code: def test_ideal_difference_from_metadata_no_matches(
      positive_items,
      negative_items,
      metadata_a,
      metadata_a_diff,
  ):
      ideal_diff = ideal_difference_from_metadata(
          positive_items=positive_items,
          negative_items=negative_items,
          metadata={"a": torch.tensor([0, 0, 0, 0, 1, 1, 1, 1, 1])},
          metadata_weights={"a": 0.2},
      )
  
      assert_array_equal(ideal_diff, torch.ones(4))
  
file_path: collie/tests/test_losses.py
imports: from numpy.testing import assert_almost_equal, assert_array_equal
  import pytest
  import torch
  from collie.loss import adaptive_bpr_loss, adaptive_hinge_loss, bpr_loss, hinge_loss, ideal_difference_from_metadata, warp_loss
label_desc: Use image node_id 3 for calling a global function with example usage: test_ideal_difference_from_metadata_no_matches(positive_items, negative_items, metadata_a, metadata_a_diff) without return types