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op_math_test.go
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op_math_test.go
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package gorgonia
import (
"io/ioutil"
"testing"
"github.com/chewxy/gorgonia/tensor"
"github.com/stretchr/testify/assert"
)
var binOpTests = []struct {
binOp func(*Node, *Node) (*Node, error)
a, b Value
correct Value
correctDerivA Value
correctDerivB Value
correctShape tensor.Shape
}{
{Add,
tensor.New(tensor.WithBacking([]float64{1, 2, 3, 4})),
tensor.New(tensor.WithBacking([]float64{1, 2, 3, 4})),
tensor.New(tensor.WithBacking([]float64{2, 4, 6, 8})),
tensor.New(tensor.WithBacking([]float64{1, 1, 1, 1})),
tensor.New(tensor.WithBacking([]float64{1, 1, 1, 1})),
tensor.Shape{4},
},
{Add,
tensor.New(tensor.WithBacking([]float64{1, 2, 3, 4})),
newF64(1.0),
tensor.New(tensor.WithBacking([]float64{2, 3, 4, 5})),
tensor.New(tensor.WithBacking([]float64{1, 1, 1, 1})),
newF64(4.0),
tensor.Shape{4},
},
{Add,
newF64(1.0),
tensor.New(tensor.WithBacking([]float64{1, 2, 3, 4})),
tensor.New(tensor.WithBacking([]float64{2, 3, 4, 5})),
newF64(4.0),
tensor.New(tensor.WithBacking([]float64{1, 1, 1, 1})),
tensor.Shape{4},
},
{Add,
newF64(1.0),
newF64(1.0),
newF64(2.0),
newF64(1.0),
newF64(1.0),
scalarShape,
},
{Sub,
tensor.New(tensor.WithBacking([]float64{1, 2, 3, 4})),
tensor.New(tensor.WithBacking([]float64{1, 2, 3, 4})),
tensor.New(tensor.WithBacking([]float64{0, 0, 0, 0})),
tensor.New(tensor.WithBacking([]float64{1, 1, 1, 1})),
tensor.New(tensor.WithBacking([]float64{-1, -1, -1, -1})),
tensor.Shape{4},
},
{Sub,
tensor.New(tensor.WithBacking([]float64{1, 2, 3, 4})),
newF64(1.0),
tensor.New(tensor.WithBacking([]float64{0, 1, 2, 3})),
tensor.New(tensor.WithBacking([]float64{1, 1, 1, 1})),
newF64(-4.0),
tensor.Shape{4},
},
{Sub,
newF64(1.0),
tensor.New(tensor.WithBacking([]float64{1, 2, 3, 4})),
tensor.New(tensor.WithBacking([]float64{0, -1, -2, -3})),
newF64(4.0),
tensor.New(tensor.WithBacking([]float64{-1, -1, -1, -1})),
tensor.Shape{4},
},
{Sub,
newF64(1.0),
newF64(1.0),
newF64(0.0),
newF64(1.0),
newF64(-1.0),
scalarShape,
},
{HadamardProd,
tensor.New(tensor.WithBacking([]float64{1, 2, 3, 4})),
tensor.New(tensor.WithBacking([]float64{1, 2, 3, 4})),
tensor.New(tensor.WithBacking([]float64{1, 4, 9, 16})),
tensor.New(tensor.WithBacking([]float64{1, 2, 3, 4})),
tensor.New(tensor.WithBacking([]float64{1, 2, 3, 4})),
tensor.Shape{4},
},
{Mul,
tensor.New(tensor.WithBacking([]float64{1, 2, 3, 4})),
newF64(1.0),
tensor.New(tensor.WithBacking([]float64{1, 2, 3, 4})),
tensor.New(tensor.WithBacking([]float64{1, 1, 1, 1})),
newF64(10),
tensor.Shape{4},
},
{Mul,
newF64(1.0),
tensor.New(tensor.WithBacking([]float64{1, 2, 3, 4})),
tensor.New(tensor.WithBacking([]float64{1, 2, 3, 4})),
