code: def get_embeddings(self, x):
      x = self.process_if_list(x)
      if isinstance(x, torch.Tensor):
          x = c_f.to_device(
              x, device=self.data_device, dtype=self.dtype
          )
      self.trunk.eval()
      self.embedder.eval()
      with torch.no_grad():
          x_emb = self.embedder(self.trunk(x))
      if self.normalize_embeddings:
          x_emb = torch.nn.functional.normalize(x_emb, p=2, dim=1)
      return x_emb
  
imports: import numpy
  import torch
  from ..distances import BatchedDistance, CosineSimilarity
  from .None import common_functions
label_desc: Use image node_id 7 for calling the InferenceModel obj's underlying member method code with example usage: obj.get_embeddings(x) and returns: x_emb