstring'''







    __A       :		defaultdict							=	defaultdict(snake_case_		)
    __A       :		Any							=	2
    while 2 * euclid_m * (euclid_m + 1) <= limit:
        for euclid_n in range((euclid_m % 2) + 1							,snake_case_							,2		):
            if gcd(snake_case_							,snake_case_		) > 1:
                continue
            __A       :		List[Any]							=	2 * euclid_m * (euclid_m + euclid_n)
            for perimeter in range(snake_case_							,limit + 1							,snake_case_		):
                frequencies[perimeter] += 1
        euclid_m += 1
    return sum(1 for frequency in frequencies.values() if frequency == 1		)


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




