moving cosine similarity to math ops

Author: Shashi456

Sources/TensorFlow/Loss.swift

@@ -102,19 +102,6 @@ public func hingeLoss<Scalar: TensorFlowFloatingPoint>(
     return max(Tensor(1) - expected * predicted, Tensor(0)).mean()
 }
 
-/// Returns the cosine similarity between predictions and expectations.
-///
-/// - Parameters:
-///   - predicted: Predicted outputs from a neural network.
-///   - expected: Expected values, i.e. targets, that correspond to the correct output.
-@differentiable(wrt: (predicted, expected))
-public func cosineSimilarity<Scalar: TensorFlowFloatingPoint>(
-    _ predicted: Tensor<Scalar>, _ expected: Tensor<Scalar>
-) -> Tensor<Scalar> {
-    return -(expected * predicted).sum() /
-        (sqrt(expected.squared().sum()) * sqrt(predicted.squared().sum()))
-}
-
 /// Returns the squared hinge loss between predictions and expectations.
 ///
 /// - Parameters:

Sources/TensorFlow/Operators/Math.swift

@@ -644,6 +644,15 @@ public func rsqrt<T: TensorFlowFloatingPoint>(_ x: Tensor<T>) -> Tensor<T> {
     Raw.rsqrt(x)
 }
 
+/// Returns the cosine similarity between x and y.
+@differentiable(wrt: (predicted, expected))
+public func cosineSimilarity<Scalar: TensorFlowFloatingPoint>(
+    _ x: Tensor<Scalar>, _ y: Tensor<Scalar>
+) -> Tensor<Scalar> {
+    return -(x * y).sum() /
+        (sqrt(x.squared().sum()) * sqrt(y.squared().sum()))
+}
+
 @inlinable
 internal func _vjpRsqrt<T: TensorFlowFloatingPoint>(
     _ x: Tensor<T>

Tests/TensorFlowTests/LossTests.swift

@@ -103,14 +103,6 @@ final class LossTests: XCTestCase {
         let expectedLoss: Float = 0.225
         assertElementsEqual(expected: Tensor(expectedLoss), actual: loss)
     }
-    
-    func testCosineSimilarityLoss() {
-        let predicted = Tensor<Float>([1, 2, 3, 4, 5, 6, 7, 8])
-        let expected = Tensor<Float>([0.5, 1, 1.5, 2.0, 2.5, 3.0, 3.5, 4.0])
-        let loss = cosineSimilarity(predicted: predicted, expected: expected)
-        let expectedLoss: Float = -1.0
-        assertElementsEqual(expected: Tensor(expectedLoss), actual: loss)
-    }
 
     func testSquaredHingeLoss() {
         let predicted = Tensor<Float>([1, 2, 3, 4, 5, 6, 7, 8])
@@ -245,7 +237,6 @@ final class LossTests: XCTestCase {
         ("testHingeLoss", testHingeLoss),
         ("testKullbackLeiblerDivergence", testKullbackLeiblerDivergence),
         ("testCategoricalHingeLoss", testCategoricalHingeLoss),
-        ("testCosineSimilarityLoss", testCosineSimilarityLoss),
         ("testSquaredHingeLoss", testSquaredHingeLoss),
         ("testPoissonLoss", testPoissonLoss),
         ("testSoftmaxCrossEntropyWithProbabilitiesLoss",

Tests/TensorFlowTests/OperatorTests/MathTests.swift

@@ -65,6 +65,14 @@ final class MathOperatorTests: XCTestCase {
         assertEqual(y, log(1 + x), accuracy: 0.0001)
     }
 
+    func testCosineSimilarity() {
+        let x = Tensor<Float>([1, 2, 3, 4, 5, 6, 7, 8])
+        let y = Tensor<Float>([0.5, 1, 1.5, 2.0, 2.5, 3.0, 3.5, 4.0])
+        let loss = cosineSimilarity(x, y)
+        let expectedLoss: Float = -1.0
+        assertElementsEqual(expected: Tensor(expectedLoss), actual: loss)
+    }
+
     // FIXME(https://bugs.swift.org/browse/TF-543): Disable failing test.
     /*
     func testExpm1() {
@@ -118,7 +126,7 @@ final class MathOperatorTests: XCTestCase {
             x.variance(squeezingAxes: 0),
             Tensor(shape: [5], scalars: [0, 0, 0, 0, 0]))
         XCTAssertEqual(
-            x.variance(alongAxes: 0), 
+            x.variance(alongAxes: 0),
             Tensor(shape: [5], scalars: [0, 0, 0, 0, 0]))
         XCTAssertEqual(
             x.variance(squeezingAxes: 1),
@@ -280,6 +288,7 @@ final class MathOperatorTests: XCTestCase {
         // ("testExpm1", testExpm1),
         ("testSign", testSign),
         ("testReduction", testReduction),
+        ("testCosineSimilarity", testCosineSimilarity)
         ("testArgmax", testArgmax),
         ("testCeilAndFloor", testCeilAndFloor),
         ("testSimpleMath", testSimpleMath),