ollama/llm/ggla.go
2024-03-08 15:46:25 -08:00

152 lines
2.8 KiB
Go

package llm
import (
"encoding/binary"
"errors"
"io"
"slices"
)
type ContainerGGLA struct {
version uint32
}
func (c *ContainerGGLA) Name() string {
return "ggla"
}
func (c *ContainerGGLA) Decode(rso *readSeekOffset) (model, error) {
binary.Read(rso, binary.LittleEndian, &c.version)
switch c.version {
case 1:
default:
return nil, errors.New("invalid version")
}
model := newModelGGLA(c)
err := model.decode(rso)
return model, err
}
type ModelGGLA struct {
*ContainerGGLA
kv KV
tensors []Tensor
}
func newModelGGLA(container *ContainerGGLA) *ModelGGLA {
return &ModelGGLA{
ContainerGGLA: container,
kv: make(KV),
}
}
func (m *ModelGGLA) decode(rso *readSeekOffset) error {
var r uint32
if err := binary.Read(rso, binary.LittleEndian, &r); err != nil {
return err
}
m.kv["r"] = r
var alpha uint32
if err := binary.Read(rso, binary.LittleEndian, &alpha); err != nil {
return err
}
m.kv["alpha"] = alpha
for {
var dims uint32
if err := binary.Read(rso, binary.LittleEndian, &dims); err != nil {
return err
}
var namesize uint32
if err := binary.Read(rso, binary.LittleEndian, &namesize); err != nil {
return err
}
var t Tensor
if err := binary.Read(rso, binary.LittleEndian, &t.Kind); err != nil {
return err
}
t.Shape = make([]uint64, dims)
for i := 0; uint32(i) < dims; i++ {
var shape32 uint32
if err := binary.Read(rso, binary.LittleEndian, &shape32); err != nil {
return err
}
t.Shape[i] = uint64(shape32)
}
// ggla tensor shape is reversed
// ref: https://github.com/ggerganov/llama.cpp/blob/29ae62d2ae163e2b68aa0ad3bf2ab4636de0c957/convert-lora-to-ggml.py#L44
slices.Reverse(t.Shape)
name := make([]byte, namesize)
if err := binary.Read(rso, binary.LittleEndian, &name); err != nil {
return err
}
t.Name = string(name)
if _, err := rso.Seek((rso.offset+31)&-32, io.SeekStart); err != nil {
return err
}
t.Offset = uint64(rso.offset)
if _, err := rso.Seek(int64(t.Size()), io.SeekCurrent); err != nil {
return err
}
m.tensors = append(m.tensors, t)
}
}
func (m *ModelGGLA) KV() KV {
return m.kv
}
func (m *ModelGGLA) Tensor() []Tensor {
return m.tensors
}
func (*ModelGGLA) ModelFamily() string {
return "ggla"
}
func (*ModelGGLA) ModelType() string {
panic("not implemented")
}
func (*ModelGGLA) FileType() string {
panic("not implemented")
}
func (*ModelGGLA) NumLayers() uint32 {
panic("not implemented")
}
func (*ModelGGLA) NumGQA() uint32 {
panic("not implemented")
}
func (*ModelGGLA) NumEmbed() uint32 {
panic("not implemented")
}
func (*ModelGGLA) NumHead() uint32 {
panic("not implemented")
}
func (*ModelGGLA) NumHeadKv() uint32 {
panic("not implemented")
}
func (*ModelGGLA) NumCtx() uint32 {
panic("not implemented")
}