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parent
75e75d9afe
commit
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113
llama/patches/0032-interleave-multi-rope.patch
Normal file
113
llama/patches/0032-interleave-multi-rope.patch
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@ -0,0 +1,113 @@
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From 0000000000000000000000000000000000000000 Mon Sep 17 00:00:00 2001
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From: Michael Yang <git@mxy.ng>
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Date: Web, 16 Oct 2025 20:37:19 -0700
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Subject: [PATCH] interleave multi rope
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since ollama doesn't use mrope for anything else, change it to mean the
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interleaved version used for qwen3vl
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---
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ggml/src/ggml-cpu/ops.cpp | 7 ++-----
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ggml/src/ggml-cuda/rope.cu | 12 +++---------
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ggml/src/ggml-metal/ggml-metal.metal | 10 +++-------
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ggml/src/ggml-vulkan/vulkan-shaders/rope_multi.comp | 12 +++---------
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4 files changed, 11 insertions(+), 30 deletions(-)
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diff --git a/ggml/src/ggml-cpu/ops.cpp b/ggml/src/ggml-cpu/ops.cpp
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index 31478dd8e..4d1ed207e 100644
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--- a/ggml/src/ggml-cpu/ops.cpp
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+++ b/ggml/src/ggml-cpu/ops.cpp
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@@ -5509,15 +5509,12 @@ static void ggml_mrope_cache_init(
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}
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float theta = theta_t;
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- if (sector >= sections[0] && sector < sec_w) {
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+ if (sector % 3 == 1 && sector < 1 + 3 * sections[1]) {
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theta = theta_h;
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}
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- else if (sector >= sec_w && sector < sec_w + sections[2]) {
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+ else if (sector % 3 == 2 && sector < 2 + 3 * sections[2]) {
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theta = theta_w;
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}
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- else if (sector >= sec_w + sections[2]) {
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- theta = theta_e;
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- }
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rope_yarn(
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theta/ff, freq_scale, corr_dims, i0, ext_factor, mscale, &cache[i0 + 0], &cache[i0 + 1]
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diff --git a/ggml/src/ggml-cuda/rope.cu b/ggml/src/ggml-cuda/rope.cu
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index d058504cd..287fe9d2c 100644
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--- a/ggml/src/ggml-cuda/rope.cu
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+++ b/ggml/src/ggml-cuda/rope.cu
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@@ -151,19 +151,13 @@ static __global__ void rope_multi(
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const int sec_w = sections.v[1] + sections.v[0];
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const int sector = (i0 / 2) % sect_dims;
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- float theta_base = 0.0;
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- if (sector < sections.v[0]) {
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- theta_base = pos[channel_x]*powf(theta_scale, i0/2.0f);
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- }
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- else if (sector >= sections.v[0] && sector < sec_w) {
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+ float theta_base = pos[channel_x]*powf(theta_scale, i0/2.0f);
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+ if (sector % 3 == 1 && sector < 1 + 3 * sections.v[1]) {
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theta_base = pos[channel_x + ne2 * 1]*powf(theta_scale, i0/2.0f);
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}
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- else if (sector >= sec_w && sector < sec_w + sections.v[2]) {
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+ else if (sector % 3 == 2 && sector < 2 + 3 * sections.v[2]) {
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theta_base = pos[channel_x + ne2 * 2]*powf(theta_scale, i0/2.0f);
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}
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- else if (sector >= sec_w + sections.v[2]) {
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- theta_base = pos[channel_x + ne2 * 3]*powf(theta_scale, i0/2.0f);
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- }
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const float freq_factor = has_ff ? freq_factors[i0/2] : 1.0f;
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diff --git a/ggml/src/ggml-metal/ggml-metal.metal b/ggml/src/ggml-metal/ggml-metal.metal
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index 375a0c7fd..9866c96b4 100644
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--- a/ggml/src/ggml-metal/ggml-metal.metal
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+++ b/ggml/src/ggml-metal/ggml-metal.metal
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@@ -3858,15 +3858,11 @@ kernel void kernel_rope_multi(
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const int sec_w012 = args.sect_0 + args.sect_1 + args.sect_2; // end of section 2
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const int sector = ic % sect_dims;
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- float theta_base;
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- if (sector < args.sect_0) {
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- theta_base = (float) pos[i2];
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- } else if (sector < sec_w01) {
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+ float theta_base = (float) pos[i2];
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+ if (sector % 3 == 1 && sector < 1 + 3 * args.sect_1) {
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theta_base = (float) pos[i2 + args.ne02];
