code: def get_all_embeddings(
      self,
      dataset,
      trunk_model,
      embedder_model=None,
      collate_fn=None,
      eval=True,
      return_as_numpy=False,
  ):
      if embedder_model is None:
          embedder_model = torch.nn.Identity()
      if eval:
          trunk_model.eval()
          embedder_model.eval()
      dataloader = c_f.get_eval_dataloader(
          dataset,
          self.batch_size,
          self.dataloader_num_workers,
          collate_fn,
      )
      embeddings, labels = self.compute_all_embeddings(
          dataloader, trunk_model, embedder_model
      )
      embeddings = self.maybe_normalize(embeddings)
      if return_as_numpy:
          return embeddings.cpu().numpy(), labels.cpu().numpy()
      return embeddings, labels
  
imports: from collections import defaultdict
  import torch
  import tqdm
  from ..utils import common_functions
  from ..utils import inference
  from ..utils.accuracy_calculator import AccuracyCalculator
label_desc: Use image node_id 7 for calling the BaseTester obj's underlying member method code with example usage: obj.get_all_embeddings(dataset, trunk_model, embedder_model, collate_fn, eval, return_as_numpy) and returns: embeddings,  labels, embeddings,  labels