Skip to content

refactor: remove ununsed encode_video #1332

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Merged
leejet merged 1 commit into from
Mar 9, 2026
Merged

refactor: remove ununsed encode_video #1332

Changes from all commits
Commits
Show all changes
1 commit
Select commit
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
12 changes: 6 additions & 6 deletions src/stable-diffusion.cpp
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -2526,14 +2526,14 @@ class StableDiffusionGGML {
tile_size_y = get_tile_size(params.tile_size_y, params.rel_size_y, latent_y);
}

ggml_tensor* vae_encode(ggml_context* work_ctx, ggml_tensor* x, bool encode_video = false) {
ggml_tensor* vae_encode(ggml_context* work_ctx, ggml_tensor* x) {
int64_t t0 = ggml_time_ms();
ggml_tensor* result = nullptr;
const int vae_scale_factor = get_vae_scale_factor();
int64_t W = x->ne[0] / vae_scale_factor;
int64_t H = x->ne[1] / vae_scale_factor;
int64_t C = get_latent_channel();
if (vae_tiling_params.enabled && !encode_video) {
if (vae_tiling_params.enabled) {
// TODO wan2.2 vae support?
int64_t ne2;
int64_t ne3;
Expand Down Expand Up @@ -2561,7 +2561,7 @@ class StableDiffusionGGML {

if (!use_tiny_autoencoder) {
process_vae_input_tensor(x);
if (vae_tiling_params.enabled && !encode_video) {
if (vae_tiling_params.enabled) {
float tile_overlap;
int tile_size_x, tile_size_y;
// multiply tile size for encode to keep the compute buffer size consistent
Expand All @@ -2578,7 +2578,7 @@ class StableDiffusionGGML {
}
first_stage_model->free_compute_buffer();
} else {
if (vae_tiling_params.enabled && !encode_video) {
if (vae_tiling_params.enabled) {
// split latent in 32x32 tiles and compute in several steps
auto on_tiling = [&](ggml_tensor* in, ggml_tensor* out, bool init) {
return tae_first_stage->compute(n_threads, in, false, &out, nullptr);
Expand Down Expand Up @@ -2654,8 +2654,8 @@ class StableDiffusionGGML {
return latent;
}

ggml_tensor* encode_first_stage(ggml_context* work_ctx, ggml_tensor* x, bool encode_video = false) {
ggml_tensor* vae_output = vae_encode(work_ctx, x, encode_video);
ggml_tensor* encode_first_stage(ggml_context* work_ctx, ggml_tensor* x) {
ggml_tensor* vae_output = vae_encode(work_ctx, x);
return get_first_stage_encoding(work_ctx, vae_output);
}

Expand Down
Loading