interleaved mrope (#12807)

* ml(ggml): mrope
* interleave mrope
This commit is contained in:
Michael Yang 2025-10-30 11:29:00 -07:00 committed by GitHub
parent 75e75d9afe
commit f67a6df110
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10 changed files with 209 additions and 119 deletions

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@ -0,0 +1,113 @@
From 0000000000000000000000000000000000000000 Mon Sep 17 00:00:00 2001
From: Michael Yang <git@mxy.ng>
Date: Web, 16 Oct 2025 20:37:19 -0700
Subject: [PATCH] interleave multi rope
since ollama doesn't use mrope for anything else, change it to mean the
interleaved version used for qwen3vl
---
ggml/src/ggml-cpu/ops.cpp | 7 ++-----
ggml/src/ggml-cuda/rope.cu | 12 +++---------
ggml/src/ggml-metal/ggml-metal.metal | 10 +++-------
ggml/src/ggml-vulkan/vulkan-shaders/rope_multi.comp | 12 +++---------
4 files changed, 11 insertions(+), 30 deletions(-)
diff --git a/ggml/src/ggml-cpu/ops.cpp b/ggml/src/ggml-cpu/ops.cpp
index 31478dd8e..4d1ed207e 100644
--- a/ggml/src/ggml-cpu/ops.cpp
+++ b/ggml/src/ggml-cpu/ops.cpp
@@ -5509,15 +5509,12 @@ static void ggml_mrope_cache_init(
}
float theta = theta_t;
- if (sector >= sections[0] && sector < sec_w) {
+ if (sector % 3 == 1 && sector < 1 + 3 * sections[1]) {
theta = theta_h;
}
- else if (sector >= sec_w && sector < sec_w + sections[2]) {
+ else if (sector % 3 == 2 && sector < 2 + 3 * sections[2]) {
theta = theta_w;
}
- else if (sector >= sec_w + sections[2]) {
- theta = theta_e;
- }
rope_yarn(
theta/ff, freq_scale, corr_dims, i0, ext_factor, mscale, &cache[i0 + 0], &cache[i0 + 1]
diff --git a/ggml/src/ggml-cuda/rope.cu b/ggml/src/ggml-cuda/rope.cu
index d058504cd..287fe9d2c 100644
--- a/ggml/src/ggml-cuda/rope.cu
+++ b/ggml/src/ggml-cuda/rope.cu
@@ -151,19 +151,13 @@ static __global__ void rope_multi(
const int sec_w = sections.v[1] + sections.v[0];
const int sector = (i0 / 2) % sect_dims;
- float theta_base = 0.0;
- if (sector < sections.v[0]) {
- theta_base = pos[channel_x]*powf(theta_scale, i0/2.0f);
- }
- else if (sector >= sections.v[0] && sector < sec_w) {
+ float theta_base = pos[channel_x]*powf(theta_scale, i0/2.0f);
+ if (sector % 3 == 1 && sector < 1 + 3 * sections.v[1]) {
theta_base = pos[channel_x + ne2 * 1]*powf(theta_scale, i0/2.0f);
}
- else if (sector >= sec_w && sector < sec_w + sections.v[2]) {
+ else if (sector % 3 == 2 && sector < 2 + 3 * sections.v[2]) {
theta_base = pos[channel_x + ne2 * 2]*powf(theta_scale, i0/2.0f);
}
- else if (sector >= sec_w + sections.v[2]) {
- theta_base = pos[channel_x + ne2 * 3]*powf(theta_scale, i0/2.0f);
- }
const float freq_factor = has_ff ? freq_factors[i0/2] : 1.0f;
diff --git a/ggml/src/ggml-metal/ggml-metal.metal b/ggml/src/ggml-metal/ggml-metal.metal
index 375a0c7fd..9866c96b4 100644
--- a/ggml/src/ggml-metal/ggml-metal.metal
+++ b/ggml/src/ggml-metal/ggml-metal.metal
@@ -3858,15 +3858,11 @@ kernel void kernel_rope_multi(
const int sec_w012 = args.sect_0 + args.sect_1 + args.sect_2; // end of section 2
const int sector = ic % sect_dims;
- float theta_base;
- if (sector < args.sect_0) {
- theta_base = (float) pos[i2];
- } else if (sector < sec_w01) {
