code: def test_h5_file(h5_file):
      rows, dims = 258, 32
      create_random_dataset(h5_file, rows, dims)
  
      # Load data
      with h5py.File(h5_file, "r") as f:
          X_train = f["data"]
          y_train = f["labels"]
  
          # Train and transform with ivis
          model = Ivis(
              epochs=5,
              k=15,
              batch_size=16,
              precompute=False,
              build_index_on_disk=False,
          )
          y_pred = model.fit_transform(X_train, shuffle_mode="batch")
  
          assert y_pred.shape[0] == len(X_train)
          assert y_pred.shape[1] == model.embedding_dims
  
file_path: ivis/tests/integration/test_h5.py
imports: import tempfile
  import h5py
  import numpy
  import pytest
  from ivis import Ivis
label_desc: Use image node_id 3 for calling a global function with example usage: test_h5_file(h5_file) without return types