


"""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 					lowerCamelCase_   (	_a	):




		"""simple docstring"""






		return EnvironmentCommand()






def 					lowerCamelCase_   (	_a	):




		"""simple docstring"""






		return EnvironmentCommand(args.accelerate_config_file	)





class  _a							(    A__):




	@staticmethod
	def 							UpperCAmelCase__( _SCREAMING_SNAKE_CASE						:		List[Any]		)->	str:
			lowerCAmelCase__       :      int   					= 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						:		Tuple		, _SCREAMING_SNAKE_CASE						:		Union[str, Any]		, *_SCREAMING_SNAKE_CASE						:		Any		)->	Optional[int]:
			lowerCAmelCase__       :      List[str]   					= accelerate_config_file




	def 							UpperCAmelCase__( self						:		Dict		)->	Dict:
			lowerCAmelCase__       :      Optional[int]   					= '''not installed'''
			if is_safetensors_available():
					import safetensors

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

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

			lowerCAmelCase__       :      Dict   					= '''not installed'''
			lowerCAmelCase__       :      List[Any]   					= '''not found'''
			if is_accelerate_available():
					import accelerate
					from accelerate.commands.config import default_config_file, load_config_from_file

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

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

			lowerCAmelCase__       :      Any   					= '''not installed'''
			lowerCAmelCase__       :      Optional[int]   					= '''NA'''
			if is_torch_available():
					import torch

					lowerCAmelCase__       :      Optional[Any]   					= torch.__version__
					lowerCAmelCase__       :      Any   					= torch.cuda.is_available()

			lowerCAmelCase__       :      Optional[Any]   					= '''not installed'''
			lowerCAmelCase__       :      List[str]   					= '''NA'''
			if is_tf_available():
					import tensorflow as tf

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

			lowerCAmelCase__       :      Optional[Any]   					= '''not installed'''
			lowerCAmelCase__       :      Any   					= '''not installed'''
			lowerCAmelCase__       :      str   					= '''not installed'''
			lowerCAmelCase__       :      List[Any]   					= '''NA'''
			if is_flax_available():
					import flax
					import jax
					import jaxlib

					lowerCAmelCase__       :      Union[str, Any]   					= flax.__version__
					lowerCAmelCase__       :      int   					= jax.__version__
					lowerCAmelCase__       :      Union[str, Any]   					= jaxlib.__version__
					lowerCAmelCase__       :      int   					= jax.lib.xla_bridge.get_backend().platform

			lowerCAmelCase__       :      Optional[int]   					= {
			    '''`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__( _SCREAMING_SNAKE_CASE						:		List[Any]		)->	Any:
			return "\n".join([F'- {prop}: {val}' for prop, val in d.items()]		) + "\n"








from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_flax_available,
    is_torch_available,
    is_vision_available,
)


lowerCamelCase						=		{'''configuration_beit''': ['''BEIT_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''BeitConfig''', '''BeitOnnxConfig''']}

try:
		if not is_vision_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		lowerCamelCase						=		['''BeitFeatureExtractor''']
		lowerCamelCase						=		['''BeitImageProcessor''']

try:
		if not is_torch_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		lowerCamelCase						=		[
		    '''BEIT_PRETRAINED_MODEL_ARCHIVE_LIST''',
		    '''BeitForImageClassification''',
		    '''BeitForMaskedImageModeling''',
		    '''BeitForSemanticSegmentation''',
		    '''BeitModel''',
		    '''BeitPreTrainedModel''',
		]


try:
		if not is_flax_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		lowerCamelCase						=		[
		    '''FlaxBeitForImageClassification''',
		    '''FlaxBeitForMaskedImageModeling''',
		    '''FlaxBeitModel''',
		    '''FlaxBeitPreTrainedModel''',
		]

if TYPE_CHECKING:
		from .configuration_beit import BEIT_PRETRAINED_CONFIG_ARCHIVE_MAP, BeitConfig, BeitOnnxConfig

		try:
				if not is_vision_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .feature_extraction_beit import BeitFeatureExtractor
				from .image_processing_beit import BeitImageProcessor

		try:
				if not is_torch_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .modeling_beit import (
				    BEIT_PRETRAINED_MODEL_ARCHIVE_LIST,
				    BeitForImageClassification,
				    BeitForMaskedImageModeling,
				    BeitForSemanticSegmentation,
				    BeitModel,
				    BeitPreTrainedModel,
				)

		try:
				if not is_flax_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .modeling_flax_beit import (
				    FlaxBeitForImageClassification,
				    FlaxBeitForMaskedImageModeling,
				    FlaxBeitModel,
				    FlaxBeitPreTrainedModel,
				)


else:
		import sys

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