newF64(10),
tensor.New(tensor.WithBacking([]float64{1, 1, 1, 1})),
tensor.Shape{4},
},
{Mul,
newF64(1.0),
newF64(1.0),
newF64(1.0),
newF64(1.0),
newF64(1.0),
scalarShape,
},
{HadamardDiv,
tensor.New(tensor.WithBacking([]float64{1, 2, 3, 4})),
tensor.New(tensor.WithBacking([]float64{1, 1, 1, 1})),
tensor.New(tensor.WithBacking([]float64{1, 2, 3, 4})),
tensor.New(tensor.WithBacking([]float64{1, 1, 1, 1})),
tensor.New(tensor.WithBacking([]float64{-1, -2, -3, -4})),
tensor.Shape{4},
},
{Div,
tensor.New(tensor.WithBacking([]float64{1, 2, 3, 4})),
newF64(1.0),
tensor.New(tensor.WithBacking([]float64{1, 2, 3, 4})),
tensor.New(tensor.WithBacking([]float64{1, 1, 1, 1})),
newF64(-10),
tensor.Shape{4},
},
{Div,
newF64(1),
tensor.New(tensor.WithBacking([]float64{1, 1, 1, 1})),
tensor.New(tensor.WithBacking([]float64{1, 1, 1, 1})),
newF64(4),
tensor.New(tensor.WithBacking([]float64{-1, -1, -1, -1})),
tensor.Shape{4},
},
{Div,
newF64(1.0),
newF64(1.0),
newF64(1.0),
newF64(1.0),
newF64(-1.0),
scalarShape,
},
// Float32
{Add,
tensor.New(tensor.WithBacking([]float32{1, 2, 3, 4})),
tensor.New(tensor.WithBacking([]float32{1, 2, 3, 4})),
tensor.New(tensor.WithBacking([]float32{2, 4, 6, 8})),
tensor.New(tensor.WithBacking([]float32{1, 1, 1, 1})),
tensor.New(tensor.WithBacking([]float32{1, 1, 1, 1})),
tensor.Shape{4},
},
{Add,
tensor.New(tensor.WithBacking([]float32{1, 2, 3, 4})),
newF32(1.0),
tensor.New(tensor.WithBacking([]float32{2, 3, 4, 5})),
tensor.New(tensor.WithBacking([]float32{1, 1, 1, 1})),
newF32(4.0),
tensor.Shape{4},
},
{Add,
newF32(1.0),
tensor.New(tensor.WithBacking([]float32{1, 2, 3, 4})),
tensor.New(tensor.WithBacking([]float32{2, 3, 4, 5})),
newF32(4.0),
tensor.New(tensor.WithBacking([]float32{1, 1, 1, 1})),
tensor.Shape{4},
},
{Add,
newF32(1.0),
newF32(1.0),
newF32(2.0),
newF32(1.0),
newF32(1.0),
scalarShape,
},
{Sub,
tensor.New(tensor.WithBacking([]float32{1, 2, 3, 4})),
tensor.New(tensor.WithBacking([]float32{1, 2, 3, 4})),
tensor.New(tensor.WithBacking([]float32{0, 0, 0, 0})),
tensor.New(tensor.WithBacking([]float32{1, 1, 1, 1})),
tensor.New(tensor.WithBacking([]float32{-1, -1, -1, -1})),
tensor.Shape{4},
},
{Sub,
tensor.New(tensor.WithBacking([]float32{1, 2, 3, 4})),
newF32(1.0),
tensor.New(tensor.WithBacking([]float32{0, 1, 2, 3})),
tensor.New(tensor.WithBacking([]float32{1, 1, 1, 1})),
newF32(-4.0),
tensor.Shape{4},
},
{Sub,
newF32(1.0),
tensor.New(tensor.WithBacking([]float32{1, 2, 3, 4})),
tensor.New(tensor.WithBacking([]float32{0, -1, -2, -3})),
newF32(4.0),
tensor.New(tensor.WithBacking([]float32{-1, -1, -1, -1})),
tensor.Shape{4},
},
{Sub,
newF32(1.0),
newF32(1.0),
newF32(0.0),
newF32(1.0),
newF32(-1.0),
scalarShape,
},
{HadamardProd,
tensor.New(tensor.WithBacking([]float32{1, 2, 3, 4})),
tensor.New(tensor.WithBacking([]float32{1, 2, 3, 4})),