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- } else if (sector < sec_w012) {
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+ } else if (sector % 3 == 2 && sector < 2 + 3 * args.sect_2) {
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theta_base = (float) pos[i2 + args.ne02 * 2];
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- } else {
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- theta_base = (float) pos[i2 + args.ne02 * 3];
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}
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// end of mrope
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diff --git a/ggml/src/ggml-vulkan/vulkan-shaders/rope_multi.comp b/ggml/src/ggml-vulkan/vulkan-shaders/rope_multi.comp
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index 111286b49..6fc2b42f8 100644
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--- a/ggml/src/ggml-vulkan/vulkan-shaders/rope_multi.comp
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+++ b/ggml/src/ggml-vulkan/vulkan-shaders/rope_multi.comp
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@@ -31,19 +31,13 @@ void main() {
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const int sec_w = p.sections[1] + p.sections[0];
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const uint sector = (i0 / 2) % sect_dims;
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- float theta_base = 0.0;
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- if (sector < p.sections[0]) {
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- theta_base = data_pos[channel_x]*pow(p.theta_scale, i0/2.0f);
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- }
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- else if (sector >= p.sections[0] && sector < sec_w) {
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+ float theta_base = data_pos[channel_x]*pow(p.theta_scale, i0/2.0f);
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+ if (sector % 3 == 1 && sector < 1 + 3 * p.sections[1]) {
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theta_base = data_pos[channel_x + ne2 * 1]*pow(p.theta_scale, i0/2.0f);
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}
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- else if (sector >= sec_w && sector < sec_w + p.sections[2]) {
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+ else if (sector % 3 == 2 && sector < 2 + 3 * p.sections[2]) {
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theta_base = data_pos[channel_x + ne2 * 2]*pow(p.theta_scale, i0/2.0f);
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}
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- else if (sector >= sec_w + p.sections[2]) {
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- theta_base = data_pos[channel_x + ne2 * 3]*pow(p.theta_scale, i0/2.0f);
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- }
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const float freq_factor = p.has_ff != 0 ? data_ff[i0/2] : 1.0f;
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@ -11,6 +11,7 @@ package ggml
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import "C"
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import "C"
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import (
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import (
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"cmp"
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"context"
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"context"
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"encoding/binary"
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"encoding/binary"
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"errors"
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"errors"
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@ -1490,14 +1491,7 @@ func (t *Tensor) View(ctx ml.Context, offset int, shape ...int) ml.Tensor {
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func (t *Tensor) RoPE(ctx ml.Context, positions ml.Tensor, ropeDim int, ropeBase, ropeScale float32, options ...func(*rope.Options)) ml.Tensor {
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func (t *Tensor) RoPE(ctx ml.Context, positions ml.Tensor, ropeDim int, ropeBase, ropeScale float32, options ...func(*rope.Options)) ml.Tensor {
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// Default options
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// Default options
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opts := rope.Options{
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opts := rope.Options{Factors: &Tensor{}}
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Factors: &Tensor{},
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OriginalContextLength: 131072,
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ExtrapolationFactor: 0.,
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AttentionFactor: 1.,
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BetaFast: 32.,
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BetaSlow: 1.,
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}
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// Apply any provided options
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// Apply any provided options
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for _, option := range options {
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for _, option := range options {
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@ -1509,24 +1503,44 @@ func (t *Tensor) RoPE(ctx ml.Context, positions ml.Tensor, ropeDim int, ropeBase
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dequant = C.ggml_cast(ctx.(*Context).ctx, t.t, C.GGML_TYPE_F32)
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dequant = C.ggml_cast(ctx.(*Context).ctx, t.t, C.GGML_TYPE_F32)
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}
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}
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return &Tensor{
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var tt *C.struct_ggml_tensor
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b: t.b,
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if len(opts.MRoPE.Sections) > 0 {
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t: C.ggml_rope_ext(
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mropeSections := make([]C.int32_t, 4)
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for i, section := range opts.MRoPE.Sections {
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mropeSections[i] = C.int32_t(section)
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}
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tt = C.ggml_rope_multi(
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ctx.(*Context).ctx,