+ float theta_base = (float) pos[i2];
+ if (sector % 3 == 1 && sector < 1 + 3 * args.sect_1) {
theta_base = (float) pos[i2 + args.ne02];
- } else if (sector < sec_w012) {
+ } else if (sector % 3 == 2 && sector < 2 + 3 * args.sect_2) {
theta_base = (float) pos[i2 + args.ne02 * 2];
- } else {
- theta_base = (float) pos[i2 + args.ne02 * 3];
}
// end of mrope
diff --git a/ggml/src/ggml-vulkan/vulkan-shaders/rope_multi.comp b/ggml/src/ggml-vulkan/vulkan-shaders/rope_multi.comp
index 111286b49..6fc2b42f8 100644
--- a/ggml/src/ggml-vulkan/vulkan-shaders/rope_multi.comp
+++ b/ggml/src/ggml-vulkan/vulkan-shaders/rope_multi.comp
@@ -31,19 +31,13 @@ void main() {
const int sec_w = p.sections[1] + p.sections[0];
const uint sector = (i0 / 2) % sect_dims;
- float theta_base = 0.0;
- if (sector < p.sections[0]) {
- theta_base = data_pos[channel_x]*pow(p.theta_scale, i0/2.0f);
- }
- else if (sector >= p.sections[0] && sector < sec_w) {
+ float theta_base = data_pos[channel_x]*pow(p.theta_scale, i0/2.0f);
+ if (sector % 3 == 1 && sector < 1 + 3 * p.sections[1]) {
theta_base = data_pos[channel_x + ne2 * 1]*pow(p.theta_scale, i0/2.0f);
}
- else if (sector >= sec_w && sector < sec_w + p.sections[2]) {
+ else if (sector % 3 == 2 && sector < 2 + 3 * p.sections[2]) {
theta_base = data_pos[channel_x + ne2 * 2]*pow(p.theta_scale, i0/2.0f);
}
- else if (sector >= sec_w + p.sections[2]) {
- theta_base = data_pos[channel_x + ne2 * 3]*pow(p.theta_scale, i0/2.0f);
- }
const float freq_factor = p.has_ff != 0 ? data_ff[i0/2] : 1.0f;

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@ -11,6 +11,7 @@ package ggml
import "C" import "C"
import ( import (
"cmp"
"context" "context"
"encoding/binary" "encoding/binary"
"errors" "errors"
@ -1490,14 +1491,7 @@ func (t *Tensor) View(ctx ml.Context, offset int, shape ...int) ml.Tensor {
func (t *Tensor) RoPE(ctx ml.Context, positions ml.Tensor, ropeDim int, ropeBase, ropeScale float32, options ...func(*rope.Options)) ml.Tensor { func (t *Tensor) RoPE(ctx ml.Context, positions ml.Tensor, ropeDim int, ropeBase, ropeScale float32, options ...func(*rope.Options)) ml.Tensor {
// Default options // Default options
opts := rope.Options{ opts := rope.Options{Factors: &Tensor{}}
Factors: &Tensor{},
OriginalContextLength: 131072,
ExtrapolationFactor: 0.,
AttentionFactor: 1.,
BetaFast: 32.,
BetaSlow: 1.,
}
// Apply any provided options // Apply any provided options
for _, option := range options { for _, option := range options {
@ -1509,24 +1503,44 @@ func (t *Tensor) RoPE(ctx ml.Context, positions ml.Tensor, ropeDim int, ropeBase
dequant = C.ggml_cast(ctx.(*Context).ctx, t.t, C.GGML_TYPE_F32) dequant = C.ggml_cast(ctx.(*Context).ctx, t.t, C.GGML_TYPE_F32)
} }
return &Tensor{ var tt *C.struct_ggml_tensor
b: t.b, if len(opts.MRoPE.Sections) > 0 {
t: C.ggml_rope_ext( mropeSections := make([]C.int32_t, 4)
for i, section := range opts.MRoPE.Sections {
mropeSections[i] = C.int32_t(section)
}
tt = C.ggml_rope_multi(
ctx.(*Context).ctx, ctx.(*Context).ctx,
dequant, dequant,
positions.(*Tensor).t, positions.(*Tensor).t,
opts.Factors.(*Tensor).t, opts.Factors.(*Tensor).t,
C.int(ropeDim), C.int(ropeDim),
unsafe.SliceData(mropeSections),
