def test_set_obsm_key(adata):
    init_hash = joblib.hash(adata)

    orig_obsm_val = adata.obsm["o"].copy()
    subset_obsm = adata[:50]
    assert subset_obsm.is_view
    subset_obsm.obsm["o"] = np.ones((50, 20))
    assert not subset_obsm.is_view
    assert np.all(adata.obsm["o"] == orig_obsm_val)

    assert init_hash == joblib.hash(adata)
def batch_norm(inputs, training, data_format, name=''):
  """Performs a batch normalization using a standard set of parameters."""
  # We set fused=True for a significant performance boost. See
  # https://www.tensorflow.org/performance/performance_guide#common_fused_ops
  return tf.compat.v1.layers.batch_normalization(
      inputs=inputs,
      axis=1 if data_format == 'channels_first' else 3,
      momentum=_BATCH_NORM_DECAY,
      epsilon=_BATCH_NORM_EPSILON,
      center=True,
      scale=True,
      training=training,
      fused=True,
      name=name)