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ml/backend/ggml: offload vision to cpu

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temporary until tensor loading can accurately account for vision models
This commit is contained in:
Michael Yang 2025-02-27 16:46:01 -08:00
parent b5312f30e8
commit 2dc60d4620
1 changed files with 6 additions and 10 deletions
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16
ml/backend/ggml/ggml.go
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@ -134,13 +134,7 @@ func New(r *os.File, params ml.BackendParams) (ml.Backend, error) {
cpuDeviceBufferTypes := deviceBufferType{C.ggml_backend_dev_by_type(C.GGML_BACKEND_DEVICE_TYPE_CPU), cpuBufferTypes}
input := cpuDeviceBufferTypes
var blocks int
for key, value := range meta.KV() {
if strings.HasSuffix(key, ".block_count") {
blocks += int(value.(uint32))
}
}
blocks := int(meta.KV().BlockCount())
assignLayer := func(i int) (temp deviceBufferType) {
if i >= params.NumGPULayers {
return cpuDeviceBufferTypes
@ -206,7 +200,7 @@ func New(r *os.File, params ml.BackendParams) (ml.Backend, error) {
return nil
}
hasPart := func(s string, parts ...string) bool {
contains := func(s string, parts ...string) bool {
split := strings.Split(s, ".")
for _, part := range parts {
if slices.Contains(split, part) {
@ -219,10 +213,12 @@ func New(r *os.File, params ml.BackendParams) (ml.Backend, error) {
for _, t := range meta.Tensors().Items() {
switch {
case hasPart(t.Name, "position_embd", "token_embd", "token_norm_embd", "token_types"):
case contains(t.Name, "position_embd", "token_embd", "token_norm_embd", "token_types"):
createTensor(tensor{source: t}, input.bts)
case hasPart(t.Name, "cls", "output", "output_norm"):
case contains(t.Name, "cls", "output", "output_norm"):
createTensor(tensor{source: t}, output.bts)
case strings.HasPrefix(t.Name, "v.") || strings.HasPrefix(t.Name, "mm."):
createTensor(tensor{source: t}, input.bts)
default:
if i := func() int {
if fields := strings.FieldsFunc(t.Name, func(r rune) bool { return !unicode.IsNumber(r) }); len(fields) > 0 {