C.int(opts.Type), C.int(opts.Type),
C.int(opts.OriginalContextLength), cmp.Or(C.int(opts.YaRN.OriginalContextLength), 128<<10),
C.float(ropeBase), C.float(ropeBase), C.float(ropeScale),
C.float(ropeScale), C.float(opts.YaRN.ExtrapolationFactor),
C.float(opts.ExtrapolationFactor), cmp.Or(C.float(opts.YaRN.AttentionFactor), 1),
C.float(opts.AttentionFactor), cmp.Or(C.float(opts.YaRN.BetaFast), 32),
C.float(opts.BetaFast), cmp.Or(C.float(opts.YaRN.BetaSlow), 1),
C.float(opts.BetaSlow), )
), } else {
tt = C.ggml_rope_ext(
ctx.(*Context).ctx,
dequant,
positions.(*Tensor).t,
opts.Factors.(*Tensor).t,
C.int(ropeDim), C.int(opts.Type),
cmp.Or(C.int(opts.YaRN.OriginalContextLength), 128<<10),
C.float(ropeBase), C.float(ropeScale),
C.float(opts.YaRN.ExtrapolationFactor),
cmp.Or(C.float(opts.YaRN.AttentionFactor), 1),
cmp.Or(C.float(opts.YaRN.BetaFast), 32),
cmp.Or(C.float(opts.YaRN.BetaSlow), 1),
)
} }
return &Tensor{b: t.b, t: tt}
} }
func (t *Tensor) IM2Col(ctx ml.Context, t2 ml.Tensor, s0, s1, p0, p1, d0, d1 int) ml.Tensor { func (t *Tensor) IM2Col(ctx ml.Context, t2 ml.Tensor, s0, s1, p0, p1, d0, d1 int) ml.Tensor {

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@ -5509,15 +5509,12 @@ static void ggml_mrope_cache_init(
} }
float theta = theta_t; float theta = theta_t;
if (sector >= sections[0] && sector < sec_w) { if (sector % 3 == 1 && sector < 1 + 3 * sections[1]) {
theta = theta_h; theta = theta_h;
} }
else if (sector >= sec_w && sector < sec_w + sections[2]) { else if (sector % 3 == 2 && sector < 2 + 3 * sections[2]) {
theta = theta_w; theta = theta_w;
} }
else if (sector >= sec_w + sections[2]) {
theta = theta_e;
}
rope_yarn( rope_yarn(
theta/ff, freq_scale, corr_dims, i0, ext_factor, mscale, &cache[i0 + 0], &cache[i0 + 1] theta/ff, freq_scale, corr_dims, i0, ext_factor, mscale, &cache[i0 + 0], &cache[i0 + 1]

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@ -151,19 +151,13 @@ static __global__ void rope_multi(
const int sec_w = sections.v[1] + sections.v[0]; const int sec_w = sections.v[1] + sections.v[0];
const int sector = (i0 / 2) % sect_dims; const int sector = (i0 / 2) % sect_dims;
float theta_base = 0.0; float theta_base = pos[channel_x]*powf(theta_scale, i0/2.0f);
if (sector < sections.v[0]) { if (sector % 3 == 1 && sector < 1 + 3 * sections.v[1]) {
theta_base = pos[channel_x]*powf(theta_scale, i0/2.0f);
}
else if (sector >= sections.v[0] && sector < sec_w) {
theta_base = pos[channel_x + ne2 * 1]*powf(theta_scale, i0/2.0f); theta_base = pos[channel_x + ne2 * 1]*powf(theta_scale, i0/2.0f);
} }
else if (sector >= sec_w && sector < sec_w + sections.v[2]) { else if (sector % 3 == 2 && sector < 2 + 3 * sections.v[2]) {
theta_base = pos[channel_x + ne2 * 2]*powf(theta_scale, i0/2.0f); theta_base = pos[channel_x + ne2 * 2]*powf(theta_scale, i0/2.0f);
} }
else if (sector >= sec_w + sections.v[2]) {
theta_base = pos[channel_x + ne2 * 3]*powf(theta_scale, i0/2.0f);
}
const float freq_factor = has_ff ? freq_factors[i0/2] : 1.0f; const float freq_factor = has_ff ? freq_factors[i0/2] : 1.0f;

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@ -6523,15 +6523,11 @@ kernel void kernel_rope_multi(
