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 			lowercase_				(			_lowerCamelCase							:       List[str]):
    return EnvironmentCommand()



class   snake_case_       (		__A       ):






   @staticmethod
   def       __UpperCamelCase     (      lowercase_				:     ArgumentParser  )					->						str:
       lowercase__ :   List[Any]    					=				parser.add_parser("env"  )
       download_parser.set_defaults(func=lowercase_  )






   def       __UpperCamelCase     (      self				:     Union[str, Any]  )					->						Optional[int]:
       lowercase__ :   Optional[int]    					=				huggingface_hub.__version__

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

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

       lowercase__ :   Union[str, Any]    					=				"not installed"
       if is_transformers_available():
           import transformers

           lowercase__ :   Any    					=				transformers.__version__

       lowercase__ :   str    					=				"not installed"
       if is_accelerate_available():
           import accelerate

           lowercase__ :   Optional[int]    					=				accelerate.__version__

       lowercase__ :   List[str]    					=				"not installed"
       if is_xformers_available():
           import xformers

           lowercase__ :   Optional[int]    					=				xformers.__version__

       lowercase__ :   List[str]    					=				{
           "`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(lowercase_  )  )

       return info







   @staticmethod
   def       __UpperCamelCase     (      lowercase_				:     str  )					->						Dict:
       return "\n".join([F'''- {prop}: {val}''' for prop, val in d.items()]  ) + "\n"







'''simple docstring'''



from . import (
    albert,
    align,
    altclip,
    audio_spectrogram_transformer,
    auto,
    autoformer,
    bark,
    bart,
    barthez,
    bartpho,
    beit,
    bert,
    bert_generation,
    bert_japanese,
    bertweet,
    big_bird,
    bigbird_pegasus,
    biogpt,
    bit,
    blenderbot,
    blenderbot_small,
    blip,
    blip_a,
    bloom,
    bridgetower,
    byta,
    camembert,
    canine,
    chinese_clip,
    clap,
    clip,
    clipseg,
    codegen,
    conditional_detr,
    convbert,
    convnext,
    convnextva,
    cpm,
    cpmant,
    ctrl,
    cvt,
    dataavec,
    deberta,
    deberta_va,
    decision_transformer,
    deformable_detr,
    deit,
    deprecated,
    deta,
    detr,
    dialogpt,
    dinat,
    distilbert,
    dit,
    donut,
    dpr,
    dpt,
    efficientformer,
    efficientnet,
    electra,
    encodec,
    encoder_decoder,
    ernie,
    ernie_m,
    esm,
    falcon,
    flaubert,
    flava,
    fnet,
    focalnet,
    fsmt,
    funnel,
    git,
    glpn,
    gpta,
    gpt_bigcode,
    gpt_neo,
    gpt_neox,
    gpt_neox_japanese,
    gpt_swa,
    gptj,
    gptsan_japanese,
    graphormer,
    groupvit,
    herbert,
    hubert,
    ibert,
    imagegpt,
    informer,
    instructblip,
    jukebox,
    layoutlm,
    layoutlmva,
    layoutlmva,
    layoutxlm,
    led,
    levit,
    lilt,
    llama,
    longformer,
    longta,
    luke,
    lxmert,
    mam_aaa,
    marian,
    markuplm,
    maskaformer,
    maskformer,
    mbart,
    mbartaa,
    mega,
    megatron_bert,
    megatron_gpta,
    mgp_str,
    mluke,
    mobilebert,
    mobilenet_va,
    mobilenet_va,
    mobilevit,
    mobilevitva,
    mpnet,
    mra,
    mta,
    musicgen,
    mvp,
    nat,
    nezha,
    nllb,
    nllb_moe,
    nystromformer,
    oneformer,
    open_llama,
    openai,
    opt,
    owlvit,
    pegasus,
    pegasus_x,
    perceiver,
    phobert,
    pixastruct,
    plbart,
    poolformer,
    prophetnet,
    qdqbert,
    rag,
    realm,
    reformer,
    regnet,
    rembert,
    resnet,
    roberta,
    roberta_prelayernorm,
    roc_bert,
    roformer,
    rwkv,
    sam,
    segformer,
    sew,
    sew_d,
    speech_encoder_decoder,
    speech_to_text,
    speech_to_text_a,
    speechta,
    splinter,
    squeezebert,
    swiftformer,
    swin,
    swinasr,
    swinva,
    switch_transformers,
    ta,
    table_transformer,
    tapas,
    time_series_transformer,
    timesformer,
    timm_backbone,
    transfo_xl,
    trocr,
    tvlt,
    umta,
    unispeech,
    unispeech_sat,
    upernet,
    videomae,
    vilt,
    vision_encoder_decoder,
    vision_text_dual_encoder,
    visual_bert,
    vit,
    vit_hybrid,
    vit_mae,
    vit_msn,
    vivit,
    wavaveca,
    wavaveca_conformer,
    wavaveca_phoneme,
    wavaveca_with_lm,
    wavlm,
    whisper,
    x_clip,
    xglm,
    xlm,
    xlm_prophetnet,
    xlm_roberta,
    xlm_roberta_xl,
    xlnet,
    xmod,
    yolos,
    yoso,
)






