


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 				__SCREAMING_SNAKE_CASE   (			UpperCAmelCase__   ):
      A				:							Optional[int]    							=     {
          'sld_warmup_steps': 15,
          'sld_guidance_scale': 20,
          'sld_threshold': 0.0,
          'sld_momentum_scale': 0.0,
          'sld_mom_beta': 0.0,
      }
      A				:							List[Any]    							=     {
          'sld_warmup_steps': 10,
          'sld_guidance_scale': 1000,
          'sld_threshold': 0.01,
          'sld_momentum_scale': 0.3,
          'sld_mom_beta': 0.4,
      }
      A				:							Dict    							=     {
          'sld_warmup_steps': 7,
          'sld_guidance_scale': 2000,
          'sld_threshold': 0.025,
          'sld_momentum_scale': 0.5,
          'sld_mom_beta': 0.7,
      }
      A				:							Optional[int]    							=     {
          'sld_warmup_steps': 0,
          'sld_guidance_scale': 5000,
          'sld_threshold': 1.0,
          'sld_momentum_scale': 0.5,
          'sld_mom_beta': 0.7,
      }






@dataclass
class 				__SCREAMING_SNAKE_CASE   (			UpperCAmelCase__   ):
      A				:							Union[List[PIL.Image.Image], np.ndarray]
      A				:							Optional[List[bool]]
      A				:							Optional[Union[List[PIL.Image.Image], np.ndarray]]
      A				:							Optional[str]


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





from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


__a   				=      {
    '''configuration_decision_transformer''': [
        '''DECISION_TRANSFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP''',
        '''DecisionTransformerConfig''',
    ],
}

try:
  if not is_torch_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  __a   				=      [
      '''DECISION_TRANSFORMER_PRETRAINED_MODEL_ARCHIVE_LIST''',
      '''DecisionTransformerGPT2Model''',
      '''DecisionTransformerGPT2PreTrainedModel''',
      '''DecisionTransformerModel''',
      '''DecisionTransformerPreTrainedModel''',
  ]


if TYPE_CHECKING:
  from .configuration_decision_transformer import (
      DECISION_TRANSFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP,
      DecisionTransformerConfig,
  )

  try:
    if not is_torch_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .modeling_decision_transformer import (
        DECISION_TRANSFORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
        DecisionTransformerGPTaModel,
        DecisionTransformerGPTaPreTrainedModel,
        DecisionTransformerModel,
        DecisionTransformerPreTrainedModel,
    )


else:
  import sys

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

