 /// - Outputs:
 ///   - output_min: The float value that the minimum quantized output value represents.
 ///   - output_max: The float value that the maximum quantized output value represents.
-@_inlineable @inline(__always)
+@inlinable @inline(__always)
 public static func quantizeDownAndShrinkRange<Tinput: AccelerableByTensorFlow, Out_type: AccelerableByTensorFlow>(
   _ input: Tensor<Tinput>,
   inputMin: Tensor<Float>,

/// - Output output: A `Tensor` with the concatenation of values stacked along the
///   `concat_dim` dimension.  This tensor's shape matches that of `values` except
///   in `concat_dim` where it has the sum of the sizes.
@_inlineable @inline(__always)
public static func concat<T: AccelerableByTensorFlow>(
  concatDim: Tensor<Int32>,
  values: [Tensor<T>]

///   - v: A `Tensor` of type T. Same dimension sizes as x except the first dimension, which must be the same as i's size.
///
/// - Output y: A `Tensor` of type T. An alias of `x`. The content of `y` is undefined if there are duplicates in `i`.
@inlinable @inline(__always)
public static func inplaceSub<T: AccelerableByTensorFlow>(
  _ x: Tensor<T>,
  i: Tensor<Int32>,
