Added Sin operator (#157)

* Added Sin operator

* Added ONNX sin test coverage

* Fix tests

* Remove unused error

* Remove unused error

* Fix lint

* Fix lint

* Use float type

---------

Co-authored-by: Swopper050 <[email protected]>

ops/opset13/opset13.go

@@ -27,6 +27,7 @@ var operators13 = map[string]func() ops.Operator{
 	"Scaler":          newScaler,
 	"Shape":           newShape,
 	"Sigmoid":         newSigmoid,
+	"Sin":             newSin,
 	"Slice":           newSlice,
 	"Squeeze":         newSqueeze,
 	"Sub":             newSub,

ops/opset13/opset13_test.go

@@ -118,6 +118,11 @@ func TestGetOperator(t *testing.T) {
 			newSigmoid(),
 			nil,
 		},
+		{
+			"Sin",
+			newSin(),
+			nil,
+		},
 		{
 			"Slice",
 			newSlice(),

ops/opset13/sin.go

@@ -0,0 +1,75 @@
+package opset13
+
+import (
+	"math"
+
+	"github.com/advancedclimatesystems/gonnx/onnx"
+	"github.com/advancedclimatesystems/gonnx/ops"
+	"gorgonia.org/tensor"
+)
+
+// Sin represents the ONNX sin operator.
+type Sin struct{}
+
+// newSin creates a new sin operator.
+func newSin() ops.Operator {
+	return &Sin{}
+}
+
+// Init initializes the sin operator.
+func (s *Sin) Init(_ []*onnx.AttributeProto) error {
+	return nil
+}
+
+// Apply applies the sin operator.
+func (s *Sin) Apply(inputs []tensor.Tensor) ([]tensor.Tensor, error) {
+	var (
+		out tensor.Tensor
+		err error
+	)
+
+	switch inputs[0].Dtype() {
+	case tensor.Float32:
+		out, err = inputs[0].Apply(sin[float32])
+	case tensor.Float64:
+		out, err = inputs[0].Apply(sin[float64])
+	default:
+		return nil, ops.ErrInvalidInputType(0, inputs[0].Dtype().String(), s)
+	}
+
+	if err != nil {
+		return nil, err
+	}
+
+	return []tensor.Tensor{out}, nil
+}
+
+// ValidateInputs validates the inputs that will be given to Apply for this operator.
+func (s *Sin) ValidateInputs(inputs []tensor.Tensor) ([]tensor.Tensor, error) {
+	return ops.ValidateInputs(s, inputs)
+}
+
+// GetMinInputs returns the minimum number of input tensors this operator expects.
+func (s *Sin) GetMinInputs() int {
+	return 1
+}
+
+// GetMaxInputs returns the maximum number of input tensors this operator expects.
+func (s *Sin) GetMaxInputs() int {
+	return 1
+}
+
+// GetInputTypeConstraints returns a list. Every element represents a set of allowed tensor dtypes
+// for the corresponding input tensor.
+func (s *Sin) GetInputTypeConstraints() [][]tensor.Dtype {
+	return [][]tensor.Dtype{{tensor.Float32, tensor.Float64}}
+}
+
+// String implements the stringer interface, and can be used to format errors or messages.
+func (s *Sin) String() string {
+	return "sin operator"
+}
+
+func sin[T ops.FloatType](x T) T {
+	return T(math.Sin(float64(x)))
+}

ops/opset13/sin_test.go

@@ -0,0 +1,99 @@
+package opset13
+
+import (
+	"testing"
+
+	"github.com/advancedclimatesystems/gonnx/ops"
+	"github.com/stretchr/testify/assert"
+	"gorgonia.org/tensor"
+)
+
+func TestSinInit(t *testing.T) {
+	a := &Sin{}
+
+	// since 'sin' does not have any attributes we pass in nil. This should not
+	// fail initializing the sin.
+	err := a.Init(nil)
+	assert.Nil(t, err)
+}
+
+func TestSin(t *testing.T) {
+	tests := []struct {
+		sin      *Sin
+		backing  []float32
+		shape    []int
+		expected []float32
+	}{
+		{
+			&Sin{},
+			[]float32{-2, -1, 0, 1},
+			[]int{2, 2},
+			[]float32{-0.9092974, -0.84147096, 0, 0.84147096},
+		},
+		{
+			&Sin{},
+			[]float32{1, 3, 4, 5},
+			[]int{1, 4},
+			[]float32{0.84147096, 0.14112, -0.7568025, -0.9589243},
+		},
+		{
+			&Sin{},
+			[]float32{-1, -1, -1, -1},
+			[]int{1, 4},
+			[]float32{-0.84147096, -0.84147096, -0.84147096, -0.84147096},
+		},
+	}
+
+	for _, test := range tests {
+		inputs := []tensor.Tensor{
+			ops.TensorWithBackingFixture(test.backing, test.shape...),
+		}
+
+		res, err := test.sin.Apply(inputs)
+		assert.Nil(t, err)
+
+		assert.Nil(t, err)
+		assert.Equal(t, test.expected, res[0].Data())
+	}
+}
+
+func TestInputValidationSin(t *testing.T) {
+	tests := []struct {
+		inputs []tensor.Tensor
+		err    error
+	}{
+		{
+			[]tensor.Tensor{
+				ops.TensorWithBackingFixture([]float32{1, 2}, 2),
+			},
+			nil,
+		},
+		{
+			[]tensor.Tensor{
+				ops.TensorWithBackingFixture([]float64{1, 2}, 2),
+			},
+			nil,
+		},
+		{
+			[]tensor.Tensor{},
+			ops.ErrInvalidInputCount(0, &Sin{}),
+		},
+		{
+			[]tensor.Tensor{
+				ops.TensorWithBackingFixture([]int{1, 2}, 2),
+			},
+			ops.ErrInvalidInputType(0, "int", &Sin{}),
+		},
+	}
+
+	for _, test := range tests {
+		sin := &Sin{}
+		validated, err := sin.ValidateInputs(test.inputs)
+
+		assert.Equal(t, test.err, err)
+
+		if test.err == nil {
+			assert.Equal(t, test.inputs, validated)
+		}
+	}
+}

ops_test.go

@@ -335,6 +335,8 @@ var expectedTests = []string{
 	"test_reshape_zero_and_negative_dim",
 	"test_reshape_zero_dim",
 	"test_shape",
+	"test_sin",
+	"test_sin_example",
 	"test_sigmoid_example",
 	"test_sigmoid",
 	"test_slice_negative_axes",