mirror of
https://github.com/ollama/ollama.git
synced 2025-12-05 18:46:22 -06:00
feat: uneven splits (#11048)
The current splitDim function only operates on tensors that are split evenly which isn't always the case, e.g. a QKV tensor. This change allows the function to be used for arbitrary splits
This commit is contained in:
Michael Yang
GitHub
@@ -65,17 +65,17 @@ func (q *qwen25VLModel) Tensors(ts []Tensor) []*ggml.Tensor {
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for _, t := range ts {
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if strings.Contains(t.Name(), "patch_embed.proj") {
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for t := range splitDim(t, 2,
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strings.NewReplacer("patch_embed.proj", "patch_embd_0"),
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strings.NewReplacer("patch_embed.proj", "patch_embd_1"),
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split{Replacer: strings.NewReplacer("patch_embed.proj", "patch_embd_0")},
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split{Replacer: strings.NewReplacer("patch_embed.proj", "patch_embd_1")},
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) {
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t.Shape = slices.DeleteFunc(t.Shape, func(i uint64) bool { return i == 1 })
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out = append(out, t)
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}
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} else if strings.Contains(t.Name(), "attn.qkv") {
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out = append(out, slices.Collect(splitDim(t, 0,
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strings.NewReplacer("attn.qkv", "attn_q"),
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strings.NewReplacer("attn.qkv", "attn_k"),
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strings.NewReplacer("attn.qkv", "attn_v"),
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split{Replacer: strings.NewReplacer("attn.qkv", "attn_q")},
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split{Replacer: strings.NewReplacer("attn.qkv", "attn_k")},
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split{Replacer: strings.NewReplacer("attn.qkv", "attn_v")},
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))...)
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} else {
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out = append(out, &ggml.Tensor{
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@@ -1,53 +1,73 @@
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package convert
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import (
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"cmp"
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"iter"
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"slices"
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"strings"
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"github.com/ollama/ollama/fs/ggml"
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"github.com/pdevine/tensor"
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"github.com/pdevine/tensor/native"
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"github.com/ollama/ollama/fs/ggml"
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)
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type split struct {
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*strings.Replacer
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dim int
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// fn is an optional function to apply to the tensor after slicing
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fn func(tensor.Tensor) (tensor.Tensor, error)
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}
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// splitDim splits a tensor along a specified dimension into multiple tensors. The dimension
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// is split evenly based on the number of replacers provided.
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func splitDim(t Tensor, dim int, replacers ...*strings.Replacer) iter.Seq[*ggml.Tensor] {
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// is split evenly based on the number of replacers provided unless a specific count is given.
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func splitDim(t Tensor, dim int, splits ...split) iter.Seq[*ggml.Tensor] {
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return func(yield func(*ggml.Tensor) bool) {
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for i, replacer := range replacers {
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var offset int
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for _, split := range splits {
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t := t.Clone()
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shape := slices.Clone(t.Shape())
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shape[dim] = shape[dim] / uint64(len(replacers))
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shape[dim] = cmp.Or(uint64(split.dim), shape[dim]/uint64(len(splits)))
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slice := slices.Repeat([]tensor.Slice{nil}, len(shape))
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slice[dim] = tensor.S(i*int(shape[dim]), (i+1)*int(shape[dim]))
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slice[dim] = tensor.S(offset, offset+int(shape[dim]))
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offset += int(shape[dim])
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tt := t.Clone()
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tt.SetRepacker(func(_ string, data []float32, shape []uint64) ([]float32, error) {
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t.SetRepacker(func(_ string, data []float32, shape []uint64) ([]float32, error) {
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dims := make([]int, len(shape))
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for i := range shape {
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dims[i] = int(shape[i])
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}
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var t tensor.Tensor = tensor.New(tensor.WithShape(dims...), tensor.WithBacking(data))
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t, err := t.Slice(slice...)
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var tt tensor.Tensor = tensor.New(tensor.WithShape(dims...), tensor.WithBacking(data))
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tt, err := tt.Slice(slice...)
