code: def _load_frame_patch_embeddings(samples, path):
      embeddings_dict = {}
      for sample_id, frame_numbers, frame_embeddings in zip(
          *samples.values(["id", "frames.frame_number", path])
      ):
          frame_embeddings_dict = {}
          for frame_number, embeddings in zip(
              frame_numbers, frame_embeddings
          ):
              if embeddings:
                  frame_embeddings_dict[frame_number] = np.stack(
                      embeddings
                  )
  
          embeddings_dict[sample_id] = frame_embeddings_dict
  
      return embeddings_dict
  
imports: import unittest
  import numpy
  import pytest
  import fiftyone
  import fiftyone.zoo
  import fiftyone.utils.torch
label_desc: Use image node_id 13 for calling a global function with example usage: _load_frame_patch_embeddings(samples, path) and returns: embeddings_dict