Add Categorical Hinge Loss (#188)

Author: Shashi456

Sources/TensorFlow/Loss.swift

@@ -48,6 +48,20 @@ public func hingeLoss<Scalar: TensorFlowFloatingPoint>(
     return max(Tensor(1) - expected * predicted, Tensor(0)).mean()
 }
 
+/// Returns the hinge loss 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)
+public func categoricalHingeLoss<Scalar: TensorFlowFloatingPoint>(
+    predicted: Tensor<Scalar>, expected: Tensor<Scalar>
+) -> Tensor<Scalar> {
+    let positive = (expected * predicted).sum()
+    let negative = ((Tensor(1) - expected) * predicted).max()
+    return max(Tensor(0), negative - positive + Tensor(1))
+}
+
 /// Computes the softmax cross entropy (categorical cross entropy) between logits and labels.
 ///
 /// - Parameters:

Tests/TensorFlowTests/LossTests.swift

@@ -68,6 +68,15 @@ final class LossTests: XCTestCase {
         assertElementsEqual(expected: Tensor(expectedLoss), actual: loss)
     }
 
+    func testCategoricalHingeLoss() {
+        let predicted = Tensor<Float>([3, 4 ,5])
+        let expected = Tensor<Float>([0.3, 0.4, 0.3])
+
+        let loss = categoricalHingeLoss(predicted: predicted, expected: expected)
+        let expectedLoss: Float = 0.5
+        assertElementsEqual(expected: Tensor(expectedLoss), actual: loss)
+    }
+
     func testSoftmaxCrossEntropyWithProbabilitiesLoss() {
         let logits = Tensor<Float>(shape: [2, 4], scalars: [1, 2, 3, 4, 5, 6, 7, 8])
         let labels = Tensor<Float>(
@@ -161,6 +170,7 @@ final class LossTests: XCTestCase {
         ("testMeanSquaredErrorLoss", testMeanSquaredErrorLoss),
         ("testMeanSquaredErrorGrad", testMeanSquaredErrorGrad),
         ("testHingeLoss", testHingeLoss),
+        ("testCategoricalHingeLoss", testCategoricalHingeLoss),
         ("testSoftmaxCrossEntropyWithProbabilitiesLoss",
          testSoftmaxCrossEntropyWithProbabilitiesLoss),
         ("testSoftmaxCrossEntropyWithProbabilitiesGrad",