515 lines
9.5 KiB
Go
515 lines
9.5 KiB
Go
package llm
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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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"io"
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"github.com/jmorganca/ollama/format"
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)
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type containerGGUF struct {
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bo binary.ByteOrder
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Version uint32
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V1 struct {
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NumTensor uint32
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NumKV uint32
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}
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V2 struct {
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NumTensor uint64
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NumKV uint64
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}
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}
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func (c *containerGGUF) Name() string {
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return "gguf"
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}
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func (c *containerGGUF) Decode(rso *readSeekOffset) (model, error) {
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binary.Read(rso, c.bo, &c.Version)
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switch c.Version {
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case 1:
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binary.Read(rso, c.bo, &c.V1)
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default:
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binary.Read(rso, c.bo, &c.V2)
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}
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model := newGGUFModel(c)
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if err := model.Decode(rso); err != nil {
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return nil, err
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}
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return model, nil
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}
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const (
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ggufTypeUint8 uint32 = iota
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ggufTypeInt8
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ggufTypeUint16
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ggufTypeInt16
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ggufTypeUint32
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ggufTypeInt32
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ggufTypeFloat32
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ggufTypeBool
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ggufTypeString
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ggufTypeArray
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ggufTypeUint64
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ggufTypeInt64
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ggufTypeFloat64
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)
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type kv map[string]any
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type tensor struct {
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name string
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kind uint32
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offset uint64
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// shape is the number of elements in each dimension
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shape [4]uint64
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}
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func (t tensor) blockSize() uint64 {
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switch {
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case t.kind < 2:
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return 1
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case t.kind < 10:
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return 32
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default:
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return 256
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}
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}
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func (t tensor) typeSize() uint64 {
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blockSize := t.blockSize()
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switch t.kind {
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case 0: // FP32
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return 4
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case 1: // FP16
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return 2
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case 2: // Q4_0
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return 2 + blockSize/2
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case 3: // Q4_1
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return 2 + 2 + blockSize/2
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case 6: // Q5_0
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return 2 + 4 + blockSize/2
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case 7: // Q5_1
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return 2 + 2 + 4 + blockSize/2
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case 8: // Q8_0
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return 2 + blockSize
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case 9: // Q8_1
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return 4 + 4 + blockSize
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case 10: // Q2_K
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return blockSize/16 + blockSize/4 + 2 + 2
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case 11: // Q3_K
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return blockSize/8 + blockSize/4 + 12 + 2
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case 12: // Q4_K
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return 2 + 2 + 12 + blockSize/2
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case 13: // Q5_K
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return 2 + 2 + 12 + blockSize/8 + blockSize/2
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case 14: // Q6_K
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return blockSize/2 + blockSize/4 + blockSize/16 + 2
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default:
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return 0
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}
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}
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func (t tensor) parameters() uint64 {
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return t.shape[0] * t.shape[1] * t.shape[2] * t.shape[3]
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}
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func (t tensor) size() uint64 {
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return t.parameters() * t.typeSize() / t.blockSize()
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}
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type ggufModel struct {
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*containerGGUF
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kv
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tensors []tensor
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parameters uint64
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}
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func newGGUFModel(container *containerGGUF) *ggufModel {
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return &ggufModel{
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containerGGUF: container,
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kv: make(kv),
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}
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}
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func (llm *ggufModel) NumTensor() uint64 {
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if llm.Version == 1 {
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return uint64(llm.V1.NumTensor)
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}
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return llm.V2.NumTensor
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}
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func (llm *ggufModel) NumKV() uint64 {
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if llm.Version == 1 {
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return uint64(llm.V1.NumKV)
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}
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return llm.V2.NumKV
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}
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func (llm *ggufModel) ModelFamily() string {
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if t, ok := llm.kv["general.architecture"].(string); ok {
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return t
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}
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return "unknown"
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}
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func (llm *ggufModel) ModelType() string {
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if llm.parameters > 0 {
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return format.HumanNumber(llm.parameters)
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}
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return "unknown"
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}
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func (llm *ggufModel) FileType() string {
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if t, ok := llm.kv["general.file_type"].(uint32); ok {
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return fileType(t)
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}
