DarthAffe/stable-diffusion.cpp
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feat: add taeh3 support (#1874)

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stduhpf 2026-08-19 16:18:19 +02:00 committed by GitHub
parent de298c225b
commit 6100d8339b
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2 changed files with 115 additions and 12 deletions
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113
src/model/vae/tae.hpp
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@ -426,10 +426,10 @@ class TinyVideoDecoder : public UnaryBlock {
static const int num_layers = 3; static const int num_layers = 3;
int channels[num_layers + 1] = {256, 128, 64, 64}; int channels[num_layers + 1] = {256, 128, 64, 64};
int patch_size = 1; int patch_size = 1;
int t_upscale = 1;
bool is_wide = false; bool is_wide = false;
public: public:
int t_upscale = 1;
TinyVideoDecoder(int z_channels = 4, int patch_size = 1, std::vector<bool> time_upscale = {false, true, true}, bool is_wide = false) TinyVideoDecoder(int z_channels = 4, int patch_size = 1, std::vector<bool> time_upscale = {false, true, true}, bool is_wide = false)
: z_channels(z_channels), patch_size(patch_size), is_wide(is_wide) { : z_channels(z_channels), patch_size(patch_size), is_wide(is_wide) {
t_upscale = 1; t_upscale = 1;
@ -536,6 +536,10 @@ public:
patch = 4; patch = 4;
time_downscale = {true, true, true}; time_downscale = {true, true, true};
time_upscale = {true, true, true}; time_upscale = {true, true, true};
} else if (sd_version_is_minimax_h3(version)) {
z_channels = 24;
patch = 2;
time_downscale = {true, true, false};
} }
blocks["decoder"] = std::shared_ptr<GGMLBlock>(new TinyVideoDecoder(z_channels, patch, time_upscale, is_wide)); blocks["decoder"] = std::shared_ptr<GGMLBlock>(new TinyVideoDecoder(z_channels, patch, time_upscale, is_wide));
if (!decode_only) { if (!decode_only) {
@ -545,24 +549,123 @@ public:
ggml_tensor* decode(GGMLRunnerContext* ctx, ggml_tensor* z) { ggml_tensor* decode(GGMLRunnerContext* ctx, ggml_tensor* z) {
auto decoder = std::dynamic_pointer_cast<TinyVideoDecoder>(blocks["decoder"]); auto decoder = std::dynamic_pointer_cast<TinyVideoDecoder>(blocks["decoder"]);
if (sd_version_is_wan(version) || sd_version_is_hunyuan_video(version) || sd_version_is_ltxav(version)) { if (sd_version_is_wan(version) || sd_version_is_hunyuan_video(version) || sd_version_is_ltxav(version) || sd_version_is_minimax_h3(version)) {
// (W, H, C, T) -> (W, H, T, C) // (W, H, C, T) -> (W, H, T, C)
z = ggml_cont(ctx->ggml_ctx, ggml_permute(ctx->ggml_ctx, z, 0, 1, 3, 2)); z = ggml_cont(ctx->ggml_ctx, ggml_permute(ctx->ggml_ctx, z, 0, 1, 3, 2));
} }
auto result = decoder->forward(ctx, z); auto result = decoder->forward(ctx, z);
if (sd_version_is_wan(version) || sd_version_is_hunyuan_video(version) || sd_version_is_ltxav(version)) {
if (sd_version_is_minimax_h3(version)) {
int64_t num_frames = result->ne[3];