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ctx.(*Context).ctx,
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dequant,
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dequant,
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positions.(*Tensor).t,
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positions.(*Tensor).t,
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opts.Factors.(*Tensor).t,
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opts.Factors.(*Tensor).t,
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C.int(ropeDim),
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C.int(ropeDim),
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unsafe.SliceData(mropeSections),
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C.int(opts.Type),
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C.int(opts.Type),
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C.int(opts.OriginalContextLength),
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cmp.Or(C.int(opts.YaRN.OriginalContextLength), 128<<10),
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C.float(ropeBase),
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C.float(ropeBase), C.float(ropeScale),
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C.float(ropeScale),
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C.float(opts.YaRN.ExtrapolationFactor),
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C.float(opts.ExtrapolationFactor),
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cmp.Or(C.float(opts.YaRN.AttentionFactor), 1),
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C.float(opts.AttentionFactor),
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cmp.Or(C.float(opts.YaRN.BetaFast), 32),
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C.float(opts.BetaFast),
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cmp.Or(C.float(opts.YaRN.BetaSlow), 1),
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C.float(opts.BetaSlow),
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)
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),
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} else {
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tt = C.ggml_rope_ext(
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ctx.(*Context).ctx,
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dequant,
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positions.(*Tensor).t,
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opts.Factors.(*Tensor).t,
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C.int(ropeDim), C.int(opts.Type),
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cmp.Or(C.int(opts.YaRN.OriginalContextLength), 128<<10),
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C.float(ropeBase), C.float(ropeScale),
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C.float(opts.YaRN.ExtrapolationFactor),
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cmp.Or(C.float(opts.YaRN.AttentionFactor), 1),
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cmp.Or(C.float(opts.YaRN.BetaFast), 32),
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cmp.Or(C.float(opts.YaRN.BetaSlow), 1),
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)
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}
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}
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return &Tensor{b: t.b, t: tt}
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}
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}
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func (t *Tensor) IM2Col(ctx ml.Context, t2 ml.Tensor, s0, s1, p0, p1, d0, d1 int) ml.Tensor {
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func (t *Tensor) IM2Col(ctx ml.Context, t2 ml.Tensor, s0, s1, p0, p1, d0, d1 int) ml.Tensor {
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7
ml/backend/ggml/ggml/src/ggml-cpu/ops.cpp
vendored
7
ml/backend/ggml/ggml/src/ggml-cpu/ops.cpp
vendored
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@ -5509,15 +5509,12 @@ static void ggml_mrope_cache_init(
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}
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}
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float theta = theta_t;
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float theta = theta_t;
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if (sector >= sections[0] && sector < sec_w) {
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if (sector % 3 == 1 && sector < 1 + 3 * sections[1]) {
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theta = theta_h;
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theta = theta_h;
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}
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}
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else if (sector >= sec_w && sector < sec_w + sections[2]) {
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else if (sector % 3 == 2 && sector < 2 + 3 * sections[2]) {
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theta = theta_w;
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theta = theta_w;
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}
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}
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else if (sector >= sec_w + sections[2]) {
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theta = theta_e;
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}
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rope_yarn(
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rope_yarn(
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theta/ff, freq_scale, corr_dims, i0, ext_factor, mscale, &cache[i0 + 0], &cache[i0 + 1]
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theta/ff, freq_scale, corr_dims, i0, ext_factor, mscale, &cache[i0 + 0], &cache[i0 + 1]
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12
ml/backend/ggml/ggml/src/ggml-cuda/rope.cu
vendored
12
ml/backend/ggml/ggml/src/ggml-cuda/rope.cu
vendored
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@ -151,19 +151,13 @@ static __global__ void rope_multi(
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const int sec_w = sections.v[1] + sections.v[0];
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const int sec_w = sections.v[1] + sections.v[0];
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const int sector = (i0 / 2) % sect_dims;
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const int sector = (i0 / 2) % sect_dims;
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float theta_base = 0.0;
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float theta_base = pos[channel_x]*powf(theta_scale, i0/2.0f);
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if (sector < sections.v[0]) {