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return "unknown"
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}
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func (llm *ggufModel) Decode(rso *readSeekOffset) error {
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// decode key-values
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for i := 0; uint64(i) < llm.NumKV(); i++ {
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k, err := llm.readString(rso)
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if err != nil {
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return err
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}
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vtype := llm.readU32(rso)
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var v any
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switch vtype {
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case ggufTypeUint8:
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v = llm.readU8(rso)
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case ggufTypeInt8:
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v = llm.readI8(rso)
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case ggufTypeUint16:
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v = llm.readU16(rso)
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case ggufTypeInt16:
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v = llm.readI16(rso)
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case ggufTypeUint32:
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v = llm.readU32(rso)
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case ggufTypeInt32:
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v = llm.readI32(rso)
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case ggufTypeUint64:
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v = llm.readU64(rso)
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case ggufTypeInt64:
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v = llm.readI64(rso)
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case ggufTypeFloat32:
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v = llm.readF32(rso)
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case ggufTypeFloat64:
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v = llm.readF64(rso)
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case ggufTypeBool:
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v = llm.readBool(rso)
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case ggufTypeString:
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s, err := llm.readString(rso)
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if err != nil {
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return err
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}
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v = s
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case ggufTypeArray:
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a, err := llm.readArray(rso)
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if err != nil {
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return err
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}
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v = a
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default:
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return fmt.Errorf("invalid type: %d", vtype)
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}
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llm.kv[k] = v
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}
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// decode tensors
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for i := 0; uint64(i) < llm.NumTensor(); i++ {
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name, err := llm.readString(rso)
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if err != nil {
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return err
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}
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// dims is the number of dimensions in the tensor
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dims := llm.readU32(rso)
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shape := [4]uint64{1, 1, 1, 1}
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for i := 0; uint32(i) < dims; i++ {
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shape[i] = llm.readU64(rso)
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}
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tensor := tensor{
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name: name,
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kind: llm.readU32(rso),
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offset: llm.readU64(rso),
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shape: shape,
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}
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llm.tensors = append(llm.tensors, tensor)
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llm.parameters += tensor.parameters()
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}
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alignment, ok := llm.kv["general.alignment"].(uint32)
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if !ok {
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alignment = 32
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}
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rso.Seek(int64(alignment)-rso.offset%int64(alignment), io.SeekCurrent)
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for _, tensor := range llm.tensors {
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padded := (int64(tensor.size()) + int64(alignment) - 1) & ^(int64(alignment) - 1)
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rso.Seek(padded, io.SeekCurrent)
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}
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return nil
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}
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func (llm *ggufModel) NumLayers() uint32 {
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value, exists := llm.kv[fmt.Sprintf("%s.block_count", llm.ModelFamily())]
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if !exists {
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return 0
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}
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return value.(uint32)
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}
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func (llm *ggufModel) NumHead() uint32 {
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value, exists := llm.kv[fmt.Sprintf("%s.attention.head_count", llm.ModelFamily())]
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if !exists {
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return 0
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}
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return value.(uint32)
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}
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func (llm *ggufModel) NumEmbed() uint32 {
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value, exists := llm.kv[fmt.Sprintf("%s.embedding_length", llm.ModelFamily())]
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if !exists {
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return 0
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}
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return value.(uint32)
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}
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func (llm *ggufModel) NumHeadKv() uint32 {
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value, exists := llm.kv[fmt.Sprintf("%s.attention.head_count_kv", llm.ModelFamily())]
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if !exists {
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return 0
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}
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return value.(uint32)
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}
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func (llm *ggufModel) NumCtx() uint32 {
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value, exists := llm.kv[fmt.Sprintf("%s.context_length", llm.ModelFamily())]
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if !exists {
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return 0
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}
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return value.(uint32)
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}
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func (llm *ggufModel) NumGQA() uint32 {
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numHeadKv := llm.NumHeadKv()
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if numHeadKv == 0 {
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return 0
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}
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return llm.NumHead() / numHeadKv
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}
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func (llm ggufModel) readU8(r io.Reader) uint8 {
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var u8 uint8
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binary.Read(r, llm.bo, &u8)
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return u8
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}
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func (llm ggufModel) readI8(r io.Reader) int8 {
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var i8 int8
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binary.Read(r, llm.bo, &i8)
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return i8
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}
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func (llm ggufModel) readU16(r io.Reader) uint16 {
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var u16 uint16
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binary.Read(r, llm.bo, &u16)
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return u16
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}
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func (llm ggufModel) readI16(r io.Reader) int16 {
