ollama/convert/reader_safetensors.go

206 lines
4.7 KiB
Go

package convert
import (
"bufio"
"bytes"
"encoding/binary"
"encoding/json"
"errors"
"fmt"
"io"
"io/fs"
"maps"
"slices"
"strings"
"github.com/d4l3k/go-bfloat16"
"github.com/x448/float16"
)
type safetensorMetadata struct {
Type string `json:"dtype"`
Shape []uint64 `json:"shape"`
Offsets []int64 `json:"data_offsets"`
}
func parseSafetensors(fsys fs.FS, replacer *strings.Replacer, ps ...string) ([]Tensor, error) {
var ts []Tensor
for _, p := range ps {
f, err := fsys.Open(p)
if err != nil {
return nil, err
}
defer f.Close()
var n int64
if err := binary.Read(f, binary.LittleEndian, &n); err != nil {
return nil, err
}
b := bytes.NewBuffer(make([]byte, 0, n))
if _, err = io.CopyN(b, f, n); err != nil {
return nil, err
}
var headers map[string]safetensorMetadata
if err := json.NewDecoder(b).Decode(&headers); err != nil {
return nil, err
}
keys := slices.Sorted(maps.Keys(headers))
names := make(map[string]struct{}, len(keys))
for _, key := range keys {
if value := headers[key]; value.Type != "" {
// bitsandbytes quantized models are unsupported
if len(value.Shape) == 0 {
return nil, errors.New("unsupported safetensors model")
}
ggufName := replacer.Replace(key)
if _, ok := names[ggufName]; ok {
return nil, fmt.Errorf("duplicate tensor name '%s' was found for this model", ggufName)
}
names[ggufName] = struct{}{}
ts = append(ts, safetensor{
fs: fsys,
path: p,
dtype: value.Type,
offset: safetensorsPad(n, value.Offsets[0]),
size: safetensorsPad(n, value.Offsets[1]) - safetensorsPad(n, value.Offsets[0]),
tensorBase: &tensorBase{
name: ggufName,
shape: value.Shape,
},
})
}
}
}
return ts, nil
}
// safetensorsPad returns the padded size of the safetensors file given a length n and offset s
func safetensorsPad(n, offset int64) int64 {
return 8 + n + offset
}
type safetensor struct {
fs fs.FS
path string
dtype string
offset int64
size int64
*tensorBase
}
func (st safetensor) Kind() uint32 {
kind := st.tensorBase.Kind()
if !strings.HasPrefix(st.name, "v.") && st.dtype == "BF16" && kind != tensorKindFP32 {
kind = tensorKindBF16
}
return kind
}
func (st safetensor) Clone() Tensor {
return &safetensor{
fs: st.fs,
path: st.path,
dtype: st.dtype,
offset: st.offset,
size: st.size,
tensorBase: &tensorBase{
name: st.name,
repacker: st.repacker,
shape: slices.Clone(st.shape),
},
}
}
func (st safetensor) WriteTo(w io.Writer) (int64, error) {
f, err := st.fs.Open(st.path)
if err != nil {
return 0, err
}
defer f.Close()
r, err := func() (io.Reader, error) {
if readerAt, ok := f.(io.ReaderAt); ok {
return io.NewSectionReader(readerAt, st.offset, st.size), nil
} else if seeker, ok := f.(io.Seeker); ok {
_, err := seeker.Seek(st.offset, io.SeekStart)
return f, err
} else {
_, err := io.CopyN(io.Discard, f, st.offset)
return f, err
}
}()
if err != nil {
return 0, err
}
br := bufio.NewReaderSize(r, min(32<<10, int(st.size)))
// special case when input and output are same type and the
// tensor doesn't need repacking
if (st.repacker == nil) &&
((st.dtype == "F32" && st.Kind() == tensorKindFP32) ||
(st.dtype == "F16" && st.Kind() == tensorKindFP16) ||
(st.dtype == "U8")) {
return io.CopyN(w, br, st.size)
}
var f32s []float32
switch st.dtype {
case "F32":
f32s = make([]float32, st.size/4)
if err = binary.Read(br, binary.LittleEndian, f32s); err != nil {
return 0, err
}
case "F16":
u16s := make([]uint16, st.size/2)
if err = binary.Read(br, binary.LittleEndian, u16s); err != nil {
return 0, err
}
f32s = make([]float32, len(u16s))
for i := range u16s {
f32s[i] = float16.Frombits(u16s[i]).Float32()
}
case "BF16":
u8s := make([]uint8, st.size)
if err = binary.Read(br, binary.LittleEndian, u8s); err != nil {
return 0, err
}
f32s = bfloat16.DecodeFloat32(u8s)
default:
return 0, fmt.Errorf("unknown data type: %s", st.dtype)
}
if st.repacker != nil {
f32s, err = st.repacker(st.Name(), f32s, st.Shape())
if err != nil {
return 0, err
}
}
switch st.Kind() {
case tensorKindFP32:
return int64(len(f32s) * 4), binary.Write(w, binary.LittleEndian, f32s)
case tensorKindFP16:
f16s := make([]uint16, len(f32s))
for i := range f32s {
f16s[i] = float16.Fromfloat32(f32s[i]).Bits()
}
return int64(len(f16s) * 2), binary.Write(w, binary.LittleEndian, f16s)
case tensorKindBF16:
u8s := bfloat16.EncodeFloat32(f32s)
return int64(len(u8s)), binary.Write(w, binary.LittleEndian, u8s)
default:
return 0, fmt.Errorf("unknown storage type: %d", st.Kind())
}
}