commit 2da5bc6ecedda4605aaec66e1e32631044b48874 Author: kingecg Date: Tue Dec 30 22:49:34 2025 +0800 ``` feat: 初始化Go张量库基础实现 - 添加Tensor数据结构定义，包含数据、梯度和反向传播相关字段 - 实现基本张量操作：加法、减法、乘法、矩阵乘法和数乘 - 实现张量创建函数：全零、全一、单位矩阵 - 实现反向传播机制和梯度计算 - 添加.go文件到gitignore以忽略vendor目录 - 配置go模块依赖和版本信息 ``` diff --git a/.gitignore b/.gitignore new file mode 100644 index 0000000..5657f6e --- /dev/null +++ b/.gitignore @@ -0,0 +1 @@ +vendor \ No newline at end of file diff --git a/go.mod b/go.mod new file mode 100644 index 0000000..b7d7b4f --- /dev/null +++ b/go.mod @@ -0,0 +1,5 @@ +module git.kingecg.top/kingecg/gotensor + +go 1.25.1 + +require git.kingecg.top/kingecg/gomatrix v0.0.0-20251230141944-2ff4dcfb0fcd // indirect diff --git a/go.sum b/go.sum new file mode 100644 index 0000000..976f0f5 --- /dev/null +++ b/go.sum @@ -0,0 +1,2 @@ +git.kingecg.top/kingecg/gomatrix v0.0.0-20251230141944-2ff4dcfb0fcd h1:vn3LW38hQPGig0iqofIaIMYXVp3Uqb5QX6eH5B5lVxU= +git.kingecg.top/kingecg/gomatrix v0.0.0-20251230141944-2ff4dcfb0fcd/go.mod h1:CHH1HkVvXrpsb+uDrsoyjx0lTwQ3oSSMbIRJmwvO6z8= diff --git a/tensor.go b/tensor.go new file mode 100644 index 0000000..c80fc54 --- /dev/null +++ b/tensor.go @@ -0,0 +1,303 @@ +package gotensor + +import "git.kingecg.top/kingecg/gomatrix" + +const ( + Max_Prevs = 10 + Max_Args = 10 +) + +type Arg interface { + int | float64 | []int +} + +type Tensor struct { + Data *gomatrix.Matrix + Grad *gomatrix.Matrix + Prevs [Max_Prevs]*Tensor + Num_Prevs int + Args [Max_Args]any // must meet Arg + Op string // 操作类型，用于反向传播 + backwardFunc func() // 反向传播函数 +} + +// NewTensor 创建一个新的Tensor +func NewTensor(data []float64, shape []int) (*Tensor, error) { + matrix, err := gomatrix.NewMatrix(data, shape) + if err != nil { + return nil, err + } + + // 创建梯度矩阵，初始为零 + grad, err := gomatrix.NewZeros(shape) + if err != nil { + return nil, err + } + + return &Tensor{ + Data: matrix, + Grad: grad, + Op: "", + }, nil +} + +// NewZeros 创建一个全零Tensor +func NewZeros(shape []int) (*Tensor, error) { + matrix, err := gomatrix.NewZeros(shape) + if err != nil { + return nil, err + } + + grad, err := gomatrix.NewZeros(shape) + if err != nil { + return nil, err + } + + return &Tensor{ + Data: matrix, + Grad: grad, + Op: "zeros", + }, nil +} + +// NewOnes 创建一个全一Tensor +func NewOnes(shape []int) (*Tensor, error) { + matrix, err := gomatrix.NewOnes(shape) + if err != nil { + return nil, err + } + + grad, err := gomatrix.NewZeros(shape) + if err != nil { + return nil, err + } + + return &Tensor{ + Data: matrix, + Grad: grad, + Op: "ones", + }, nil +} + +// NewIdentity 创建一个单位Tensor（矩阵） +func NewIdentity(size int) (*Tensor, error) { + matrix, err := gomatrix.NewIdentity(size) + if err != nil { + return nil, err + } + + grad, err := gomatrix.NewZeros([]int{size, size}) + if err != nil { + return nil, err + } + + return &Tensor{ + Data: matrix, + Grad: grad, + Op: "identity", + }, nil +} + +// Add Tensor加法 +func (t *Tensor) Add(other *Tensor) (*Tensor, error) { + result, err := t.Data.Add(other.Data) + if err != nil { + return nil, err + } + + // 创建结果Tensor + output := &Tensor{ + Data: result, + Op: "add", + } + + // 记录依赖关系 + output.Prevs[0] = t + output.Prevs[1] = other + output.Num_Prevs = 2 + + // 定义反向传播函数 + output.backwardFunc = func() { + if t.Grad != nil { + // 对t的梯度等于输出梯度 + grad, _ := t.Grad.Add(output.Grad) + t.Grad = grad + } + if other.Grad != nil { + // 对other的梯度等于输出梯度 + grad, _ := other.Grad.Add(output.Grad) + other.Grad = grad + } + } + + return output, nil +} + +// Subtract Tensor减法 +func (t *Tensor) Subtract(other *Tensor) (*Tensor, error) { + result, err := t.Data.Subtract(other.Data) + if err != nil { + return nil, err + } + + output := &Tensor{ + Data: result, + Op: "sub", + } + + output.Prevs[0] = t + output.Prevs[1] = other + output.Num_Prevs = 2 + + output.backwardFunc = func() { + if t.Grad != nil { + // 对t的梯度等于输出梯度 + grad, _ := t.Grad.Add(output.Grad) + t.Grad = grad + } + if other.Grad != nil { + // 对other的梯度等于输出梯度的负值 + negGrad := output.Grad.Scale(-1.0) + grad, _ := other.Grad.Add(negGrad) + other.Grad = grad + } + } + + return output, nil +} + +// Multiply Tensor乘法（逐元素相乘） +func (t *Tensor) Multiply(other *Tensor) (*Tensor, error) { + result, err := t.Data.Multiply(other.Data) + if err != nil { + return nil, err + } + + output := &Tensor{ + Data: result, + Op: "mul", + } + + output.Prevs[0] = t + output.Prevs[1] = other + output.Num_Prevs = 2 + + output.backwardFunc = func() { + if t.Grad != nil { + // 对t的梯度 = output.Grad * other.Data + gradWithOther, _ := output.Grad.Multiply(other.Data) + grad, _ := t.Grad.Add(gradWithOther) + t.Grad = grad + } + if other.Grad != nil { + // 对other的梯度 = output.Grad * t.Data + gradWithT, _ := output.Grad.Multiply(t.Data) + grad, _ := other.Grad.Add(gradWithT) + other.Grad = grad + } + } + + return output, nil +} + +// MatMul Tensor矩阵乘法 +func (t *Tensor) MatMul(other *Tensor) (*Tensor, error) { + result, err := t.Data.MatMul(other.Data) + if err != nil { + return nil, err + } + + output := &Tensor{ + Data: result, + Op: "matmul", + } + + output.Prevs[0] = t + output.Prevs[1] = other + output.Num_Prevs = 2 + + output.backwardFunc = func() { + if t.Grad != nil { + // 对t的梯度 = output.Grad * other.Data^T + otherT, _ := other.Data.Transpose() + gradResult, _ := output.Grad.MatMul(otherT) + grad, _ := t.Grad.Add(gradResult) + t.Grad = grad + } + if other.Grad != nil { + // 对other的梯度 = t.Data^T * output.Grad + tT, _ := t.Data.Transpose() + gradResult, _ := tT.MatMul(output.Grad) + grad, _ := other.Grad.Add(gradResult) + other.Grad = grad + } + } + + return output, nil +} + +// Scale Tensor数乘 +func (t *Tensor) Scale(factor float64) *Tensor { + result := t.Data.Scale(factor) + + output := &Tensor{ + Data: result, + Op: "scale", + } + + output.Prevs[0] = t + output.Num_Prevs = 1 + output.Args[0] = factor + + output.backwardFunc = func() { + if t.Grad != nil { + // 对t的梯度 = output.Grad * factor + scaledGrad := output.Grad.Scale(factor) + grad, _ := t.Grad.Add(scaledGrad) + t.Grad = grad + } + } + + return output +} + +// ZeroGrad 将梯度置零 +func (t *Tensor) ZeroGrad() { + if t.Grad != nil { + shape := t.Grad.Shape() + zeroGrad, _ := gomatrix.NewZeros(shape) + t.Grad = zeroGrad + } +} + +// Shape 返回Tensor的形状 +func (t *Tensor) Shape() []int { + return t.Data.Shape() +} + +// Size 返回Tensor的大小 +func (t *Tensor) Size() int { + return t.Data.Size() +} + +// Get 获取指定位置的值 +func (t *Tensor) Get(indices ...int) (float64, error) { + return t.Data.Get(indices...) +} + +// Set 设置指定位置的值 +func (t *Tensor) Set(value float64, indices ...int) error { + return t.Data.Set(value, indices...) +} + +// String 返回Tensor的字符串表示 +func (t *Tensor) String() string { + return t.Data.String() +} + +// Backward 执行反向传播 +func (t *Tensor) Backward() { + if t.backwardFunc != nil { + t.backwardFunc() + } +} \ No newline at end of file