int64_t chunk_frames = 5 * decoder->t_upscale;
int64_t pad = (chunk_frames - (num_frames % chunk_frames)) % chunk_frames;
result = ggml_ext_pad_ext(ctx->ggml_ctx, ctx->backend, result, 0, 0, 0, 0, 0, 0, 0, pad, false, false);
int64_t num_chunks = (num_frames + pad) / chunk_frames;
auto to_trim = decoder->t_upscale - 1;
std::vector<ggml_tensor*> to_concat = {};
for (int i = 0; i < num_chunks; i++) {
auto chunk = ggml_view_4d(ctx->ggml_ctx, result,
result->ne[0], result->ne[1], result->ne[2], chunk_frames - to_trim,
result->nb[1], result->nb[2], result->nb[3],
i * chunk_frames * result->nb[3]);
to_concat.push_back(chunk);
}
result = ggml_ext_vec_concat(ctx->ggml_ctx, to_concat, 3);
result = ggml_view_4d(ctx->ggml_ctx, result,
result->ne[0], result->ne[1], result->ne[2],
result->ne[3] - decoder->t_upscale * 3,
result->nb[1], result->nb[2], result->nb[3], 0);
}
if (sd_version_is_wan(version) || sd_version_is_hunyuan_video(version) || sd_version_is_ltxav(version) || sd_version_is_minimax_h3(version)) {
// (W, H, T, C) -> (W, H, C, T) // (W, H, T, C) -> (W, H, C, T)
result = ggml_cont(ctx->ggml_ctx, ggml_permute(ctx->ggml_ctx, result, 0, 1, 3, 2)); result = ggml_cont(ctx->ggml_ctx, ggml_permute(ctx->ggml_ctx, result, 0, 1, 3, 2));
} }
return result; return result;
} }
ggml_tensor* encode(GGMLRunnerContext* ctx, ggml_tensor* x) { ggml_tensor* encode_h3(GGMLRunnerContext* ctx, ggml_tensor* x) {
auto encoder = std::dynamic_pointer_cast<TinyVideoEncoder>(blocks["encoder"]); auto encoder = std::dynamic_pointer_cast<TinyVideoEncoder>(blocks["encoder"]);
if (sd_version_is_wan(version) || sd_version_is_hunyuan_video(version) || sd_version_is_ltxav(version)) {
int64_t num_frames = x->ne[3];
int64_t pad = (17 - (num_frames % 17)) % 17;
if (pad > 0) {
auto last_frame = ggml_view_4d(ctx->ggml_ctx, x,
x->ne[0], x->ne[1], x->ne[2], 1,
x->nb[1], x->nb[2], x->nb[3],
(num_frames - 1) * x->nb[3]);
for (int i = 0; i < pad; i++) {
x = ggml_concat(ctx->ggml_ctx, x, last_frame, 3);
}
}
int64_t T_padded = x->ne[3];
int64_t num_chunks = T_padded / 17;
auto zero_frame = ggml_view_4d(ctx->ggml_ctx, x,
x->ne[0], x->ne[1], x->ne[2], 1,
x->nb[1], x->nb[2], x->nb[3], 0);
auto zeros_1 = ggml_scale(ctx->ggml_ctx, ggml_cont(ctx->ggml_ctx, zero_frame), 0.0f);
auto zeros_3 = zeros_1;
for (int i = 1; i < 3; i++) {
zeros_3 = ggml_concat(ctx->ggml_ctx, zeros_3, zeros_1, 3);
}
ggml_tensor* out = nullptr;
if (false) {
std::vector<ggml_tensor*> to_concat = {};
for (int i = 0; i < num_chunks; i++) {
auto chunk = ggml_view_4d(ctx->ggml_ctx, x,
x->ne[0], x->ne[1], x->ne[2], 17,
x->nb[1], x->nb[2], x->nb[3],
i * 17 * x->nb[3]);
auto chunk_padded = ggml_concat(ctx->ggml_ctx, zeros_3, chunk, 3);
to_concat.push_back(chunk_padded);
}
ggml_tensor* x_in = ggml_ext_vec_concat(ctx->ggml_ctx, to_concat, 3);
out = encoder->forward(ctx, x_in);
} else {
std::vector<ggml_tensor*> to_concat = {};
for (int i = 0; i < num_chunks; i++) {
