157 lines
3.6 KiB
Go
157 lines
3.6 KiB
Go
package gotensor
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import (
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"testing"
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"math"
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)
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// TestSGD 测试SGD优化器
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func TestSGD(t *testing.T) {
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// 创建一些参数用于测试
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weightData, _ := NewMatrix([][]float64{{1.0, 2.0}, {3.0, 4.0}})
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weightGrad, _ := NewMatrix([][]float64{{0.1, 0.2}, {0.3, 0.4}})
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params := []*Tensor{
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{
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Data: Must(NewVector([]float64{1.0, 2.0, 3.0})),
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Grad: Must(NewVector([]float64{0.1, 0.2, 0.3})),
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},
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{
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Data: weightData,
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Grad: weightGrad,
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},
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}
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// 创建SGD优化器
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lr := 0.1
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sgd := NewSGD(params, lr)
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// 保存原始参数值
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origVec0, _ := params[0].Data.Get(0)
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origMat00, _ := params[1].Data.Get(0, 0)
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// 执行一步优化
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sgd.Step()
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// 检查参数是否已更新
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newVec0, _ := params[0].Data.Get(0)
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newMat00, _ := params[1].Data.Get(0, 0)
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expectedVec0 := origVec0 - lr*0.1
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expectedMat00 := origMat00 - lr*0.1
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if math.Abs(newVec0-expectedVec0) > 1e-9 {
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t.Errorf("Expected updated param[0][0] to be %v, got %v", expectedVec0, newVec0)
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}
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if math.Abs(newMat00-expectedMat00) > 1e-9 {
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t.Errorf("Expected updated param[1][0,0] to be %v, got %v", expectedMat00, newMat00)
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}
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// 测试ZeroGrad
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sgd.ZeroGrad()
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for _, param := range params {
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shape := param.Shape()
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for i := 0; i < param.Size(); i++ {
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var gradVal float64
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if len(shape) == 1 {
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gradVal, _ = param.Grad.Get(i)
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} else if len(shape) == 2 {
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cols := shape[1]
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gradVal, _ = param.Grad.Get(i/cols, i%cols)
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}
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if math.Abs(gradVal) > 1e-9 {
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t.Errorf("Expected gradient to be zero after ZeroGrad, got %v", gradVal)
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}
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}
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}
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}
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// TestAdam 测试Adam优化器
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func TestAdam(t *testing.T) {
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// 创建一些参数用于测试
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params := []*Tensor{
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{
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Data: Must(NewVector([]float64{1.0, 2.0})),
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Grad: Must(NewVector([]float64{0.1, 0.2})),
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},
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}
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// 创建Adam优化器
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lr := 0.001
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beta1 := 0.9
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beta2 := 0.999
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epsilon := 1e-8
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adam := NewAdam(params, lr, beta1, beta2, epsilon)
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// 保存原始参数值
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origVec0, _ := params[0].Data.Get(0)
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// 执行几步优化
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for i := 0; i < 3; i++ {
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adam.Step()
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}
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// 检查参数是否已更新
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newVec0, _ := params[0].Data.Get(0)
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if math.Abs(newVec0-origVec0) < 1e-9 {
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t.Errorf("Expected parameter to be updated, but it wasn't. Original: %v, New: %v", origVec0, newVec0)
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}
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// 验证内部状态是否已创建
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if len(adam.M) != len(params) || len(adam.V) != len(params) {
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t.Error("Adam internal states M and V not properly initialized")
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}
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// 测试ZeroGrad
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adam.ZeroGrad()
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for _, param := range params {
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shape := param.Shape()
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for i := 0; i < param.Size(); i++ {
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var gradVal float64
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if len(shape) == 1 {
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gradVal, _ = param.Grad.Get(i)
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} else if len(shape) == 2 {
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cols := shape[1]
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gradVal, _ = param.Grad.Get(i/cols, i%cols)
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}
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if math.Abs(gradVal) > 1e-9 {
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t.Errorf("Expected gradient to be zero after ZeroGrad, got %v", gradVal)
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}
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}
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}
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}
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// TestAdamWithMatrix 测试Adam优化器处理矩阵参数
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func TestAdamWithMatrix(t *testing.T) {
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matrixData, _ := NewMatrix([][]float64{{1.0, 2.0}, {3.0, 4.0}})
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matrixGrad, _ := NewMatrix([][]float64{{0.1, 0.2}, {0.3, 0.4}})
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// 创建矩阵参数用于测试
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params := []*Tensor{
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{
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Data: matrixData,
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Grad: matrixGrad,
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},
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}
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// 创建Adam优化器
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lr := 0.001
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adam := NewAdam(params, lr, 0.9, 0.999, 1e-8)
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// 保存原始参数值
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origMat00, _ := params[0].Data.Get(0, 0)
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// 执行几步优化
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for i := 0; i < 5; i++ {
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adam.Step()
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}
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// 检查参数是否已更新
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newMat00, _ := params[0].Data.Get(0, 0)
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if math.Abs(newMat00-origMat00) < 1e-9 {
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t.Errorf("Expected parameter to be updated, but it wasn't. Original: %v, New: %v", origMat00, newMat00)
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}
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} |