Missing newline

Author: ProfFan

Sources/TensorFlow/Layers/Recurrent.swift

@@ -537,39 +537,44 @@ extension Tensor: Mergeable where Scalar: TensorFlowFloatingPoint {
 }
 
 /// Concatenates two values.
-@differentiable(reverse)public func concatenate<T: Mergeable>(
+@differentiable(reverse)
+public func concatenate<T: Mergeable>(
   _ first: T,
   _ second: T
 ) -> T {
   T.concatenate(first, second)
 }
 
 /// Adds two values and produces their sum.
-@differentiable(reverse)public func sum<T: Mergeable>(
+@differentiable(reverse)
+public func sum<T: Mergeable>(
   _ first: T,
   _ second: T
 ) -> T {
   T.sum(first, second)
 }
 
 /// Averages two values.
-@differentiable(reverse)public func average<T: Mergeable>(
+@differentiable(reverse)
+public func average<T: Mergeable>(
   _ first: T,
   _ second: T
 ) -> T {
   T.average(first, second)
 }
 
 /// Multiplies two values.
-@differentiable(reverse)public func multiply<T: Mergeable>(
+@differentiable(reverse)
+public func multiply<T: Mergeable>(
   _ first: T,
   _ second: T
 ) -> T {
   T.multiply(first, second)
 }
 
 /// Stack two values.
-@differentiable(reverse)public func stack<T: Mergeable>(
+@differentiable(reverse)
+public func stack<T: Mergeable>(
   _ first: T,
   _ second: T
 ) -> T {

Sources/TensorFlow/Loss.swift

@@ -357,7 +357,8 @@ public func huberLoss<Scalar: TensorFlowFloatingPoint>(
 /// Workaround for TF-1030 so that we can use sum as a default argument for reductions.
 /// `Tensor<Scalar>.sum()` is the preferred way to do this.
 // TODO(TF-1030): Remove this and replace with `{ $0.sum() }`.
-@differentiable(reverse)public func _sum<Scalar: TensorFlowFloatingPoint>(
+@differentiable(reverse)
+public func _sum<Scalar: TensorFlowFloatingPoint>(
   _ value: Tensor<Scalar>
 ) -> Tensor<Scalar> {
   return value.sum()
@@ -366,7 +367,8 @@ public func huberLoss<Scalar: TensorFlowFloatingPoint>(
 /// Workaround for TF-1030 so that we can use mean as a default argument for reductions.
 /// `Tensor<Scalar>.mean()` is the preferred way to do this.
 // TODO(TF-1030): Remove this and replace with `{ $0.mean() }`.
-@differentiable(reverse)public func _mean<Scalar: TensorFlowFloatingPoint>(
+@differentiable(reverse)
+public func _mean<Scalar: TensorFlowFloatingPoint>(
   _ value: Tensor<Scalar>
 ) -> Tensor<Scalar> {
   return value.mean()

Sources/TensorFlow/Operators/LinearAlgebra.swift

@@ -235,7 +235,8 @@ func logdet<T: TensorFlowFloatingPoint>(_ matrix: Tensor<T>) -> Tensor<T> {
 ///
 /// - Parameter input: A tensor of shape `[..., M, M]`.
 @inlinable
-@differentiable(reverse)public func cholesky<T: TensorFlowFloatingPoint>(_ x: Tensor<T>) -> Tensor<T> {
+@differentiable(reverse)
+public func cholesky<T: TensorFlowFloatingPoint>(_ x: Tensor<T>) -> Tensor<T> {
   _Raw.cholesky(x)
 }
 
@@ -325,7 +326,8 @@ extension Tensor where Scalar: TensorFlowFloatingPoint {
 /// - Precondition: `matrix` must be a tensor with shape `[..., M, M]`.
 /// - Precondition: `rhs` must be a tensor with shape `[..., M, K]`.
 @inlinable
-@differentiable(reverse)public func triangularSolve<T: TensorFlowFloatingPoint>(
+@differentiable(reverse)
+public func triangularSolve<T: TensorFlowFloatingPoint>(
   matrix: Tensor<T>,
   rhs: Tensor<T>,
   lower: Bool = true,