

from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_flax_available,
    is_sentencepiece_available,
    is_tf_available,
    is_tokenizers_available,
    is_torch_available,
)


A_						:     Optional[Any]			  =				{
    'configuration_switch_transformers': [
        'SWITCH_TRANSFORMERS_PRETRAINED_CONFIG_ARCHIVE_MAP',
        'SwitchTransformersConfig',
        'SwitchTransformersOnnxConfig',
    ]
}

try:
       if not is_torch_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       A_						:     int			  =				[
           'SWITCH_TRANSFORMERS_PRETRAINED_MODEL_ARCHIVE_LIST',
           'SwitchTransformersEncoderModel',
           'SwitchTransformersForConditionalGeneration',
           'SwitchTransformersModel',
           'SwitchTransformersPreTrainedModel',
           'SwitchTransformersTop1Router',
           'SwitchTransformersSparseMLP',
       ]


if TYPE_CHECKING:
       from .configuration_switch_transformers import (
           SWITCH_TRANSFORMERS_PRETRAINED_CONFIG_ARCHIVE_MAP,
           SwitchTransformersConfig,
           SwitchTransformersOnnxConfig,
       )

       try:
              if not is_torch_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .modeling_switch_transformers import (
                  SWITCH_TRANSFORMERS_PRETRAINED_MODEL_ARCHIVE_LIST,
                  SwitchTransformersEncoderModel,
                  SwitchTransformersForConditionalGeneration,
                  SwitchTransformersModel,
                  SwitchTransformersPreTrainedModel,
                  SwitchTransformersSparseMLP,
                  SwitchTransformersTopaRouter,
              )


else:
       import sys

       A_						:     Union[str, Any]			  =				_LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)







from dataclasses import dataclass
from enum import Enum
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
class    A_				( _a  ):


    '''simple docstring'''






    a__       							=    {
        "sld_warmup_steps": 15,
        "sld_guidance_scale": 20,
        "sld_threshold": 0.0,
        "sld_momentum_scale": 0.0,
        "sld_mom_beta": 0.0,
    }
    a__       							=    {
        "sld_warmup_steps": 10,
        "sld_guidance_scale": 10_00,
        "sld_threshold": 0.01,
        "sld_momentum_scale": 0.3,
        "sld_mom_beta": 0.4,
    }
    a__       							=    {
        "sld_warmup_steps": 7,
        "sld_guidance_scale": 20_00,
        "sld_threshold": 0.0_25,
        "sld_momentum_scale": 0.5,
        "sld_mom_beta": 0.7,
    }
    a__       							=    {
        "sld_warmup_steps": 0,
        "sld_guidance_scale": 50_00,
        "sld_threshold": 1.0,
        "sld_momentum_scale": 0.5,
        "sld_mom_beta": 0.7,
    }






@dataclass
class    A_				( _a  ):


    '''simple docstring'''






    a__       							=    42
    a__       							=    42
    a__       							=    42
    a__       							=    42


if is_transformers_available() and is_torch_available():
       from .pipeline_stable_diffusion_safe import StableDiffusionPipelineSafe
       from .safety_checker import SafeStableDiffusionSafetyChecker




