





'''simple docstring'''



from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available


_SCREAMING_SNAKE_CASE   =      {
    '''configuration_chinese_clip''': [
        '''CHINESE_CLIP_PRETRAINED_CONFIG_ARCHIVE_MAP''',
        '''ChineseCLIPConfig''',
        '''ChineseCLIPOnnxConfig''',
        '''ChineseCLIPTextConfig''',
        '''ChineseCLIPVisionConfig''',
    ],
    '''processing_chinese_clip''': ['''ChineseCLIPProcessor'''],
}

try:
 if not is_vision_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 _SCREAMING_SNAKE_CASE   =      ['''ChineseCLIPFeatureExtractor''']
 _SCREAMING_SNAKE_CASE   =      ['''ChineseCLIPImageProcessor''']

try:
 if not is_torch_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 _SCREAMING_SNAKE_CASE   =      [
     '''CHINESE_CLIP_PRETRAINED_MODEL_ARCHIVE_LIST''',
     '''ChineseCLIPModel''',
     '''ChineseCLIPPreTrainedModel''',
     '''ChineseCLIPTextModel''',
     '''ChineseCLIPVisionModel''',
 ]

if TYPE_CHECKING:
 from .configuration_chinese_clip import (
     CHINESE_CLIP_PRETRAINED_CONFIG_ARCHIVE_MAP,
     ChineseCLIPConfig,
     ChineseCLIPOnnxConfig,
     ChineseCLIPTextConfig,
     ChineseCLIPVisionConfig,
 )
 from .processing_chinese_clip import ChineseCLIPProcessor

 try:
  if not is_vision_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .feature_extraction_chinese_clip import ChineseCLIPFeatureExtractor, ChineseCLIPImageProcessor

 try:
  if not is_torch_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .modeling_chinese_clip import (
      CHINESE_CLIP_PRETRAINED_MODEL_ARCHIVE_LIST,
      ChineseCLIPModel,
      ChineseCLIPPreTrainedModel,
      ChineseCLIPTextModel,
      ChineseCLIPVisionModel,
  )

else:
 import sys

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












'''simple docstring'''



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 							__lowercase    ( lowerCAmelCase__  ):







	'''simple docstring'''

	a      :			Union[List[PIL.Image.Image], np.ndarray]
	a      :			Optional[List[bool]]


if is_transformers_available() and is_torch_available():
	from .pipeline_semantic_stable_diffusion import SemanticStableDiffusionPipeline





