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Refactor cosine similarity and add cosine distance #240

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Jun 16, 2019
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Refactor cosine similarity and add cosine distance #240

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db478bd
Removing argument labels from cosine similarity:
Shashi456 Jun 14, 2019
cc648b0
Removing argument labels acc to swift docs
Shashi456 Jun 14, 2019
5a5ed0c
moving cosine similarity to math ops
Shashi456 Jun 14, 2019
7487a58
appending comma to tests
Shashi456 Jun 14, 2019
e76de20
Forgot changin expected, predicted to x, y
Shashi456 Jun 14, 2019
17f5a75
Anthony's comments
Shashi456 Jun 14, 2019
650f84e
Review
Shashi456 Jun 14, 2019
9410ec2
fixing test
Shashi456 Jun 14, 2019
68a3c16
Merge branch 'master' of https://github.com/tensorflow/swift-apis int…
Shashi456 Jun 15, 2019
18d97c2
fixing cosine test
Shashi456 Jun 15, 2019
af0ab9e
test error
Shashi456 Jun 15, 2019
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13 changes: 0 additions & 13 deletions Sources/TensorFlow/Loss.swift
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Original file line number Diff line number Diff line change
Expand Up @@ -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:
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17 changes: 17 additions & 0 deletions Sources/TensorFlow/Operators/Math.swift
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Expand Up @@ -774,6 +774,23 @@ public func rsqrt<T: TensorFlowFloatingPoint>(_ x: Tensor<T>) -> Tensor<T> {
Raw.rsqrt(x)
}

/// Returns the cosine similarity between `x` and `y`.
@differentiable
public func cosineSimilarity<Scalar: TensorFlowFloatingPoint>(
_ x: Tensor<Scalar>, _ y: Tensor<Scalar>
) -> Tensor<Scalar> {
(x * y).sum() / (sqrt(x.squared().sum()) * sqrt(y.squared().sum()))
}

/// Returns the cosine distance between `x` and `y`. Cosine distance is defined as
/// `1 - cosineSimilarity(x, y)`.
@differentiable
public func cosineDistance<Scalar: TensorFlowFloatingPoint>(
_ x: Tensor<Scalar>, _ y: Tensor<Scalar>
) -> Tensor<Scalar> {
1 - cosineSimilarity(x, y)
}

@inlinable
internal func _vjpRsqrt<T: TensorFlowFloatingPoint>(
_ x: Tensor<T>
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9 changes: 0 additions & 9 deletions Tests/TensorFlowTests/LossTests.swift
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Expand Up @@ -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])
Expand Down Expand Up @@ -245,7 +237,6 @@ final class LossTests: XCTestCase {
("testHingeLoss", testHingeLoss),
("testKullbackLeiblerDivergence", testKullbackLeiblerDivergence),
("testCategoricalHingeLoss", testCategoricalHingeLoss),
("testCosineSimilarityLoss", testCosineSimilarityLoss),
("testSquaredHingeLoss", testSquaredHingeLoss),
("testPoissonLoss", testPoissonLoss),
("testSoftmaxCrossEntropyWithProbabilitiesLoss",
Expand Down
11 changes: 10 additions & 1 deletion Tests/TensorFlowTests/OperatorTests/MathTests.swift
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Expand Up @@ -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 z = cosineSimilarity(x, y)
let output: Float = 1.0
XCTAssertEqual(z, Tensor(output))
}

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Could you please also add a test for cosine distance?

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@saeta, actually cosine distance just returns 1 - cosineSimilarity, so in effect we would be testing the same function. To avoid redundancy I didn't add a test

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Even though the function is implemented as a trivial wrapper, it's good practice to assume the implementation can change in the future for whatever reasons and have tests be implementation-agnostic.

// FIXME(https://bugs.swift.org/browse/TF-543): Disable failing test.
/*
func testExpm1() {
Expand Down Expand Up @@ -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),
Expand Down Expand Up @@ -280,6 +288,7 @@ final class MathOperatorTests: XCTestCase {
// ("testExpm1", testExpm1),
("testSign", testSign),
("testReduction", testReduction),
("testCosineSimilarity", testCosineSimilarity),
("testArgmax", testArgmax),
("testCeilAndFloor", testCeilAndFloor),
("testSimpleMath", testSimpleMath),
Expand Down