code: def test_compute_embeddings_frames_skip_failures():
      dataset = fo.Dataset()
      dataset.add_samples(
          [
              fo.Sample(filepath="non-existent1.mp4"),
              fo.Sample(filepath="non-existent2.mp4"),
              fo.Sample(filepath="non-existent3.mp4"),
              fo.Sample(filepath="non-existent4.mp4"),
          ]
      )
  
      # torch, data loader, single batches
      model = foz.load_zoo_model("inception-v3-imagenet-torch")
      dataset.compute_embeddings(model)
  
      # torch, data loader, batches
      model = foz.load_zoo_model("inception-v3-imagenet-torch")
      dataset.compute_embeddings(model, batch_size=2)
  
      # TF, batch inference
      model = foz.load_zoo_model("resnet-v2-50-imagenet-tf1")
      dataset.compute_embeddings(model, batch_size=2)
  
imports: import unittest
  import numpy
  import pytest
  import fiftyone
  import fiftyone.zoo
  import fiftyone.utils.torch
label_desc: Use image node_id 19 for calling a global function with example usage: test_compute_embeddings_frames_skip_failures() without return types