




"""simple docstring"""
from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available


_SCREAMING_SNAKE_CASE						 =     {"""configuration_hubert""": ["""HUBERT_PRETRAINED_CONFIG_ARCHIVE_MAP""", """HubertConfig"""]}

try:
    if not is_torch_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    _SCREAMING_SNAKE_CASE						 =     [
        """HUBERT_PRETRAINED_MODEL_ARCHIVE_LIST""",
        """HubertForCTC""",
        """HubertForSequenceClassification""",
        """HubertModel""",
        """HubertPreTrainedModel""",
    ]


try:
    if not is_tf_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    _SCREAMING_SNAKE_CASE						 =     [
        """TF_HUBERT_PRETRAINED_MODEL_ARCHIVE_LIST""",
        """TFHubertForCTC""",
        """TFHubertModel""",
        """TFHubertPreTrainedModel""",
    ]

if TYPE_CHECKING:
    from .configuration_hubert import HUBERT_PRETRAINED_CONFIG_ARCHIVE_MAP, HubertConfig

    try:
        if not is_torch_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .modeling_hubert import (
            HUBERT_PRETRAINED_MODEL_ARCHIVE_LIST,
            HubertForCTC,
            HubertForSequenceClassification,
            HubertModel,
            HubertPreTrainedModel,
        )

    try:
        if not is_tf_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .modeling_tf_hubert import (
            TF_HUBERT_PRETRAINED_MODEL_ARCHIVE_LIST,
            TFHubertForCTC,
            TFHubertModel,
            TFHubertPreTrainedModel,
        )


else:
    import sys

    _SCREAMING_SNAKE_CASE						 =     _LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)









"""simple docstring"""
import platform
from argparse import ArgumentParser

import huggingface_hub
import pandas
import pyarrow

from datasets import __version__ as version
from datasets.commands import BaseDatasetsCLICommand






def 				__lowerCAmelCase					(					__lowerCAmelCase			:		Union[str, Any]						)    ->       int:
 return EnvironmentCommand()







class  _SCREAMING_SNAKE_CASE       (     SCREAMING_SNAKE_CASE__				):



 '''simple docstring'''





 @staticmethod
 def lowercase_      (lowerCAmelCase__   ):

  '''simple docstring'''







  _UpperCamelCase      :	Optional[Any]					      =  parser.add_parser("env"					,     help="Print relevant system environment info."   )
  download_parser.set_defaults(func=lowerCAmelCase__   )






 def lowercase_      (self   ):

  '''simple docstring'''







  _UpperCamelCase      :	Any					      =  {
      "`datasets` version": version,
      "Platform": platform.platform(),
      "Python version": platform.python_version(),
      "Huggingface_hub version": huggingface_hub.__version__,
      "PyArrow version": pyarrow.__version__,
      "Pandas version": pandas.__version__,
  }

  print("\nCopy-and-paste the text below in your GitHub issue.\n"   )
  print(self.format_dict(lowerCAmelCase__   )   )

  return info






 @staticmethod
 def lowercase_      (lowerCAmelCase__   ):

  '''simple docstring'''







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



