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model: add support for qwen3vl series (#16780)

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* support qwen3vl series.

Co-authored-by: Thireus ☠ <Thireus@users.noreply.github.com>
Co-authored-by: yairpatch <yairpatch@users.noreply.github.com>
Co-authored-by: LETS-BEE <LETS-BEE@users.noreply.github.com>

* bugfix: fix the arch check for qwen3vl-moe.

* use build_ffn

* optimize deepstack structure

* optimize deepstack feature saving

* Revert "optimize deepstack feature saving" for temporal fix

This reverts commit f321b9fdf1.

* code clean

* use fused qkv in clip

* clean up / rm is_deepstack_layers for simplification

* add test model

* move test model to "big" section

* fix imrope check

* remove trailing whitespace

* fix rope fail

* metal : add imrope support

* add imrope support for sycl

* vulkan: add imrope w/o check

* fix vulkan

* webgpu: add imrope w/o check

* Update gguf-py/gguf/tensor_mapping.py

Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@scala.com>

* fix tensor mapping

---------

Co-authored-by: Thireus ☠ <Thireus@users.noreply.github.com>
Co-authored-by: yairpatch <yairpatch@users.noreply.github.com>
Co-authored-by: LETS-BEE <LETS-BEE@users.noreply.github.com>
Co-authored-by: Xuan Son Nguyen <son@huggingface.co>
Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@scala.com>
This commit is contained in:
JJJYmmm
2025-10-30 23:19:14 +08:00
committed by GitHub
parent dcca0d3ab8
commit d261223d24
28 changed files with 1125 additions and 97 deletions
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47
ggml/src/ggml-cuda/rope.cu
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@@ -125,7 +125,7 @@ template<bool forward, bool has_ff, typename T>
static __global__ void rope_multi(
const T * x, T * dst, const int ne0, const int ne1, const int ne2, const int s1, const int s2,
const int n_dims, const int32_t * pos, const float freq_scale, const float ext_factor, const float attn_factor,
const rope_corr_dims corr_dims, const float theta_scale, const float * freq_factors, const mrope_sections sections) {
const rope_corr_dims corr_dims, const float theta_scale, const float * freq_factors, const mrope_sections sections, const bool is_imrope) {
const int i0 = 2*(blockDim.y*blockIdx.y + threadIdx.y);
if (i0 >= ne0) {
@@ -152,17 +152,29 @@ static __global__ void rope_multi(
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) {
theta_base = pos[channel_x + ne2 * 1]*powf(theta_scale, i0/2.0f);
}
else if (sector >= sec_w && sector < sec_w + 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);
if (is_imrope) {
if (sector % 3 == 1 && sector < 3 * sections.v[1]) { // h
theta_base = pos[channel_x + ne2 * 1]*powf(theta_scale, i0/2.0f);
} else if (sector % 3 == 2 && sector < 3 * sections.v[2]) { // w
theta_base = pos[channel_x + ne2 * 2]*powf(theta_scale, i0/2.0f);
} else if (sector % 3 == 0 && sector < 3 * sections.v[0]) { // t
theta_base = pos[channel_x]*powf(theta_scale, i0/2.0f);
} else {
theta_base = pos[channel_x + ne2 * 3]*powf(theta_scale, i0/2.0f);
}
} else {
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) {
theta_base = pos[channel_x + ne2 * 1]*powf(theta_scale, i0/2.0f);
}
else if (sector >= sec_w && sector < sec_w + 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;
@@ -276,7 +288,7 @@ template<bool forward, typename T>
static void rope_multi_cuda(
const T * x, T * dst, const int ne0, const int ne1, const int ne2, const int s1, const int s2, const int n_dims, const int nr,
const int32_t * pos, const float freq_scale, const float freq_base, const float ext_factor, const float attn_factor,
const rope_corr_dims corr_dims, const float * freq_factors, const mrope_sections sections, cudaStream_t stream) {
const rope_corr_dims corr_dims, const float * freq_factors, const mrope_sections sections, const bool is_imrope, cudaStream_t stream) {
GGML_ASSERT(ne0 % 2 == 0);
const dim3 block_dims(1, CUDA_ROPE_BLOCK_SIZE, 1);
const int n_blocks_x = (ne0 + 2*CUDA_ROPE_BLOCK_SIZE - 1) / (2*CUDA_ROPE_BLOCK_SIZE);
@@ -287,11 +299,11 @@ static void rope_multi_cuda(
if (freq_factors == nullptr) {
rope_multi<forward, false, T><<<block_nums, block_dims, 0, stream>>>(
x, dst, ne0, ne1, ne2, s1, s2, n_dims, pos, freq_scale, ext_factor,
attn_factor, corr_dims, theta_scale, freq_factors, sections);
attn_factor, corr_dims, theta_scale, freq_factors, sections, is_imrope);
} else {
rope_multi<forward, true, T><<<block_nums, block_dims, 0, stream>>>(
x, dst, ne0, ne1, ne2, s1, s2, n_dims, pos, freq_scale, ext_factor,
attn_factor, corr_dims, theta_scale, freq_factors, sections);
attn_factor, corr_dims, theta_scale, freq_factors, sections, is_imrope);
}
}
@@ -369,6 +381,7 @@ void ggml_cuda_op_rope_impl(ggml_backend_cuda_context & ctx, ggml_tensor * dst)
const bool is_neox = mode & GGML_ROPE_TYPE_NEOX;
const bool is_mrope = mode & GGML_ROPE_TYPE_MROPE;
const bool is_imrope = mode == GGML_ROPE_TYPE_IMROPE;
const bool is_vision = mode == GGML_ROPE_TYPE_VISION;
if (is_mrope) {
@@ -406,11 +419,11 @@ void ggml_cuda_op_rope_impl(ggml_backend_cuda_context & ctx, ggml_tensor * dst)
if (src0->type == GGML_TYPE_F32) {
rope_multi_cuda<forward>(
(const float *) src0_d, (float *) dst_d, ne00, ne01, ne02, s01, s02, n_dims, nr, pos, freq_scale,
freq_base, ext_factor, attn_factor, corr_dims, freq_factors, sections, stream);
freq_base, ext_factor, attn_factor, corr_dims, freq_factors, sections, is_imrope, stream);
} else if (src0->type == GGML_TYPE_F16) {
rope_multi_cuda<forward>(
(const half *) src0_d, (half *) dst_d, ne00, ne01, ne02, s01, s02, n_dims, nr, pos, freq_scale,
freq_base, ext_factor, attn_factor, corr_dims, freq_factors, sections, stream);
freq_base, ext_factor, attn_factor, corr_dims, freq_factors, sections, is_imrope, stream);
} else {
GGML_ABORT("fatal error");
}