Files
ollama37/model/model.go
Jesse Gross ed443a0393 Runner for Ollama engine
This provides integration with the new Ollama engine
(5824541 next ollama runner (#7913)) and the rest of the Ollama
infrastructure such as the runner and Ollama server.

In addition, it also builds out the KV cache infrastructure to
support requirements of how Ollama runs models such as:
 - Parallel processing
 - Memory management for defragmentation and shifting
 - Multi-modal modals

Both old and new engines continue to be supported. By default, only
the old engine is used. To enable the new engine:

Start the server with the OLLAMA_NEW_ENGINE environment variable set:
OLLAMA_NEW_ENGINE=1 ./ollama serve

Start a model that is supported by the Ollama engine. This one is Llama 3.1 8b Q4_K_M:
./ollama run jessegross/llama3.1
2025-02-13 17:09:26 -08:00

250 lines
4.8 KiB
Go

package model
import (
"errors"
"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/kvcache"
"github.com/ollama/ollama/ml"
_ "github.com/ollama/ollama/ml/backend"
)
type Options struct {
Inputs []int32
Positions []int32
Sequences []int
Outputs []int32
Images []image.Image
}
type config struct {
Cache kvcache.Cache
}
type Base struct {
b ml.Backend
config
}
func (m *Base) Backend() ml.Backend {
return m.b
}
func (m *Base) Config() config {
return m.config
}
type Model interface {
Forward(ml.Context, Options) (ml.Tensor, error)
Backend() ml.Backend
Config() config
}
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
}
base := Base{b: b, config: m.Config()}
v := reflect.ValueOf(m)
v.Elem().Set(populateFields(base, v.Elem()))
return m, nil
}
func populateFields(base Base, v reflect.Value, tags ...Tag) reflect.Value {
t := v.Type()
if t.Kind() == reflect.Struct {
allNil := true
for i := range t.NumField() {
tt := t.Field(i).Type
vv := v.Field(i)
if !vv.CanSet() {
continue
}
// make a copy
tagsCopy := tags
if tag := t.Field(i).Tag.Get("gguf"); tag != "" {
tagsCopy = append(tagsCopy, ParseTags(tag))
}
if tt == reflect.TypeOf((*Base)(nil)).Elem() {
vv.Set(reflect.ValueOf(base))
} else if tt == reflect.TypeOf((*ml.Tensor)(nil)).Elem() {
var fn func([]Tag) [][]string
fn = func(tags []Tag) (values [][]string) {
if len(tags) < 1 {
return nil
}
values = [][]string{{tags[0].Name}}
for _, alt := range tags[0].Alternate {
values = append(values, []string{alt})
}
for i, value := range values {
for _, rest := range fn(tags[1:]) {
value = append(value, rest...)
}
values[i] = value
}
return values
}
names := fn(tagsCopy)
for _, name := range names {
if tensor := base.Backend().Get(strings.Join(name, ".")); tensor != nil {
slog.Debug("found tensor", "", tensor)
vv.Set(reflect.ValueOf(tensor))
break
}
}
} else if tt.Kind() == reflect.Pointer || tt.Kind() == reflect.Interface {
setPointer(base, vv, tagsCopy)
} else if tt.Kind() == reflect.Slice || tt.Kind() == reflect.Array {
for i := range vv.Len() {
vvv := vv.Index(i)
if vvv.Kind() == reflect.Pointer || vvv.Kind() == reflect.Interface {
setPointer(base, vvv, append(tagsCopy, Tag{Name: strconv.Itoa(i)}))
} else {
vvv.Set(populateFields(base, vvv, append(tagsCopy, Tag{Name: strconv.Itoa(i)})...))
}
}
}
if !canNil(tt) || !vv.IsNil() {
allNil = false
}
}
if allNil {
return reflect.Zero(t)
}
}
return v
}
func setPointer(base Base, v reflect.Value, tags []Tag) {
vv := v
if v.Kind() == reflect.Interface {
if v.IsNil() {
return
}
vv = vv.Elem()
}
vv = vv.Elem()
if v.IsNil() {
vv = reflect.New(v.Type().Elem()).Elem()
}
if f := populateFields(base, vv, tags...); f.CanAddr() {
v.Set(f.Addr())
}
}
type Tag struct {
Name string
Alternate []string
}
func ParseTags(s string) (tag Tag) {
parts := strings.Split(s, ",")
if len(parts) > 0 {
tag.Name = parts[0]
for _, part := range parts[1:] {
if value, ok := strings.CutPrefix(part, "alt:"); ok {
tag.Alternate = append(tag.Alternate, value)
}
}
}
return
}
func canNil(t reflect.Type) bool {
return t.Kind() == reflect.Chan ||
t.Kind() == reflect.Func ||
t.Kind() == reflect.Interface ||
t.Kind() == reflect.Map ||
t.Kind() == reflect.Pointer ||
t.Kind() == reflect.Slice
}
func Forward(ctx ml.Context, m Model, opts Options) (ml.Tensor, error) {
if len(opts.Positions) != len(opts.Sequences) {
return nil, fmt.Errorf("length of positions (%v) must match length of seqs (%v)", len(opts.Positions), len(opts.Sequences))
}
if len(opts.Positions) < 1 {
return nil, errors.New("batch size cannot be less than 1")
}
cache := m.Config().Cache
if cache != nil {
err := cache.StartForward(ctx, opts.Positions, opts.Sequences)
if err != nil {
return nil, err
}
}
t, err := m.Forward(ctx, opts)
if err != nil {
return nil, err
}
ctx.Forward(t)
ctx.Compute(t)
return t, nil
}