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if (sector % 3 == 1 && sector < 1 + 3 * sections.v[1]) {
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theta_base = pos[channel_x]*powf(theta_scale, i0/2.0f);
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}
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else if (sector >= sections.v[0] && sector < sec_w) {
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theta_base = pos[channel_x + ne2 * 1]*powf(theta_scale, i0/2.0f);
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theta_base = pos[channel_x + ne2 * 1]*powf(theta_scale, i0/2.0f);
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}
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}
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else if (sector >= sec_w && sector < sec_w + sections.v[2]) {
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else if (sector % 3 == 2 && sector < 2 + 3 * sections.v[2]) {
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theta_base = pos[channel_x + ne2 * 2]*powf(theta_scale, i0/2.0f);
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theta_base = pos[channel_x + ne2 * 2]*powf(theta_scale, i0/2.0f);
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}
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}
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else if (sector >= sec_w + sections.v[2]) {
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theta_base = pos[channel_x + ne2 * 3]*powf(theta_scale, i0/2.0f);
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}
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const float freq_factor = has_ff ? freq_factors[i0/2] : 1.0f;
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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(
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const int sec_w012 = args.sect_0 + args.sect_1 + args.sect_2; // end of section 2
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const int sec_w012 = args.sect_0 + args.sect_1 + args.sect_2; // end of section 2
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const int sector = ic % sect_dims;
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const int sector = ic % sect_dims;
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float theta_base;
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float theta_base = (float) pos[i2];
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if (sector < args.sect_0) {
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if (sector % 3 == 1 && sector < 1 + 3 * args.sect_1) {
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theta_base = (float) pos[i2];
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} else if (sector < sec_w01) {
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theta_base = (float) pos[i2 + args.ne02];
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theta_base = (float) pos[i2 + args.ne02];
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} else if (sector < sec_w012) {
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} else if (sector % 3 == 2 && sector < 2 + 3 * args.sect_2) {
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theta_base = (float) pos[i2 + args.ne02 * 2];
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theta_base = (float) pos[i2 + args.ne02 * 2];
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} else {
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theta_base = (float) pos[i2 + args.ne02 * 3];
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}
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}
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// end of mrope
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// end of mrope
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@ -3858,15 +3858,11 @@ kernel void kernel_rope_multi(
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const int sec_w012 = args.sect_0 + args.sect_1 + args.sect_2; // end of section 2
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const int sec_w012 = args.sect_0 + args.sect_1 + args.sect_2; // end of section 2
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const int sector = ic % sect_dims;
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const int sector = ic % sect_dims;
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float theta_base;
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float theta_base = (float) pos[i2];
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if (sector < args.sect_0) {
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if (sector % 3 == 1 && sector < 1 + 3 * args.sect_1) {
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theta_base = (float) pos[i2];
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} else if (sector < sec_w01) {
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theta_base = (float) pos[i2 + args.ne02];
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theta_base = (float) pos[i2 + args.ne02];
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} else if (sector < sec_w012) {
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} else if (sector % 3 == 2 && sector < 2 + 3 * args.sect_2) {
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theta_base = (float) pos[i2 + args.ne02 * 2];
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theta_base = (float) pos[i2 + args.ne02 * 2];
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} else {
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theta_base = (float) pos[i2 + args.ne02 * 3];
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}
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}
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// end of mrope
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// end of mrope
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@ -31,19 +31,13 @@ void main() {
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const int sec_w = p.sections[1] + p.sections[0];
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const int sec_w = p.sections[1] + p.sections[0];
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const uint sector = (i0 / 2) % sect_dims;
|
const uint sector = (i0 / 2) % sect_dims;
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|
|
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float theta_base = 0.0;
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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) {
|
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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;
|
||||||
|
|
||||||
|
|
|
||||||
|
|
@ -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
|
||||||
}
|
}
|
||||||
}
|
}
|
||||||
|
|
|
||||||
|
|
@ -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
|
||||||
}
|
}
|
||||||
|
|
|
||||||
|
|
@ -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 {
|
||||||
|
|
|
||||||
Loading…
Reference in New Issue
Block a user