
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 			lowerCamelCase_ (				lowerCamelCase__    ):
				return EnvironmentCommand()





def 			lowerCamelCase_ (				lowerCamelCase__    ):
				return EnvironmentCommand(args.accelerate_config_file    )





class     _SCREAMING_SNAKE_CASE     (      snake_case_						):



	@staticmethod
	def     SCREAMING_SNAKE_CASE_(    lowercase )				->       str:
					lowerCamelCase_						=			parser.add_parser("env" )
					download_parser.set_defaults(func=lowercase )
					download_parser.add_argument(
					    "--accelerate-config_file"						,  default=lowercase						,  help="The accelerate config file to use for the default values in the launching script."						,  )
					download_parser.set_defaults(func=lowercase )



	def __init__(    self						,  lowercase						,  *lowercase )				->       None:
					lowerCamelCase_						=			accelerate_config_file



	def     SCREAMING_SNAKE_CASE_(    self )				->       Optional[int]:
					lowerCamelCase_						=			"not installed"
					if is_safetensors_available():
									import safetensors

									lowerCamelCase_						=			safetensors.__version__
					elif importlib.util.find_spec("safetensors" ) is not None:
									import safetensors

									lowerCamelCase_						=			f'{safetensors.__version__} but is ignored because of PyTorch version too old.'

					lowerCamelCase_						=			"not installed"
					lowerCamelCase_						=			lowerCamelCase_						=			"not found"
					if is_accelerate_available():
									import accelerate
									from accelerate.commands.config import default_config_file, load_config_from_file

									lowerCamelCase_						=			accelerate.__version__
									# Get the default from the config file.
									if self._accelerate_config_file is not None or os.path.isfile(lowercase ):
													lowerCamelCase_						=			load_config_from_file(self._accelerate_config_file ).to_dict()

									lowerCamelCase_						=			(
									    "\n".join([f'\t- {prop}: {val}' for prop, val in accelerate_config.items()] )
									    if isinstance(lowercase						,  lowercase )
									    else f'\t{accelerate_config}'
									)

					lowerCamelCase_						=			"not installed"
					lowerCamelCase_						=			"NA"
					if is_torch_available():
									import torch

									lowerCamelCase_						=			torch.__version__
									lowerCamelCase_						=			torch.cuda.is_available()

					lowerCamelCase_						=			"not installed"
					lowerCamelCase_						=			"NA"
					if is_tf_available():
									import tensorflow as tf

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

					lowerCamelCase_						=			"not installed"
					lowerCamelCase_						=			"not installed"
					lowerCamelCase_						=			"not installed"
					lowerCamelCase_						=			"NA"
					if is_flax_available():
									import flax
									import jax
									import jaxlib

									lowerCamelCase_						=			flax.__version__
									lowerCamelCase_						=			jax.__version__
									lowerCamelCase_						=			jaxlib.__version__
									lowerCamelCase_						=			jax.lib.xla_bridge.get_backend().platform

					lowerCamelCase_						=			{
					    "`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(lowercase ) )

					return info



	@staticmethod
	def     SCREAMING_SNAKE_CASE_(    lowercase )				->       List[Any]:
					return "\n".join([f'- {prop}: {val}' for prop, val in d.items()] ) + "\n"




def 			lowerCamelCase_ (				lowerCamelCase__	, lowerCamelCase__    ):
				lowerCamelCase_						=			[0 for i in range(r + 1    )]
				# nc0 = 1
				lowerCamelCase_						=			1
				for i in range(1	, n + 1    ):
								# to compute current row from previous row.
								lowerCamelCase_						=			min(lowerCamelCase__	, lowerCamelCase__    )
								while j > 0:
												c[j] += c[j - 1]
												j -= 1
				return c[r]





print(binomial_coefficient(n=1_0, r=5))


