




"""simple docstring"""




import platform
from argparse import ArgumentParser

import huggingface_hub

from .. import __version__ as version
from ..utils import is_accelerate_available, is_torch_available, is_transformers_available, is_xformers_available
from . import BaseDiffusersCLICommand
def   lowerCAmelCase						(					__UpperCamelCase      ):
 '''simple docstring'''





 return EnvironmentCommand()







class      __lowercase			(    __lowerCamelCase					):

  @staticmethod
  def    __lowercase       (  A		:			Union[str, Any]    ):






   '''simple docstring'''
   UpperCAmelCase__					:  List[str]					   =					parser.add_parser("""env"""    )
   download_parser.set_defaults(func=_SCREAMING_SNAKE_CASE    )

  def    __lowercase       (  self		:			Optional[int]    ):






   '''simple docstring'''
   UpperCAmelCase__					:  int					   =					huggingface_hub.__version__

   UpperCAmelCase__					:  Union[str, Any]					   =					"""not installed"""
   UpperCAmelCase__					:  List[Any]					   =					"""NA"""
   if is_torch_available():
    import torch

    UpperCAmelCase__					:  Optional[int]					   =					torch.__version__
    UpperCAmelCase__					:  List[str]					   =					torch.cuda.is_available()

   UpperCAmelCase__					:  Any					   =					"""not installed"""
   if is_transformers_available():
    import transformers

    UpperCAmelCase__					:  Optional[Any]					   =					transformers.__version__

   UpperCAmelCase__					:  int					   =					"""not installed"""
   if is_accelerate_available():
    import accelerate

    UpperCAmelCase__					:  str					   =					accelerate.__version__

   UpperCAmelCase__					:  str					   =					"""not installed"""
   if is_xformers_available():
    import xformers

    UpperCAmelCase__					:  Tuple					   =					xformers.__version__

   UpperCAmelCase__					:  Any					   =					{
       """`diffusers` version""": version,
       """Platform""": platform.platform(),
       """Python version""": platform.python_version(),
       """PyTorch version (GPU?)""": f"{pt_version} ({pt_cuda_available})",
       """Huggingface_hub version""": hub_version,
       """Transformers version""": transformers_version,
       """Accelerate version""": accelerate_version,
       """xFormers version""": xformers_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(_SCREAMING_SNAKE_CASE    )    )

   return info




  @staticmethod
  def    __lowercase       (  A		:			List[str]    ):






   '''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 OptionalDependencyNotAvailable, _LazyModule, is_torch_available


__UpperCAmelCase =				{
    'configuration_table_transformer': [
        'TABLE_TRANSFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP',
        'TableTransformerConfig',
        'TableTransformerOnnxConfig',
    ]
}

try:
      if not is_torch_available():
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      pass
else:
      __UpperCAmelCase =				[
          'TABLE_TRANSFORMER_PRETRAINED_MODEL_ARCHIVE_LIST',
          'TableTransformerForObjectDetection',
          'TableTransformerModel',
          'TableTransformerPreTrainedModel',
      ]


if TYPE_CHECKING:
      from .configuration_table_transformer import (
          TABLE_TRANSFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP,
          TableTransformerConfig,
          TableTransformerOnnxConfig,
      )

      try:
            if not is_torch_available():
                  raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
            pass
      else:
            from .modeling_table_transformer import (
                TABLE_TRANSFORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
                TableTransformerForObjectDetection,
                TableTransformerModel,
                TableTransformerPreTrainedModel,
            )

else:
      import sys

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





