class_docstr: Torch implementation of CLIP from
  https://github.com/mlfoundations/open_clip.
  
  Args:
      config: a :class:`TorchOpenClipModelConfig`
class_docstr_tok: ["Torch","implementation","of","CLIP","from","https",":","\/\/github.com\/mlfoundations\/open_clip",".","Args",":","config",":","a",":","class",":","`","TorchOpenClipModelConfig","`"]
code: def _predict_all(self, imgs):
      if self._preprocess:
          imgs = [self._preprocess(img).unsqueeze(0) for img in imgs]
  
      if isinstance(imgs, (list, tuple)):
          imgs = torch.stack(imgs)
  
      height, width = imgs.size()[-2:]
      frame_size = (width, height)
  
      if self._using_gpu:
          imgs = imgs.cuda()
  
      with torch.no_grad(), torch.cuda.amp.autocast():
          image_features = self._model.encode_image(imgs)
          text_features = self._get_text_features()
  
          output, _ = self._get_class_logits(
              text_features, image_features
          )
  
          if self.has_logits:
              self._output_processor.store_logits = self.store_logits
  
      return self._output_processor(
          output,
          frame_size,
          confidence_thresh=self.config.confidence_thresh,
      )
  
imports: import logging
  import fiftyone.core.models
  import fiftyone.core.utils
  import fiftyone.utils.torch
  import fiftyone.zoo.models
  import torch
label_desc: Use image node_id 9 for calling the TorchOpenClipModel obj's underlying member method code with example usage: obj._predict_all(imgs) and returns: self