






"""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       __UpperCamelCase						(		snake_case__       ):
	return EnvironmentCommand()






def       __UpperCamelCase						(		snake_case__       ):
	return EnvironmentCommand(args.accelerate_config_file       )




class   SCREAMING_SNAKE_CASE	(					_SCREAMING_SNAKE_CASE    ):





	"""simple docstring"""




	@staticmethod
	def  lowerCamelCase(lowerCAmelCase_				):
		A_		:    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  ,  lowerCAmelCase_  ,  *lowerCAmelCase_				):
		A_		:    Optional[Any]						     = accelerate_config_file





	def  lowerCamelCase(self				):
		A_		:    Optional[int]						     = """not installed"""
		if is_safetensors_available():
			import safetensors

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

			A_		:    Tuple						     = f"""{safetensors.__version__} but is ignored because of PyTorch version too old."""

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

			A_		:    Optional[Any]						     = accelerate.__version__
			# Get the default from the config file.
			if self._accelerate_config_file is not None or os.path.isfile(lowerCAmelCase_				):
				A_		:    List[str]						     = load_config_from_file(self._accelerate_config_file				).to_dict()

			A_		:    List[str]						     = (
			    """\n""".join([f"""\t- {prop}: {val}""" for prop, val in accelerate_config.items()]				)
			    if isinstance(lowerCAmelCase_  ,  lowerCAmelCase_				)
			    else f"""\t{accelerate_config}"""
			)

		A_		:    Tuple						     = """not installed"""
		A_		:    List[Any]						     = """NA"""
		if is_torch_available():
			import torch

			A_		:    Union[str, Any]						     = torch.__version__
			A_		:    Union[str, Any]						     = torch.cuda.is_available()

		A_		:    List[Any]						     = """not installed"""
		A_		:    Optional[Any]						     = """NA"""
		if is_tf_available():
			import tensorflow as tf

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

		A_		:    Optional[int]						     = """not installed"""
		A_		:    Any						     = """not installed"""
		A_		:    Any						     = """not installed"""
		A_		:    Dict						     = """NA"""
		if is_flax_available():
			import flax
			import jax
			import jaxlib

			A_		:    Optional[int]						     = flax.__version__
			A_		:    List[Any]						     = jax.__version__
			A_		:    int						     = jaxlib.__version__
			A_		:    Dict						     = jax.lib.xla_bridge.get_backend().platform

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









"""simple docstring"""
_lowerCAmelCase       =				[
    "Audio",
    "Array2D",
    "Array3D",
    "Array4D",
    "Array5D",
    "ClassLabel",
    "Features",
    "Sequence",
    "Value",
    "Image",
    "Translation",
    "TranslationVariableLanguages",
]
from .audio import Audio
from .features import ArrayaD, ArrayaD, ArrayaD, ArrayaD, ClassLabel, Features, Sequence, Value
from .image import Image
from .translation import Translation, TranslationVariableLanguages

