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- package model
- import (
- "fmt"
- "image"
- _ "image/jpeg"
- _ "image/png"
- "log/slog"
- "os"
- "reflect"
- "strconv"
- "strings"
- _ "golang.org/x/image/bmp"
- _ "golang.org/x/image/tiff"
- _ "golang.org/x/image/webp"
- "github.com/ollama/ollama/cache"
- "github.com/ollama/ollama/ml"
- _ "github.com/ollama/ollama/ml/backend"
- )
- type Cache struct {
- cache.Cache
- cache.Options
- }
- func (c Cache) Sub(i int) Cache {
- if c.Cache != nil {
- return Cache{
- Cache: c.Cache.Sub(i),
- Options: c.Options,
- }
- }
- return c
- }
- func (c Cache) Put(ctx ml.Context, key, value ml.Tensor, opts cache.Options) (ml.Tensor, ml.Tensor) {
- if c.Cache != nil {
- return c.Cache.Put(ctx, key, value, opts)
- }
- return key, value
- }
- type Options struct {
- inputs []int32
- Offset int
- Images []image.Image
- Cache
- }
- func (opts Options) Inputs() []int32 {
- return opts.inputs[opts.Offset:]
- }
- func (opts Options) Positions() []int32 {
- positions := make([]int32, len(opts.inputs)-opts.Offset)
- for i := range positions {
- positions[i] = int32(opts.Offset + i)
- }
- return positions
- }
- type OptionsFunc func(Model, *Options)
- func WithInputIDs(ids []int32) OptionsFunc {
- return func(m Model, opts *Options) {
- opts.inputs = ids
- }
- }
- func WithOffset(offset int) OptionsFunc {
- return func(m Model, opts *Options) {
- opts.Offset = offset
- opts.Cache.Position = offset
- }
- }
- func WithImage(img image.Image) OptionsFunc {
- return func(m Model, opts *Options) {
- opts.Images = append(opts.Images, img)
- }
- }
- func WithCache(c cache.Cache) OptionsFunc {
- return func(m Model, opts *Options) {
- opts.Cache = Cache{
- Cache: c,
- Options: cache.Options{
- Position: opts.Offset,
- },
- }
- }
- }
- type Base struct {
- b ml.Backend
- }
- func (m *Base) Backend() ml.Backend {
- return m.b
- }
- func (m *Base) SetBackend(b ml.Backend) {
- m.b = b
- }
- type Model interface {
- Forward(ml.Context, Options) (ml.Tensor, error)
- Backend() ml.Backend
- SetBackend(ml.Backend)
- }
- var models = make(map[string]func(ml.Config) (Model, error))
- func Register(name string, f func(ml.Config) (Model, error)) {
- if _, ok := models[name]; ok {
- panic("model: model already registered")
- }
- models[name] = f
- }
- func New(s string) (Model, error) {
- r, err := os.Open(s)
- if err != nil {
- return nil, err
- }
- defer r.Close()
- b, err := ml.NewBackend(r)
- if err != nil {
- return nil, err
- }
- arch := b.Config().Architecture()
- f, ok := models[arch]
- if !ok {
- return nil, fmt.Errorf("unsupported model architecture %q", arch)
- }
- m, err := f(b.Config())
- if err != nil {
- return nil, err
- }
- if err := loadTensors(b, m); err != nil {
- return nil, err
- }
- m.SetBackend(b)
- return m, nil
- }
- var mlTensorType = reflect.TypeOf((*ml.Tensor)(nil)).Elem()
- func loadTensors(b ml.Backend, m any, tensorPath ...string) error {
- t := reflect.TypeOf(m)
- v := reflect.ValueOf(m)
- if t.Kind() == reflect.Pointer {
- t = t.Elem()
- v = v.Elem()
- }
- if t.Kind() == reflect.Interface {
- return loadTensors(b, v.Interface(), tensorPath...)
- }
- for i := range t.NumField() {
- f := v.Field(i)
- fullTensorPath := tensorPath
- if tag := t.Field(i).Tag.Get("ggml"); tag != "" {
- tensorName, _, _ := strings.Cut(tag, ",")
- fullTensorPath = append(tensorPath, tensorName)
- }
- if !f.CanSet() {
- continue
- }
- if f.Kind() == reflect.Ptr && f.IsNil() {
- f.Set(reflect.New(f.Type().Elem()))
- } else if f.Kind() == reflect.Interface && f.IsNil() && f.Type().Implements(mlTensorType) {
- if tensor := b.Get(strings.Join(fullTensorPath, ".")); tensor != nil {
- f.Set(reflect.ValueOf(tensor))
- slog.Debug("loaded tensor", "kind", f.Elem().Type(), "", f.Interface())
- }
- }
- if r := reflect.Indirect(f); r.Kind() == reflect.Struct {
- if err := loadTensors(b, f.Interface(), fullTensorPath...); err != nil {
- return err
- }
- } else if r.Kind() == reflect.Slice {
- for i := range r.Len() {
- if err := loadTensors(b, f.Index(i).Addr().Interface(), append(fullTensorPath, strconv.Itoa(i))...); err != nil {
- return err
- }
- }
- }
- }
- return nil
- }
- func Forward(m Model, optsFuncs ...OptionsFunc) (ml.Tensor, error) {
- var opts Options
- for _, optsFunc := range optsFuncs {
- optsFunc(m, &opts)
- }
- ctx := m.Backend().NewContext()
- t, err := m.Forward(ctx, opts)
- if err != nil {
- return nil, err
- }
- defer ctx.Close()
- return ctx.Compute(t), nil
- }
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