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var i16 int16
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binary.Read(r, llm.bo, &i16)
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return i16
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}
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func (llm ggufModel) readU32(r io.Reader) uint32 {
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var u32 uint32
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binary.Read(r, llm.bo, &u32)
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return u32
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}
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func (llm ggufModel) readI32(r io.Reader) int32 {
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var i32 int32
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binary.Read(r, llm.bo, &i32)
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return i32
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}
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func (llm ggufModel) readU64(r io.Reader) uint64 {
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var u64 uint64
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binary.Read(r, llm.bo, &u64)
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return u64
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}
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func (llm ggufModel) readI64(r io.Reader) int64 {
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var i64 int64
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binary.Read(r, llm.bo, &i64)
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return i64
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}
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func (llm ggufModel) readF32(r io.Reader) float32 {
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var f32 float32
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binary.Read(r, llm.bo, &f32)
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return f32
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}
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func (llm ggufModel) readF64(r io.Reader) float64 {
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var f64 float64
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binary.Read(r, llm.bo, &f64)
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return f64
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}
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func (llm ggufModel) readBool(r io.Reader) bool {
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var b bool
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binary.Read(r, llm.bo, &b)
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return b
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}
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func (llm ggufModel) readStringV1(r io.Reader) (string, error) {
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var nameLength uint32
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binary.Read(r, llm.bo, &nameLength)
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var b bytes.Buffer
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if _, err := io.CopyN(&b, r, int64(nameLength)); err != nil {
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return "", err
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}
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// gguf v1 strings are null-terminated
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b.Truncate(b.Len() - 1)
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return b.String(), nil
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}
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func (llm ggufModel) readString(r io.Reader) (string, error) {
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if llm.Version == 1 {
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return llm.readStringV1(r)
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}
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var nameLength uint64
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binary.Read(r, llm.bo, &nameLength)
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var b bytes.Buffer
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if _, err := io.CopyN(&b, r, int64(nameLength)); err != nil {
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return "", err
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}
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return b.String(), nil
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}
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func (llm *ggufModel) readArrayV1(r io.Reader) (arr []any, err error) {
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atype := llm.readU32(r)
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n := llm.readU32(r)
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for i := 0; uint32(i) < n; i++ {
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switch atype {
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case ggufTypeUint8:
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arr = append(arr, llm.readU8(r))
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case ggufTypeInt8:
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arr = append(arr, llm.readI8(r))
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case ggufTypeUint16:
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arr = append(arr, llm.readU16(r))
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case ggufTypeInt16:
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arr = append(arr, llm.readI16(r))
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case ggufTypeUint32:
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arr = append(arr, llm.readU32(r))
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case ggufTypeInt32:
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arr = append(arr, llm.readI32(r))
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case ggufTypeFloat32:
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arr = append(arr, llm.readF32(r))
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case ggufTypeBool:
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arr = append(arr, llm.readBool(r))
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case ggufTypeString:
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s, err := llm.readStringV1(r)
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if err != nil {
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return nil, err
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}
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arr = append(arr, s)
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default:
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return nil, fmt.Errorf("invalid array type: %d", atype)
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}
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}
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return
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}
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func (llm *ggufModel) readArray(r io.Reader) (arr []any, err error) {
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if llm.Version == 1 {
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return llm.readArrayV1(r)
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}
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atype := llm.readU32(r)
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n := llm.readU64(r)
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for i := 0; uint64(i) < n; i++ {
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switch atype {
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case ggufTypeUint8:
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arr = append(arr, llm.readU8(r))
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case ggufTypeInt8:
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arr = append(arr, llm.readI8(r))
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case ggufTypeUint16:
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arr = append(arr, llm.readU16(r))
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case ggufTypeInt16:
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arr = append(arr, llm.readI16(r))
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case ggufTypeUint32:
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arr = append(arr, llm.readU32(r))
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case ggufTypeInt32:
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arr = append(arr, llm.readI32(r))
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case ggufTypeUint64:
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arr = append(arr, llm.readU64(r))
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case ggufTypeInt64:
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arr = append(arr, llm.readI64(r))
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case ggufTypeFloat32:
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arr = append(arr, llm.readF32(r))
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case ggufTypeFloat64:
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arr = append(arr, llm.readF64(r))
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case ggufTypeBool:
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arr = append(arr, llm.readBool(r))
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case ggufTypeString:
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s, err := llm.readString(r)
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if err != nil {
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return nil, err
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}
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arr = append(arr, s)
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default:
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return nil, fmt.Errorf("invalid array type: %d", atype)
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}
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}
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return
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}
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