const int sec_w012 = args.sect_0 + args.sect_1 + args.sect_2; // end of section 2 const int sec_w012 = args.sect_0 + args.sect_1 + args.sect_2; // end of section 2
const int sector = ic % sect_dims; const int sector = ic % sect_dims;
float theta_base; float theta_base = (float) pos[i2];
if (sector < args.sect_0) { if (sector % 3 == 1 && sector < 1 + 3 * args.sect_1) {
theta_base = (float) pos[i2];
} else if (sector < sec_w01) {
theta_base = (float) pos[i2 + args.ne02]; theta_base = (float) pos[i2 + args.ne02];
} else if (sector < sec_w012) { } else if (sector % 3 == 2 && sector < 2 + 3 * args.sect_2) {
theta_base = (float) pos[i2 + args.ne02 * 2]; theta_base = (float) pos[i2 + args.ne02 * 2];
} else {
theta_base = (float) pos[i2 + args.ne02 * 3];
} }
// end of mrope // end of mrope

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@ -3858,15 +3858,11 @@ kernel void kernel_rope_multi(
const int sec_w012 = args.sect_0 + args.sect_1 + args.sect_2; // end of section 2 const int sec_w012 = args.sect_0 + args.sect_1 + args.sect_2; // end of section 2
const int sector = ic % sect_dims; const int sector = ic % sect_dims;
float theta_base; float theta_base = (float) pos[i2];
if (sector < args.sect_0) { if (sector % 3 == 1 && sector < 1 + 3 * args.sect_1) {
theta_base = (float) pos[i2];
} else if (sector < sec_w01) {
theta_base = (float) pos[i2 + args.ne02]; theta_base = (float) pos[i2 + args.ne02];
} else if (sector < sec_w012) { } else if (sector % 3 == 2 && sector < 2 + 3 * args.sect_2) {
theta_base = (float) pos[i2 + args.ne02 * 2]; theta_base = (float) pos[i2 + args.ne02 * 2];
} else {
theta_base = (float) pos[i2 + args.ne02 * 3];
} }
// end of mrope // end of mrope

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@ -31,19 +31,13 @@ void main() {
const int sec_w = p.sections[1] + p.sections[0]; const int sec_w = p.sections[1] + p.sections[0];
const uint sector = (i0 / 2) % sect_dims; const uint sector = (i0 / 2) % sect_dims;
float theta_base = 0.0; float theta_base = data_pos[channel_x]*pow(p.theta_scale, i0/2.0f);
if (sector < p.sections[0]) { if (sector % 3 == 1 && sector < 1 + 3 * p.sections[1]) {
theta_base = data_pos[channel_x]*pow(p.theta_scale, i0/2.0f);
}
else if (sector >= p.sections[0] && sector < sec_w) {
theta_base = data_pos[channel_x + ne2 * 1]*pow(p.theta_scale, i0/2.0f); theta_base = data_pos[channel_x + ne2 * 1]*pow(p.theta_scale, i0/2.0f);
} }
else if (sector >= sec_w && sector < sec_w + p.sections[2]) { else if (sector % 3 == 2 && sector < 2 + 3 * p.sections[2]) {
theta_base = data_pos[channel_x + ne2 * 2]*pow(p.theta_scale, i0/2.0f); theta_base = data_pos[channel_x + ne2 * 2]*pow(p.theta_scale, i0/2.0f);
} }
else if (sector >= sec_w + p.sections[2]) {
theta_base = data_pos[channel_x + ne2 * 3]*pow(p.theta_scale, i0/2.0f);
}
const float freq_factor = p.has_ff != 0 ? data_ff[i0/2] : 1.0f; const float freq_factor = p.has_ff != 0 ? data_ff[i0/2] : 1.0f;

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@ -4,21 +4,21 @@ import "github.com/ollama/ollama/ml"
// Options contains optional parameters for RoPE function // Options contains optional parameters for RoPE function