tensor.New(tensor.WithBacking([]float32{1, 4, 9, 16})),
tensor.New(tensor.WithBacking([]float32{1, 2, 3, 4})),
tensor.New(tensor.WithBacking([]float32{1, 2, 3, 4})),
tensor.Shape{4},
},
{Mul,
tensor.New(tensor.WithBacking([]float32{1, 2, 3, 4})),
newF32(1.0),
tensor.New(tensor.WithBacking([]float32{1, 2, 3, 4})),
tensor.New(tensor.WithBacking([]float32{1, 1, 1, 1})),
newF32(10),
tensor.Shape{4},
},
{Mul,
newF32(1.0),
tensor.New(tensor.WithBacking([]float32{1, 2, 3, 4})),
tensor.New(tensor.WithBacking([]float32{1, 2, 3, 4})),
newF32(10),
tensor.New(tensor.WithBacking([]float32{1, 1, 1, 1})),
tensor.Shape{4},
},
{Mul,
newF32(1.0),
newF32(1.0),
newF32(1.0),
newF32(1.0),
newF32(1.0),
scalarShape,
},
{HadamardDiv,
tensor.New(tensor.WithBacking([]float32{1, 2, 3, 4})),
tensor.New(tensor.WithBacking([]float32{1, 1, 1, 1})),
tensor.New(tensor.WithBacking([]float32{1, 2, 3, 4})),
tensor.New(tensor.WithBacking([]float32{1, 1, 1, 1})),
tensor.New(tensor.WithBacking([]float32{-1, -2, -3, -4})),
tensor.Shape{4},
},
{Div,
tensor.New(tensor.WithBacking([]float32{1, 2, 3, 4})),
newF32(1.0),
tensor.New(tensor.WithBacking([]float32{1, 2, 3, 4})),
tensor.New(tensor.WithBacking([]float32{1, 1, 1, 1})),
newF32(-10),
tensor.Shape{4},
},
{Div,
newF32(1),
tensor.New(tensor.WithBacking([]float32{1, 1, 1, 1})),
tensor.New(tensor.WithBacking([]float32{1, 1, 1, 1})),
newF32(4),
tensor.New(tensor.WithBacking([]float32{-1, -1, -1, -1})),
tensor.Shape{4},
},
{Div,
newF32(1.0),
newF32(1.0),
newF32(1.0),
newF32(1.0),
newF32(-1.0),
scalarShape,
},
}
func TestBasicArithmetic(t *testing.T) {
assert := assert.New(t)
for i, bot := range binOpTests {
g := NewGraph()
xV, _ := CloneValue(bot.a)
yV, _ := CloneValue(bot.b)
x := NodeFromAny(g, xV, WithName("x"))
y := NodeFromAny(g, yV, WithName("y"))
var ret *Node
var err error
if ret, err = bot.binOp(x, y); err != nil {
t.Errorf("Test %d: %v", i, err)
continue
}
cost := Must(Sum(ret))
var grads Nodes
if grads, err = Grad(cost, x, y); err != nil {
t.Errorf("Test %d: error while symbolic op: %v", i, err)
continue
}
prog, locMap, err := Compile(g)
// t.Log(prog)
// t.Log(locMap)
if err != nil {
t.Errorf("Test %d: error while compiling: %v", i, err)
continue
}
// logger := log.New(os.Stderr, "", 0)
// m1 := NewTapeMachine(prog, locMap, WithLogger(logger), WithWatchlist())
m1 := NewTapeMachine(prog, locMap, TraceExec())
if err = m1.RunAll(); err != nil {
t.Errorf("Test %d: error while running %v", i, err)
continue
}
ioutil.WriteFile("add.dot", []byte(g.ToDot()), 0644)
assert.Equal(bot.correct.Data(), ret.Value().Data())
assert.True(bot.correctShape.Eq(ret.Shape()))
assert.Equal(2, len(grads))
assert.Equal(bot.correctDerivA.Data(), grads[0].Value().Data(), "Test %v", i)
assert.Equal(bot.correctDerivB.Data(), grads[1].Value().Data())
}
}