mirror of
https://github.com/dogkeeper886/ollama37.git
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It is not common to return errors with close/free operations - most people won't check it and even if they did there's probably not much that can do. It's better to not give implementations false expectations.
197 lines
4.3 KiB
Go
197 lines
4.3 KiB
Go
package ml
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import (
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"bytes"
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"encoding/binary"
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"fmt"
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"os"
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"strconv"
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"strings"
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)
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type Config interface {
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Architecture() string
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String(string, ...string) string
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Uint(string, ...uint32) uint32
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Float(string, ...float32) float32
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Strings(string, ...[]string) []string
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Uints(string, ...[]uint32) []uint32
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}
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type Backend interface {
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Config() Config
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Get(name string) Tensor
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NewContext() Context
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}
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var backends = make(map[string]func(*os.File) (Backend, error))
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func RegisterBackend(name string, f func(*os.File) (Backend, error)) {
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if _, ok := backends[name]; ok {
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panic("backend: backend already registered")
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}
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backends[name] = f
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}
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func NewBackend(f *os.File) (Backend, error) {
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if backend, ok := backends["ggml"]; ok {
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return backend(f)
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}
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return nil, fmt.Errorf("unsupported backend")
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}
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type Context interface {
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Zeros(dtype DType, shape ...int) Tensor
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FromFloatSlice(s []float32, shape ...int) (Tensor, error)
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FromIntSlice(s []int32, shape ...int) (Tensor, error)
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Forward(Tensor)
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Compute(Tensor) Tensor
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Close()
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}
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type Tensor interface {
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Dim(n int) int64
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Stride(n int) int64
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Shape() []int64
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DType() DType
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Bytes() []byte
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Floats() []float32
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Add(ctx Context, t2 Tensor) Tensor
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Mul(ctx Context, t2 Tensor) Tensor
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Mulmat(ctx Context, t2 Tensor) Tensor
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Softmax(ctx Context) Tensor
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LayerNorm(ctx Context, weight, bias Tensor, eps float32) Tensor
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RMSNorm(ctx Context, weight Tensor, eps float32) Tensor
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Scale(ctx Context, s float64) Tensor
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Conv2D(ctx Context, weight Tensor, s0, s1, p0, p1, d0, d1 int) Tensor
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RoPE(ctx Context, positionIDs, ropeFactors Tensor, dim uint32, base, scale float32) Tensor
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Tanh(ctx Context) Tensor
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GELU(ctx Context) Tensor
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SILU(ctx Context) Tensor
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Reshape(ctx Context, shape ...int64) Tensor
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View(ctx Context, offset int, shape ...int) Tensor
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Permute(ctx Context, shape ...int) Tensor
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Contiguous(ctx Context) Tensor
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Pad(ctx Context, shape ...int64) Tensor
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Unpad(ctx Context, shape ...int64) Tensor
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Stack(ctx Context, dim int, s ...Tensor) Tensor
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Concat(ctx Context, t2 Tensor, dim int) Tensor
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Rows(ctx Context, t2 Tensor) Tensor
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Copy(ctx Context, t2 Tensor) Tensor
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}
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type number interface {
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~int | ~int8 | ~int16 | ~int32 | ~int64 |
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~uint | ~uint8 | ~uint16 | ~uint32 | ~uint64 |
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~float32 | ~float64 |
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~complex64 | ~complex128
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}
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func mul[T number](s ...T) T {
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p := T(1)
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for _, v := range s {
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p *= v
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}
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return p
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}
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type DumpOptions struct {
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// Items is the number of elements to print at the beginning and end of each dimension.
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Items int64
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// Precision is the number of decimal places to print. Applies to float32 and float64.
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Precision int
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}
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func Dump(t Tensor, opts ...DumpOptions) string {
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if len(opts) < 1 {
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opts = append(opts, DumpOptions{
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Items: 3,
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Precision: 4,
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})
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}
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switch t.DType() {
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case DTypeF32:
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return dump[[]float32](t, opts[0].Items, func(f float32) string {
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return strconv.FormatFloat(float64(f), 'f', opts[0].Precision, 32)
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})
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case DTypeI32:
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return dump[[]int32](t, opts[0].Items, func(i int32) string {
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return strconv.FormatInt(int64(i), 10)
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})
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default:
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return "<unsupported>"
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}
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}
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func dump[S ~[]E, E number](t Tensor, items int64, fn func(E) string) string {
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bts := t.Bytes()
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if bts == nil {
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return "<nil>"
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}
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s := make(S, mul(t.Shape()...))
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if err := binary.Read(bytes.NewBuffer(t.Bytes()), binary.LittleEndian, &s); err != nil {
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panic(err)
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}
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shape := t.Shape()
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var sb strings.Builder
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var f func([]int64, int64)
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f = func(dims []int64, stride int64) {
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prefix := strings.Repeat(" ", len(shape)-len(dims)+1)
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fmt.Fprint(&sb, "[")
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defer func() { fmt.Fprint(&sb, "]") }()
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for i := int64(0); i < dims[0]; i++ {
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if i >= items && i < dims[0]-items {
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fmt.Fprint(&sb, "..., ")
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// skip to next printable element
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skip := dims[0] - 2*items
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if len(dims) > 1 {
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stride += mul(append(dims[1:], skip)...)
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fmt.Fprint(&sb, strings.Repeat("\n", len(dims)-1), prefix)
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}
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i += skip - 1
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} else if len(dims) > 1 {
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f(dims[1:], stride)
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stride += mul(dims[1:]...)
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if i < dims[0]-1 {
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fmt.Fprint(&sb, ",", strings.Repeat("\n", len(dims)-1), prefix)
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}
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} else {
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fmt.Fprint(&sb, fn(s[stride+i]))
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if i < dims[0]-1 {
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fmt.Fprint(&sb, ", ")
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}
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}
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}
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}
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f(shape, 0)
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return sb.String()
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}
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type DType int
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const (
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DTypeF32 DType = iota
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DTypeI32
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DTypeOther
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)
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