type Options struct { type Options struct {
Type int Type int
Factors ml.Tensor Factors ml.Tensor
OriginalContextLength int
// YaRN options // YaRN options
ExtrapolationFactor, YaRN struct {
AttentionFactor, OriginalContextLength int
BetaFast, ExtrapolationFactor,
BetaSlow float32 AttentionFactor,
} BetaFast,
BetaSlow float32
}
// WithOriginalContextLength sets a custom context length // MRoPE options
func WithOriginalContextLength(n int) func(*Options) { MRoPE struct {
return func(opts *Options) { Sections []int
opts.OriginalContextLength = n
} }
} }
@ -38,14 +38,28 @@ func WithFactors(factors ml.Tensor) func(*Options) {
} }
} }
// WithOriginalContextLength sets a custom context length
func WithOriginalContextLength(n int) func(*Options) {
return func(opts *Options) {
opts.YaRN.OriginalContextLength = n
}
}
func WithExtrapolationFactor(extrapolationFactor float32) func(*Options) { func WithExtrapolationFactor(extrapolationFactor float32) func(*Options) {
return func(opts *Options) { return func(opts *Options) {
opts.ExtrapolationFactor = extrapolationFactor opts.YaRN.ExtrapolationFactor = extrapolationFactor
} }
} }
func WithAttentionFactor(attentionFactor float32) func(*Options) { func WithAttentionFactor(attentionFactor float32) func(*Options) {
return func(opts *Options) { return func(opts *Options) {
opts.AttentionFactor = attentionFactor opts.YaRN.AttentionFactor = attentionFactor
}
}
func WithMRoPESections(sections []int) func(*Options) {
return func(opts *Options) {
opts.Type |= 1 << 3
opts.MRoPE.Sections = sections
} }
} }

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@ -112,7 +112,8 @@ func (m *Model) PostTokenize(inputs []*input.Input) ([]*input.Input, error) {
} }
func (m *Model) Forward(ctx ml.Context, batch input.Batch) (ml.Tensor, error) { func (m *Model) Forward(ctx ml.Context, batch input.Batch) (ml.Tensor, error) {
positionSlice := slices.Collect(makeSlice2D[int32](3, len(batch.Positions))) // ggml mrope requires 4 positions per token: [time, height, width, extra]
positionSlice := slices.Collect(makeSlice2D[int32](4, len(batch.Positions)))
for i, id := range batch.Positions { for i, id := range batch.Positions {
if id < int32(len(m.positionCache)) { if id < int32(len(m.positionCache)) {
id = m.positionCache[id] id = m.positionCache[id]
@ -123,6 +124,7 @@ func (m *Model) Forward(ctx ml.Context, batch input.Batch) (ml.Tensor, error) {
positionSlice[0][i] = id positionSlice[0][i] = id
positionSlice[1][i] = id positionSlice[1][i] = id
positionSlice[2][i] = id positionSlice[2][i] = id
// positionSlice[3] is intentionally left as zeros
} }
hiddenStates := m.TextModel.TokenEmbedding.Forward(ctx, batch.Inputs).Duplicate(ctx) hiddenStates := m.TextModel.TokenEmbedding.Forward(ctx, batch.Inputs).Duplicate(ctx)
@ -147,8 +149,7 @@ func (m *Model) Forward(ctx ml.Context, batch input.Batch) (ml.Tensor, error) {
} }
} }
positions := ctx.Input().FromInts(slices.Concat(positionSlice...), len(positionSlice[0]), len(positionSlice)) positions := ctx.Input().FromInts(slices.Concat(positionSlice...), len(positionSlice[0])*len(positionSlice))
cos, sin := m.rotaryEmbedding(ctx, positions)