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if err != nil {
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return nil, err
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}
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t = tensor.Materialize(t)
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tt = tensor.Materialize(tt)
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if split.fn != nil {
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tt, err = split.fn(tt)
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if err != nil {
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return nil, err
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}
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}
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// flatten tensor so it can be written as a vector
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if err := t.Reshape(t.Shape().TotalSize()); err != nil {
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if err := tt.Reshape(tt.Shape().TotalSize()); err != nil {
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return nil, err
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}
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return native.VectorF32(t.(*tensor.Dense))
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return native.VectorF32(tt.(*tensor.Dense))
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})
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if !yield(&ggml.Tensor{
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Name: replacer.Replace(t.Name()),
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Name: split.Replace(t.Name()),
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Kind: t.Kind(),
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Shape: shape,
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WriterTo: tt,
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WriterTo: t,
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}) {
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break
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}
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304
convert/tensor_test.go
Normal file
304
convert/tensor_test.go
Normal file
@@ -0,0 +1,304 @@
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package convert
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import (
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"bytes"
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"encoding/binary"
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"io"
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"iter"
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"slices"
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"strings"
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"testing"
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"github.com/pdevine/tensor"
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)
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type fakeTensor struct {
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name string
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shape []uint64
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data []float32
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repacker Repacker
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}
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func (f fakeTensor) Name() string {
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return f.name
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}
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func (f fakeTensor) Shape() []uint64 {
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return f.shape
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}
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func (f fakeTensor) Kind() uint32 {
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return 0
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}
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func (f *fakeTensor) SetRepacker(fn Repacker) {
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f.repacker = fn
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}
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func (f fakeTensor) Clone() Tensor {
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return &fakeTensor{
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name: f.name,
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shape: slices.Clone(f.shape),
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data: slices.Clone(f.data),
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repacker: f.repacker,
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}
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}
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func (f fakeTensor) WriteTo(w io.Writer) (n int64, err error) {
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data := f.data
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if f.repacker != nil {
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data, err = f.repacker(f.name, data, f.shape)
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if err != nil {
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return 0, err
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}
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}
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if err := binary.Write(w, binary.LittleEndian, data); err != nil {
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return 0, err
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}
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return int64(len(data) * 4), nil
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}
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func mul(shape []uint64) int {
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n := 1
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for _, dim := range shape {
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n *= int(dim)
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}
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return n
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}
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func TestSplitDim(t *testing.T) {
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r := fakeTensor{
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name: "a.b",
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shape: []uint64{3, 4},
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data: []float32{0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11},
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}
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t.Run("no split", func(t *testing.T) {
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for tt := range splitDim(&r, 0, split{Replacer: strings.NewReplacer("a", "x")}) {
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if tt.Name != "x.b" {
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t.Fatalf("expected name 'x', got '%s'", tt.Name)
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}
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if !slices.Equal(tt.Shape, []uint64{3, 4}) {
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t.Fatalf("expected shape [3, 4], got %v", tt.Shape)
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}
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var b bytes.Buffer
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if _, err := tt.WriteTo(&b); err != nil {
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t.Fatal(err)
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}
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f32s := make([]float32, mul(tt.Shape))
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if err := binary.Read(&b, binary.LittleEndian, &f32s); err != nil {
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t.Fatal(err)
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}
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if !slices.Equal(f32s, []float32{0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11}) {
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t.Fatalf("expected data [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11], got %v", f32s)
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}
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}
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})
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t.Run("even split", func(t *testing.T) {
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next, stop := iter.Pull(splitDim(&r, 1,
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split{Replacer: strings.NewReplacer("a", "x")},
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split{Replacer: strings.NewReplacer("b", "y")},
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))
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defer stop()
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{
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tt, ok := next()
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if !ok {
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t.Fatal("expected at least one split")
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}
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if tt.Name != "x.b" {
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t.Fatal("expected name 'x.b', got", tt.Name)
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}
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if !slices.Equal(tt.Shape, []uint64{3, 2}) {
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t.Fatal("expected shape [3, 2], got", tt.Shape)
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}
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var b bytes.Buffer
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if _, err := tt.WriteTo(&b); err != nil {
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t.Fatal(err)
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}
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f32s := make([]float32, mul(tt.Shape))
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if err := binary.Read(&b, binary.LittleEndian, &f32s); err != nil {
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t.Fatal(err)
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}
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if !slices.Equal(f32s, []float32{0, 1, 4, 5, 8, 9}) {
