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refactor rope

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change to a flatter directory structure and group the options with the
function

update models to call rope in one place
This commit is contained in:
Michael Yang
2025-11-18 15:17:03 -08:00
committed by Michael Yang
parent e082d60a24
commit 603ceefaa6
21 changed files with 114 additions and 91 deletions
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11
model/models/gemma3n/model_text.go
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@@ -8,7 +8,6 @@ import (
"github.com/ollama/ollama/kvcache"
"github.com/ollama/ollama/ml"
"github.com/ollama/ollama/ml/nn"
"github.com/ollama/ollama/ml/nn/fast"
"github.com/ollama/ollama/ml/nn/rope"
"github.com/ollama/ollama/model/input"
)
@@ -95,7 +94,7 @@ func (m *TextModel) Shift(ctx ml.Context, layer int, key, shift ml.Tensor) (ml.T
ropeBase = m.ropeBaseLocal
}
return fast.RoPE(ctx, key, shift, m.headDim(), ropeBase, 1./m.ropeScale, rope.WithTypeNeoX()), nil
return m.applyRotaryPositionEmbeddings(ctx, key, shift, ropeBase), nil
}
type TextScaledWordEmbedding struct {
@@ -256,14 +255,14 @@ func (attn TextAttention) Forward(ctx ml.Context, hiddenStates, positions ml.Ten
query := attn.Query.Forward(ctx, hiddenStates)
query = query.Reshape(ctx, opts.headDim(), opts.numHeads, batchSize)
query = attn.QueryNorm.Forward(ctx, query, opts.eps)
query = fast.RoPE(ctx, query, positions, opts.headDim(), ropeBase, 1./opts.ropeScale, rope.WithTypeNeoX())
query = opts.applyRotaryPositionEmbeddings(ctx, query, positions, ropeBase)
var key, value ml.Tensor
if !sharedKV {
key = attn.Key.Forward(ctx, hiddenStates)
key = key.Reshape(ctx, opts.headDim(), opts.numKVHeads, batchSize)
key = attn.KeyNorm.Forward(ctx, key, opts.eps)
key = fast.RoPE(ctx, key, positions, opts.headDim(), ropeBase, 1./opts.ropeScale, rope.WithTypeNeoX())
key = opts.applyRotaryPositionEmbeddings(ctx, key, positions, ropeBase)
value = attn.Value.Forward(ctx, hiddenStates)
value = value.Reshape(ctx, opts.headDim(), opts.numKVHeads, batchSize)
@@ -330,6 +329,10 @@ func (o *TextOptions) isLocal(i int) bool {
return o.slidingWindowPattern[i]
}
func (o TextOptions) applyRotaryPositionEmbeddings(ctx ml.Context, t, p ml.Tensor, base float32) ml.Tensor {
return nn.RoPE(ctx, t, p, o.headDim(), base, 1./o.ropeScale, rope.WithTypeNeoX())
}
func newTextModel(c fs.Config) *TextModel {
return &TextModel{
TextLayers: make([]TextLayer, c.Uint("block_count")),