
'''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 A (__lowerCamelCase :Optional[int]						):
						return EnvironmentCommand()


def A (__lowerCamelCase :Dict						):
						return EnvironmentCommand(args.accelerate_config_file						)





class     UpperCAmelCase_	(						_SCREAMING_SNAKE_CASE					):






						'''simple docstring'''






						@staticmethod
						def    _lowercase      (   _lowercase ):

												"""simple docstring"""



												_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 ):

												"""simple docstring"""



												_lowerCAmelCase    		=					accelerate_config_file




						def    _lowercase      (   self ):

												"""simple docstring"""



												_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    _lowercase      (   _lowercase ):

												"""simple docstring"""



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


'''simple docstring'''



import functools


def A (__lowerCamelCase :list[int]					,      __lowerCamelCase :list[int]						):

						# Validation
						if not isinstance(__lowerCamelCase					,      __lowerCamelCase						) or not all(isinstance(__lowerCamelCase					,      __lowerCamelCase						) for day in days						):
												raise ValueError("""The parameter days should be a list of integers"""						)

						if len(__lowerCamelCase						) != 3 or not all(isinstance(__lowerCamelCase					,      __lowerCamelCase						) for cost in costs						):
												raise ValueError("""The parameter costs should be a list of three integers"""						)

						if len(__lowerCamelCase						) == 0:
												return 0

						if min(__lowerCamelCase						) <= 0:
												raise ValueError("""All days elements should be greater than 0"""						)

						if max(__lowerCamelCase						) >= 366:
												raise ValueError("""All days elements should be less than 366"""						)

						_lowerCAmelCase    		=					set(__lowerCamelCase						)

						@functools.cache
						def dynamic_programming(__lowerCamelCase :int						) -> int:
												if index > 365:
																		return 0

												if index not in days_set:
																		return dynamic_programming(index + 1						)

												return min(
												    costs[0] + dynamic_programming(index + 1						)					,      costs[1] + dynamic_programming(index + 7						)					,      costs[2] + dynamic_programming(index + 30						)					,      )

						return dynamic_programming(1						)


if __name__ == "__main__":
						import doctest

						doctest.testmod()
