
from dataclasses import dataclass
from typing import List, Optional, Union

import numpy as np
import PIL
from PIL import Image

from ...utils import BaseOutput, is_torch_available, is_transformers_available






@dataclass
# Copied from diffusers.pipelines.stable_diffusion.__init__.StableDiffusionPipelineOutput with Stable->Alt
class 						UpperCAmelCase	(		A_				):
   A__      :	Union[List[PIL.Image.Image], np.ndarray]
   A__      :	Optional[List[bool]]


if is_transformers_available() and is_torch_available():
   from .modeling_roberta_series import RobertaSeriesModelWithTransformation
   from .pipeline_alt_diffusion import AltDiffusionPipeline
   from .pipeline_alt_diffusion_imgaimg import AltDiffusionImgaImgPipeline







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     UpperCamelCase      (					__lowerCamelCase  :				int					):
       return EnvironmentCommand()






class 						UpperCAmelCase	(		A_				):



   @staticmethod
   def        _SCREAMING_SNAKE_CASE     (snake_case__	:      ArgumentParser				)	->			Any:


          '''simple docstring'''


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



   def        _SCREAMING_SNAKE_CASE     (self	:      Dict				)	->			Optional[Any]:


          '''simple docstring'''


          snake_case :     List[str]           =   {
              "`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(snake_case__				)				)

          return info



   @staticmethod
   def        _SCREAMING_SNAKE_CASE     (snake_case__	:      Tuple				)	->			Any:


          '''simple docstring'''


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





