 /// - Outputs:
 ///   - output_indices: 2-D.  The indices of the output SparseTensor.
 ///   - output_values: 1-D.  The values of the output SparseTensor.
-@_inlineable @inline(__always)
+@inlinable @inline(__always)
 public static func sparseSparseMaximum<T: Numeric>(
   aIndices: Tensor<Int64>,
   aValues: Tensor<T>,

///     var - lr * momentum * accum.
///
/// - Output out: Same as "var".
@_inlineable @inline(__always)
public static func applyMomentum<T: Numeric>(
  var_: Tensor<T>,
  accum: Tensor<T>,

/// - Outputs:
///   - loss: Per example loss (batch_size vector).
///   - backprop: backpropagated gradients (batch_size x num_classes matrix).
@inlinable @inline(__always)
public static func sparseSoftmaxCrossEntropyWithLogits<T: BinaryFloatingPoint, Tlabels: BinaryInteger>(
  features: Tensor<T>,
  labels: Tensor<Tlabels>