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t.Fatal("expected data [0, 1, 4, 5, 8, 9], got", f32s)
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}
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}
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{
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tt, ok := next()
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if !ok {
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t.Fatal("expected at least one split")
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}
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if tt.Name != "a.y" {
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t.Fatal("expected name 'a.y', got", tt.Name)
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}
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if !slices.Equal(tt.Shape, []uint64{3, 2}) {
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t.Fatal("expected shape [3, 2], got", tt.Shape)
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}
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var b bytes.Buffer
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if _, err := tt.WriteTo(&b); err != nil {
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t.Fatal(err)
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}
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f32s := make([]float32, mul(tt.Shape))
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if err := binary.Read(&b, binary.LittleEndian, &f32s); err != nil {
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t.Fatal(err)
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}
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if !slices.Equal(f32s, []float32{2, 3, 6, 7, 10, 11}) {
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t.Fatal("expected data [2, 3, 6, 7, 10, 11], got", f32s)
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}
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}
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})
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t.Run("uneven split", func(t *testing.T) {
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next, stop := iter.Pull(splitDim(&r, 0,
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split{Replacer: strings.NewReplacer("a", "x"), dim: 2},
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split{Replacer: strings.NewReplacer("b", "y"), dim: 1},
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))
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defer stop()
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{
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tt, ok := next()
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if !ok {
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t.Fatal("expected at least one split")
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}
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if tt.Name != "x.b" {
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t.Fatal("expected name 'x.b', got", tt.Name)
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}
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if !slices.Equal(tt.Shape, []uint64{2, 4}) {
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t.Fatal("expected shape [2, 4], got", tt.Shape)
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}
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var b bytes.Buffer
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if _, err := tt.WriteTo(&b); err != nil {
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t.Fatal(err)
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}
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f32s := make([]float32, mul(tt.Shape))
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if err := binary.Read(&b, binary.LittleEndian, &f32s); err != nil {
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t.Fatal(err)
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}
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if !slices.Equal(f32s, []float32{0, 1, 2, 3, 4, 5, 6, 7}) {
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t.Fatal("expected data [0, 1, 2, 3, 4, 5, 6, 7], got", f32s)
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}
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}
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{
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tt, ok := next()
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if !ok {
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t.Fatal("expected at least one split")
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}
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if tt.Name != "a.y" {
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t.Fatal("expected name 'a.y', got", tt.Name)
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}
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if !slices.Equal(tt.Shape, []uint64{1, 4}) {
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t.Fatal("expected shape [1, 4], got", tt.Shape)
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}
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var b bytes.Buffer
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if _, err := tt.WriteTo(&b); err != nil {
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t.Fatal(err)
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}
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f32s := make([]float32, mul(tt.Shape))
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if err := binary.Read(&b, binary.LittleEndian, &f32s); err != nil {
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t.Fatal(err)
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}
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if !slices.Equal(f32s, []float32{8, 9, 10, 11}) {
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t.Fatal("expected data [8, 9, 10, 11], got", f32s)
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}
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}
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})
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t.Run("split with transpose", func(t *testing.T) {
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next, stop := iter.Pull(splitDim(&r, 1,
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split{Replacer: strings.NewReplacer("a", "x")},
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split{Replacer: strings.NewReplacer("b", "y"), fn: func(tt tensor.Tensor) (tensor.Tensor, error) {
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return tensor.Transpose(tt, 1, 0)
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}},
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))
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defer stop()
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{
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tt, ok := next()
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if !ok {
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t.Fatal("expected at least one split")
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}
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if tt.Name != "x.b" {
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t.Fatal("expected name 'x.b', got", tt.Name)
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}
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if !slices.Equal(tt.Shape, []uint64{3, 2}) {
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t.Fatal("expected shape [3, 2], got", tt.Shape)
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}
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var b bytes.Buffer
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if _, err := tt.WriteTo(&b); err != nil {
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t.Fatal(err)
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}
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f32s := make([]float32, mul(tt.Shape))
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if err := binary.Read(&b, binary.LittleEndian, &f32s); err != nil {
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t.Fatal(err)
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}
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if !slices.Equal(f32s, []float32{0, 1, 4, 5, 8, 9}) {
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t.Fatal("expected data [0, 1, 4, 5, 8, 9], got", f32s)
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}
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}
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{
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tt, ok := next()
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if !ok {
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t.Fatal("expected at least one split")
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}
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if tt.Name != "a.y" {
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t.Fatal("expected name 'a.y', got", tt.Name)
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}
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if !slices.Equal(tt.Shape, []uint64{3, 2}) {
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t.Fatal("expected shape [3, 2], got", tt.Shape)
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}
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var b bytes.Buffer
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if _, err := tt.WriteTo(&b); err != nil {
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t.Fatal(err)
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}
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f32s := make([]float32, mul(tt.Shape))
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if err := binary.Read(&b, binary.LittleEndian, &f32s); err != nil {
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t.Fatal(err)
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}
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if !slices.Equal(f32s, []float32{2, 6, 10, 3, 7, 11}) {
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t.Fatal("expected data [2, 6, 10, 3, 7, 11], got", f32s)
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}
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}
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})
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}
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