Apply swift-format tool

Author: vvmnnnkv

FastStyleTransfer/Demo/main.swift

@@ -19,11 +19,14 @@ struct Config {
 }
 
 var config = Config()
-parseArguments(into: &config, with: [
-    "weights": \Config.weights, 
-    "image": \Config.image, 
-    "output": \Config.output
-])
+parseArguments(
+    into: &config,
+    with: [
+        "weights": \Config.weights,
+        "image": \Config.image,
+        "output": \Config.output
+    ]
+)
 
 guard let image = config.image, let output = config.output else {
     print("Error: No input image!")

FastStyleTransfer/Models/TransformerNet.swift

@@ -122,10 +122,7 @@ public struct ResidualBlock: Layer {
     /// - Returns: The output.
     @differentiable
     public func callAsFunction(_ input: Input) -> Output {
-        return input + input.sequenced(through:
-            conv1, in1, relu,
-            conv2, in2
-        )
+        return input + input.sequenced(through: conv1, in1, relu, conv2, in2)
     }
 }
 

FastStyleTransfer/Utility/ImportableLayer.swift

@@ -36,7 +36,7 @@ public extension ImportableLayer {
 
     /// Returns map of all recursive properties name to keypath.
     func getRecursiveNamedKeyPaths<T>(
-            ofType valueType: T.Type
+        ofType valueType: T.Type
     ) -> [String: WritableKeyPath<Self, T>] {
         let labels = getRecursiveProperties(ofType: T.self)
         let keys = self.recursivelyAllWritableKeyPaths(to: T.self)
@@ -69,7 +69,7 @@ public extension ImportableLayer {
     mutating func unsafeImport(fromCheckpointPath path: String, map: ImportMap) {
         let tensorNames = map.values.map { $0.0 }
         let tensorValues = Raw.restoreV2(
-            prefix: StringTensor(path), 
+            prefix: StringTensor(path),
             tensorNames: StringTensor(tensorNames),
             shapeAndSlices: StringTensor(Array(repeating: "", count: tensorNames.count)),
             dtypes: Array(repeating: Float.tensorFlowDataType, count: tensorNames.count)

FastStyleTransfer/Utility/Resize.swift

@@ -16,14 +16,17 @@ public func resizeNearestNeighbor<Scalar: TensorFlowFloatingPoint>(
 
 @usableFromInline
 internal func _vjpResizeNearestNeighbor<Scalar: TensorFlowFloatingPoint>(
-        input: Tensor<Scalar>, scaleFactor: Float
+    input: Tensor<Scalar>, scaleFactor: Float
 ) -> (Tensor<Scalar>, (Tensor<Scalar>) -> Tensor<Scalar>) {
     let result = resizeNearestNeighbor(input, scaleFactor: scaleFactor)
-    return (result, { v in
-        let size = Tensor<Int32>(
-            shape: [2],
-            scalars: [input.shape[1], input.shape[2]].map { Int32($0) }
-        )
-        return Raw.resizeNearestNeighborGrad(grads: result, size: size)
-    })
+    return (
+        result,
+        { v in
+            let size = Tensor<Int32>(
+                shape: [2],
+                scalars: [input.shape[1], input.shape[2]].map { Int32($0) }
+            )
+            return Raw.resizeNearestNeighborGrad(grads: result, size: size)
+        }
+    )
 }

FastStyleTransfer/Utility/Tensor+Additions.swift

@@ -18,15 +18,18 @@ public extension Tensor where Scalar: Numeric {
 internal extension Tensor where Scalar: TensorFlowFloatingPoint {
     @inlinable
     func _vjpPaddedWithReflection(
-            forSizes sizes: [(before: Int, after: Int)]
+        forSizes sizes: [(before: Int, after: Int)]
     ) -> (Tensor, (Tensor) -> Tensor) {
         let result = paddedWithReflection(forSizes: sizes)
-        return (result, { v in
-            let paddings = Tensor<Int32>(
-                shape: [sizes.count, 2],
-                scalars: sizes.flatMap { [Int32($0.before), Int32($0.after)] }
-            )
-            return Raw.mirrorPadGrad(result, paddings: paddings, mode: Raw.Mode5.reflect)
-        })
+        return (
+            result,
+            { v in
+                let paddings = Tensor<Int32>(
+                    shape: [sizes.count, 2],
+                    scalars: sizes.flatMap { [Int32($0.before), Int32($0.after)] }
+                )
+                return Raw.mirrorPadGrad(result, paddings: paddings, mode: Raw.Mode5.reflect)
+            }
+        )
     }
 }