for i, layer := range m.TextModel.Layers { for i, layer := range m.TextModel.Layers {
if m.Cache != nil { if m.Cache != nil {
m.Cache.SetLayer(i) m.Cache.SetLayer(i)
@ -159,7 +160,7 @@ func (m *Model) Forward(ctx ml.Context, batch input.Batch) (ml.Tensor, error) {
outputs = batch.Outputs outputs = batch.Outputs
} }
hiddenStates = layer.Forward(ctx, hiddenStates, cos, sin, outputs, m.Cache, m.Options) hiddenStates = layer.Forward(ctx, hiddenStates, positions, outputs, m.Cache, m.Options)
if i < len(deepstackVisualEmbeds) { if i < len(deepstackVisualEmbeds) {
hiddenStates = hiddenStates.Add(ctx, deepstackVisualEmbeds[i]) hiddenStates = hiddenStates.Add(ctx, deepstackVisualEmbeds[i])
} }
@ -191,9 +192,10 @@ func New(c fs.Config) (model.Model, error) {
ImageProcessor: newImageProcessor(c), ImageProcessor: newImageProcessor(c),
} }
m.Cache = kvcache.NewCausalCache(func(ctx ml.Context, layer int, key, position ml.Tensor) (ml.Tensor, error) { m.Cache = kvcache.NewCausalCache(func(ctx ml.Context, layer int, key, positions ml.Tensor) (ml.Tensor, error) {
m.positionCache = nil m.positionCache = nil
return nil, kvcache.ErrNotSupported positions = positions.Repeat(ctx, 1, 4).Reshape(ctx, -1)
return m.Options.applyRotaryPositionalEmbedding(ctx, key, positions), nil
}) })
return &m, nil return &m, nil
} }

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@ -10,6 +10,8 @@ import (
"github.com/ollama/ollama/kvcache" "github.com/ollama/ollama/kvcache"
"github.com/ollama/ollama/ml" "github.com/ollama/ollama/ml"
"github.com/ollama/ollama/ml/nn" "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" "github.com/ollama/ollama/model"
) )
@ -27,14 +29,18 @@ type TextOptions struct {
numExperts, numExpertsUsed int numExperts, numExpertsUsed int
normTopKProb bool normTopKProb bool
inverseFrequenciesCache []float32
} }
func (o TextOptions) headDim() int { func (o TextOptions) headDim() int {
return cmp.Or(o.keyLength, o.valueLength, o.hiddenSize/o.numHeads) return cmp.Or(o.keyLength, o.valueLength, o.hiddenSize/o.numHeads)
} }
func (o TextOptions) applyRotaryPositionalEmbedding(ctx ml.Context, t, p ml.Tensor) ml.Tensor {
return fast.RoPE(ctx, t, p, o.headDim(), o.ropeBase, 1/float32(math.Sqrt(float64(o.ropeScale))),
rope.WithMRoPESections(o.mropeSections),
)
}
type TextAttention struct { type TextAttention struct {
Query *nn.Linear `gguf:"attn_q"` Query *nn.Linear `gguf:"attn_q"`
QueryNorm *nn.RMSNorm `gguf:"attn_q_norm"` QueryNorm *nn.RMSNorm `gguf:"attn_q_norm"`
@ -44,7 +50,7 @@ type TextAttention struct {
Output *nn.Linear `gguf:"attn_output"` Output *nn.Linear `gguf:"attn_output"`
} }
func (sa *TextAttention) Forward(ctx ml.Context, hiddenStates, cos, sin ml.Tensor, cache kvcache.Cache, opts *TextOptions) ml.Tensor { func (sa *TextAttention) Forward(ctx ml.Context, hiddenStates, positions ml.Tensor, cache kvcache.Cache, opts *TextOptions) ml.Tensor {
batchSize := hiddenStates.Dim(1) batchSize := hiddenStates.Dim(1)
query := sa.Query.Forward(ctx, hiddenStates) query := sa.Query.Forward(ctx, hiddenStates)
@ -58,8 +64,8 @@ func (sa *TextAttention) Forward(ctx ml.Context, hiddenStates, cos, sin ml.Tenso
query = sa.QueryNorm.Forward(ctx, query, opts.eps) query = sa.QueryNorm.Forward(ctx, query, opts.eps)
