Added Sinh operator (#158)

* Added sinh operator

* Updated comments

* Use FloatType

---------

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

ops/opset13/opset13.go

@@ -29,6 +29,7 @@ var operators13 = map[string]func() ops.Operator{
 	"Shape":           newShape,
 	"Sigmoid":         newSigmoid,
 	"Sin":             newSin,
+	"Sinh":            newSinh,
 	"Slice":           newSlice,
 	"Squeeze":         newSqueeze,
 	"Sub":             newSub,

ops/opset13/opset13_test.go

@@ -128,6 +128,11 @@ func TestGetOperator(t *testing.T) {
 			newSin(),
 			nil,
 		},
+    {
+      "Sinh",
+			newSinh(),
+      nil,
+    },
 		{
 			"Slice",
 			newSlice(),

ops/opset13/sinh.go

@@ -0,0 +1,75 @@
+package opset13
+
+import (
+	"math"
+
+	"github.com/advancedclimatesystems/gonnx/onnx"
+	"github.com/advancedclimatesystems/gonnx/ops"
+	"gorgonia.org/tensor"
+)
+
+// Sinh represents the ONNX sinh operator.
+type Sinh struct{}
+
+// newSin creates a new sinh operator.
+func newSinh() ops.Operator {
+	return &Sinh{}
+}
+
+// Init initializes the sinh operator.
+func (s *Sinh) Init(_ []*onnx.AttributeProto) error {
+	return nil
+}
+
+// Apply applies the sinh operator.
+func (s *Sinh) 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(sinh[float32])
+	case tensor.Float64:
+		out, err = inputs[0].Apply(sinh[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 *Sinh) 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 *Sinh) GetMinInputs() int {
+	return 1
+}
+
+// GetMaxInputs returns the maximum number of input tensors this operator expects.
+func (s *Sinh) GetMaxInputs() int {
+	return 1
+}
+
+// GetInputTypeConstraints returns a list. Every element represents a set of allowed tensor dtypes
+// for the corresponding input tensor.
+func (s *Sinh) 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 *Sinh) String() string {
+	return "sinh operator"
+}
+
+func sinh[T ops.FloatType](x T) T {
+	return T(math.Sinh(float64(x)))
+}

ops/opset13/sinh_test.go

@@ -0,0 +1,99 @@
+package opset13
+
+import (
+	"testing"
+
+	"github.com/advancedclimatesystems/gonnx/ops"
+	"github.com/stretchr/testify/assert"
+	"gorgonia.org/tensor"
+)
+
+func TestSinhInit(t *testing.T) {
+	s := &Sinh{}
+
+	// since 'sinh' does not have any attributes we pass in nil. This should not
+	// fail initializing the sinh.
+	err := s.Init(nil)
+	assert.Nil(t, err)
+}
+
+func TestSinh(t *testing.T) {
+	tests := []struct {
+		sinh     *Sinh
+		backing  []float32
+		shape    []int
+		expected []float32
+	}{
+		{
+			&Sinh{},
+			[]float32{-2, -1, 0, 1},
+			[]int{2, 2},
+			[]float32{-3.6268604, -1.1752012, 0, 1.1752012},
+		},
+		{
+			&Sinh{},
+			[]float32{1, 3, 4, 5},
+			[]int{1, 4},
+			[]float32{1.1752012, 10.017875, 27.289917, 74.20321},
+		},
+		{
+			&Sinh{},
+			[]float32{-1, -1, -1, -1},
+			[]int{1, 4},
+			[]float32{-1.1752012, -1.1752012, -1.1752012, -1.1752012},
+		},
+	}
+
+	for _, test := range tests {
+		inputs := []tensor.Tensor{
+			ops.TensorWithBackingFixture(test.backing, test.shape...),
+		}
+
+		res, err := test.sinh.Apply(inputs)
+		assert.Nil(t, err)
+
+		assert.Nil(t, err)
+		assert.Equal(t, test.expected, res[0].Data())
+	}
+}
+
+func TestInputValidationSinh(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, &Sinh{}),
+		},
+		{
+			[]tensor.Tensor{
+				ops.TensorWithBackingFixture([]int{1, 2}, 2),
+			},
+			ops.ErrInvalidInputType(0, "int", &Sinh{}),
+		},
+	}
+
+	for _, test := range tests {
+		sinh := &Sinh{}
+		validated, err := sinh.ValidateInputs(test.inputs)
+
+		assert.Equal(t, test.err, err)
+
+		if test.err == nil {
+			assert.Equal(t, test.inputs, validated)
+		}
+	}
+}

ops_test.go

@@ -341,6 +341,8 @@ var expectedTests = []string{
 	"test_sin_example",
 	"test_sigmoid_example",
 	"test_sigmoid",
+	"test_sinh",
+	"test_sinh_example",
 	"test_slice_negative_axes",
 	"test_slice_default_steps",
 	"test_slice",