





'''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 				snake_case_      (		SCREAMING_SNAKE_CASE__       ):







  '''simple docstring'''



  return EnvironmentCommand()




def 				snake_case_      (		SCREAMING_SNAKE_CASE__       ):







  '''simple docstring'''



  return EnvironmentCommand(args.accelerate_config_file       )




class       __SCREAMING_SNAKE_CASE	(						__UpperCamelCase			):



     '''simple docstring'''






     @staticmethod
     def 	UpperCamelCase(					lowerCamelCase	):
       _snake_case     		=				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						,   lowerCamelCase						,   *lowerCamelCase	):
       _snake_case     		=				accelerate_config_file

     def 	UpperCamelCase(					self	):
       _snake_case     		=				"not installed"
       if is_safetensors_available():
         import safetensors

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

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

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

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

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

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

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

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

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

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

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

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









'''simple docstring'''



from __future__ import annotations

import numpy as np




def 				snake_case_      (		SCREAMING_SNAKE_CASE__       ):







  '''simple docstring'''



  return np.maximum(0					,	SCREAMING_SNAKE_CASE__       )


if __name__ == "__main__":
 print(np.array(relu([-1, 0, 5])))  # --> [0, 0, 5]


