


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 		lowercase_  (     _UpperCamelCase  ):


			'''simple docstring'''







			return EnvironmentCommand()


def 		lowercase_  (     _UpperCamelCase  ):


			'''simple docstring'''







			return EnvironmentCommand(args.accelerate_config_file  )





class 	lowerCamelCase_       (				lowerCAmelCase__				):



					'''simple docstring'''







					@staticmethod
					def A      (				snake_case_						)   ->			Dict:







								'''simple docstring'''

								__lowercase 					=   parser.add_parser('''env'''						)
								download_parser.set_defaults(func=snake_case_						)
								download_parser.add_argument(
								    '''--accelerate-config_file''' ,       default=snake_case_ ,       help='''The accelerate config file to use for the default values in the launching script.''' ,       )
								download_parser.set_defaults(func=snake_case_						)






					def __init__(				self ,       snake_case_ ,       *snake_case_						)   ->			None:







								'''simple docstring'''

								__lowercase 					=   accelerate_config_file






					def A      (				self						)   ->			str:







								'''simple docstring'''

								__lowercase 					=   '''not installed'''
								if is_safetensors_available():
											import safetensors

											__lowercase 					=   safetensors.__version__
								elif importlib.util.find_spec('''safetensors'''						) is not None:
											import safetensors

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

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

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

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

								__lowercase 					=   '''not installed'''
								__lowercase 					=   '''NA'''
								if is_torch_available():
											import torch

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

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

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

								__lowercase 					=   '''not installed'''
								__lowercase 					=   '''not installed'''
								__lowercase 					=   '''not installed'''
								__lowercase 					=   '''NA'''
								if is_flax_available():
											import flax
											import jax
											import jaxlib

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

								__lowercase 					=   {
								    '''`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(snake_case_						)						)

								return info






					@staticmethod
					def A      (				snake_case_						)   ->			Tuple:







								'''simple docstring'''

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






import unittest

from knapsack import knapsack as k
class 	lowerCamelCase_       (				unittest.TestCase				):



					'''simple docstring'''







					def A      (				self						)   ->			Optional[Any]:







								'''simple docstring'''

								__lowercase 					=   0
								__lowercase 					=   [0]
								__lowercase 					=   [0]
								__lowercase 					=   len(snake_case_						)
								self.assertEqual(k.knapsack(snake_case_ ,       snake_case_ ,       snake_case_ ,       snake_case_						) ,       0						)

								__lowercase 					=   [6_0]
								__lowercase 					=   [1_0]
								__lowercase 					=   len(snake_case_						)
								self.assertEqual(k.knapsack(snake_case_ ,       snake_case_ ,       snake_case_ ,       snake_case_						) ,       0						)






					def A      (				self						)   ->			Tuple:







								'''simple docstring'''

								__lowercase 					=   3
								__lowercase 					=   [1, 2, 3]
								__lowercase 					=   [3, 2, 1]
								__lowercase 					=   len(snake_case_						)
								self.assertEqual(k.knapsack(snake_case_ ,       snake_case_ ,       snake_case_ ,       snake_case_						) ,       5						)






					def A      (				self						)   ->			str:







								'''simple docstring'''

								__lowercase 					=   5_0
								__lowercase 					=   [6_0, 1_0_0, 1_2_0]
								__lowercase 					=   [1_0, 2_0, 3_0]
								__lowercase 					=   len(snake_case_						)
								self.assertEqual(k.knapsack(snake_case_ ,       snake_case_ ,       snake_case_ ,       snake_case_						) ,       2_2_0						)


if __name__ == "__main__":
	unittest.main()


