





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							(    lowerCAmelCase_	)				->						Union[str, Any]:
    return EnvironmentCommand()


def 							__snake_case							(    lowerCAmelCase_	)				->						Tuple:
    return EnvironmentCommand(args.accelerate_config_file	)



class 					__snake_case	(  __SCREAMING_SNAKE_CASE    ):


    '''simple docstring'''







    @staticmethod
    def  lowercase_					(       A_     ):





        '''simple docstring'''

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



    def __init__(       self   ,				A_   ,				*A_     ):





        '''simple docstring'''

        SCREAMING_SNAKE_CASE__											=			accelerate_config_file



    def  lowercase_					(       self     ):





        '''simple docstring'''

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

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

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

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

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

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

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

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

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

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

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

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

        SCREAMING_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(A_     )     )

        return info




    @staticmethod
    def  lowercase_					(       A_     ):





        '''simple docstring'''

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






"""simple docstring"""

from typing import TYPE_CHECKING

from ..utils import _LazyModule


a							      =     {
    '''config''': [
        '''EXTERNAL_DATA_FORMAT_SIZE_LIMIT''',
        '''OnnxConfig''',
        '''OnnxConfigWithPast''',
        '''OnnxSeq2SeqConfigWithPast''',
        '''PatchingSpec''',
    ],
    '''convert''': ['''export''', '''validate_model_outputs'''],
    '''features''': ['''FeaturesManager'''],
    '''utils''': ['''ParameterFormat''', '''compute_serialized_parameters_size'''],
}


if TYPE_CHECKING:
       from .config import (
           EXTERNAL_DATA_FORMAT_SIZE_LIMIT,
           OnnxConfig,
           OnnxConfigWithPast,
           OnnxSeqaSeqConfigWithPast,
           PatchingSpec,
       )
       from .convert import export, validate_model_outputs
       from .features import FeaturesManager
       from .utils import ParameterFormat, compute_serialized_parameters_size

else:
       import sys

       a							      =     _LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)