auto chunk = ggml_view_4d(ctx->ggml_ctx, x,
x->ne[0], x->ne[1], x->ne[2], 17,
x->nb[1], x->nb[2], x->nb[3],
i * 17 * x->nb[3]);
auto chunk_padded = ggml_concat(ctx->ggml_ctx, zeros_3, chunk, 3);
auto chunk_out = encoder->forward(ctx, chunk_padded);
// auto chunk_out = encoder->forward_seq(ctx, chunk_padded); // ~same vram usage, and straight-up slower. it's already sequential enough
to_concat.push_back(chunk_out);
}
out = ggml_ext_vec_concat(ctx->ggml_ctx, to_concat, 3);
}
// Return x[:, :-3] - drop the last 3 elements in the T dimension
int64_t out_T = out->ne[3];
out = ggml_view_4d(ctx->ggml_ctx, out,
out->ne[0], out->ne[1], out->ne[2], out_T - 3,
out->nb[1], out->nb[2], out->nb[3], 0);
return ggml_cont(ctx->ggml_ctx, ggml_permute(ctx->ggml_ctx, out, 0, 1, 3, 2));
}
ggml_tensor* encode(GGMLRunnerContext* ctx, ggml_tensor* x) {
if (sd_version_is_wan(version) || sd_version_is_hunyuan_video(version) || sd_version_is_ltxav(version) || (sd_version_is_minimax_h3(version) && x->ne[3] > 1)) {
// (W, H, T, C) -> (W, H, C, T) // (W, H, T, C) -> (W, H, C, T)
x = ggml_cont(ctx->ggml_ctx, ggml_permute(ctx->ggml_ctx, x, 0, 1, 3, 2)); x = ggml_cont(ctx->ggml_ctx, ggml_permute(ctx->ggml_ctx, x, 0, 1, 3, 2));
} }
if (sd_version_is_minimax_h3(version)) {
return encode_h3(ctx, x);
}
auto encoder = std::dynamic_pointer_cast<TinyVideoEncoder>(blocks["encoder"]);
int64_t num_frames = x->ne[3]; int64_t num_frames = x->ne[3];
if (num_frames % encoder->t_downscale) { if (num_frames % encoder->t_downscale) {
// pad to multiple of encoder->t_downscale at the end // pad to multiple of encoder->t_downscale at the end

12
src/stable-diffusion.cpp
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@ -1023,11 +1023,11 @@ public:
tae_preview_only = false; tae_preview_only = false;
use_tae = true; use_tae = true;
} }
if (sd_version_is_minimax_h3(version) && use_tae) { // if (sd_version_is_minimax_h3(version) && use_tae) {
LOG_WARN("MiniMax-H3 does not have a compatible TAE; ignoring --taesd"); // LOG_WARN("MiniMax-H3 does not have a compatible TAE; ignoring --taesd");
tae_preview_only = false; // tae_preview_only = false;
use_tae = false; // use_tae = false;
} // }
auto& tensor_storage_map = model_loader.get_tensor_storage_map(); auto& tensor_storage_map = model_loader.get_tensor_storage_map();
@ -1402,7 +1402,7 @@ public:
} }
auto create_tae = [&](bool decode_only) -> std::shared_ptr<VAE> { auto create_tae = [&](bool decode_only) -> std::shared_ptr<VAE> {
if (sd_version_uses_wan_vae(version) || sd_version_is_hunyuan_video(version) || sd_version_is_ltxav(version)) { if (sd_version_uses_wan_vae(version) || sd_version_is_hunyuan_video(version) || sd_version_is_ltxav(version) || sd_version_is_minimax_h3(version)) {
return std::make_shared<TinyVideoAutoEncoder>(backend_for(SDBackendModule::VAE), return std::make_shared<TinyVideoAutoEncoder>(backend_for(SDBackendModule::VAE),
tensor_storage_map, tensor_storage_map,
"decoder", "decoder",