def test_view_delattr(attr, subset_func):
    base = gen_adata((10, 10))
    orig_hash = joblib.hash(base)
    subset = base[subset_func(base.obs_names), subset_func(base.var_names)]
    empty = ad.AnnData(obs=subset.obs[[]], var=subset.var[[]])

    delattr(subset, attr)

    assert not subset.is_view
    # Should now have same value as default
    assert_equal(getattr(subset, attr), getattr(empty, attr))
    assert orig_hash == joblib.hash(base)  # Original should not be modified
def conv2d_fixed_padding(inputs, filters, kernel_size, strides, data_format,
                         name):
  """Strided 2-D convolution with explicit padding."""
  # The padding is consistent and is based only on `kernel_size`, not on the
  # dimensions of `inputs` (as opposed to using `tf.layers.conv2d` alone).
  if strides > 1:
    inputs = fixed_padding(inputs, kernel_size, data_format)

  return tf.compat.v1.layers.conv2d(
      inputs=inputs,
      filters=filters,
      kernel_size=kernel_size,
      strides=strides,
      padding=('SAME' if strides == 1 else 'VALID'),
      use_bias=False,
      reuse=tf.AUTO_REUSE,
      kernel_initializer=tf.compat.v1.variance_scaling_initializer(),
      data_format=data_format,
      name=name)