key = sa.KeyNorm.Forward(ctx, key, opts.eps) key = sa.KeyNorm.Forward(ctx, key, opts.eps)
query = applyRotaryPositionalEmbedding(ctx, query, cos, sin) query = opts.applyRotaryPositionalEmbedding(ctx, query, positions)
key = applyRotaryPositionalEmbedding(ctx, key, cos, sin) key = opts.applyRotaryPositionalEmbedding(ctx, key, positions)
attention := nn.Attention(ctx, query, key, value, 1./math.Sqrt(float64(opts.headDim())), cache) attention := nn.Attention(ctx, query, key, value, 1./math.Sqrt(float64(opts.headDim())), cache)
attention = attention.Reshape(ctx, attention.Dim(0)*attention.Dim(1), batchSize) attention = attention.Reshape(ctx, attention.Dim(0)*attention.Dim(1), batchSize)
@ -125,10 +131,10 @@ type TextLayer struct {
TextMLP TextMLP
} }
func (d *TextLayer) Forward(ctx ml.Context, hiddenStates, cos, sin, outputs ml.Tensor, cache kvcache.Cache, opts *TextOptions) ml.Tensor { func (d *TextLayer) Forward(ctx ml.Context, hiddenStates, positions, outputs ml.Tensor, cache kvcache.Cache, opts *TextOptions) ml.Tensor {
residual := hiddenStates residual := hiddenStates
hiddenStates = d.AttentionNorm.Forward(ctx, hiddenStates, opts.eps) hiddenStates = d.AttentionNorm.Forward(ctx, hiddenStates, opts.eps)
hiddenStates = d.TextAttention.Forward(ctx, hiddenStates, cos, sin, cache, opts) hiddenStates = d.TextAttention.Forward(ctx, hiddenStates, positions, cache, opts)
if outputs != nil { if outputs != nil {
hiddenStates = hiddenStates.Rows(ctx, outputs) hiddenStates = hiddenStates.Rows(ctx, outputs)
@ -153,42 +159,6 @@ type TextModel struct {
Options *TextOptions Options *TextOptions
} }
func (m *TextModel) rotaryEmbedding(ctx ml.Context, positions ml.Tensor) (_, _ ml.Tensor) {
positions = positions.Reshape(ctx, 1, positions.Dim(0), positions.Dim(1))
if len(m.Options.inverseFrequenciesCache) == 0 {
m.Options.inverseFrequenciesCache = make([]float32, m.Options.headDim()/2)
for i := range m.Options.inverseFrequenciesCache {
frequency := float32(math.Pow(float64(m.Options.ropeBase), float64(i*2)/float64(m.Options.headDim())))
m.Options.inverseFrequenciesCache[i] = 1 / frequency
}
}
inverseFrequencies := ctx.Input().FromFloats(m.Options.inverseFrequenciesCache, 1, len(m.Options.inverseFrequenciesCache))
positions = positions.Cast(ctx, ml.DTypeF32)
frequencies := inverseFrequencies.Mulmat(ctx, positions)
interleaved := frequencies.View(ctx,
0, frequencies.Dim(0),
frequencies.Stride(1), frequencies.Dim(1),
)
for _, i := range []int{1, 2} {
args := []int{
i * frequencies.Stride(0), 1,
3 * frequencies.Stride(0), m.Options.mropeSections[i],
frequencies.Stride(1), frequencies.Dim(1),
}
ctx.Forward(frequencies.View(ctx, i*frequencies.Stride(2)+args[0], args[1:]...).
Copy(ctx, interleaved.View(ctx, args[0], args[1:]...)))
}
interleaved = interleaved.Concat(ctx, interleaved, 0)
interleaved = interleaved.Reshape(ctx, interleaved.Dim(0), 1, interleaved.Dim(1), interleaved.Dim(2))
return interleaved.Cos(ctx), interleaved.Sin(ctx)
}
var _ model.Model = (*Model)(nil) var _ model.Model = (*Model)(nil)
func newTextModel(c fs.Config) *TextModel { func newTextModel(c fs.Config) *TextModel {