 ///   - normalized: indicates if the offset coordinates are normalized.
 ///   - uniform_noise: indicates if the noise should be generated using a
 ///     uniform distribution or a Gaussian distribution.
+///   - noise: indicates if the noise should `uniform`, `gaussian`, or
+///     `zero`. The default is `uniform` which means the the noise type
+///     will be decided by `uniform_noise`.
 ///
 /// - Output glimpse: A tensor representing the glimpses `[batch_size,
 ///   glimpse_height, glimpse_width, channels]`.

  return (Tensor(handle: ret.0), Tensor(handle: ret.1), Tensor(handle: ret.2), Tensor(handle: ret.3), Tensor(handle: ret.4))
}

/// Generates labels for candidate sampling with a learned unigram distribution.
///
/// See explanations of candidate sampling and the data formats at

  filter: Tensor<T>,
  strides: [Int32],
  padding: Padding,
  dataFormat: DataFormat1 = .b'ndhwc',
  dilations: [Int32] = [1, 1, 1, 1, 1]
) -> Tensor<T> {
  let ret: TensorHandle<T> = #tfop("Conv3D",
