DarthAffe/stable-diffusion.cpp
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feat: introduce GGMLBlock and implement SVD(Broken) (#159)

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* introduce GGMLBlock and implement SVD(Broken)

* add sdxl vae warning
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leejet authored and GitHub committed 2024-02-24 20:06:39 +08:00
1 parent 349439f239
commit b6368868d9
20 files changed
+4137 -3818
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upscaler.cpp
+8 -11
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@@ -6,7 +6,7 @@
struct UpscalerGGML {
ggml_backend_t backend = NULL; // general backend
ggml_type model_data_type = GGML_TYPE_F16;
ESRGAN esrgan_upscaler;
std::shared_ptr<ESRGAN> esrgan_upscaler;
std::string esrgan_path;
int n_threads;
@@ -30,7 +30,8 @@ struct UpscalerGGML {
backend = ggml_backend_cpu_init();
}
LOG_INFO("Upscaler weight type: %s", ggml_type_name(model_data_type));
if (!esrgan_upscaler.load_from_file(esrgan_path, backend)) {
esrgan_upscaler = std::make_shared<ESRGAN>(backend, model_data_type);
if (!esrgan_upscaler->load_from_file(esrgan_path)) {
return false;
}
return true;
@@ -39,8 +40,8 @@ struct UpscalerGGML {
sd_image_t upscale(sd_image_t input_image, uint32_t upscale_factor) {
// upscale_factor, unused for RealESRGAN_x4plus_anime_6B.pth
sd_image_t upscaled_image = {0, 0, 0, NULL};
int output_width = (int)input_image.width * esrgan_upscaler.scale;
int output_height = (int)input_image.height * esrgan_upscaler.scale;
int output_width = (int)input_image.width * esrgan_upscaler->scale;
int output_height = (int)input_image.height * esrgan_upscaler->scale;
LOG_INFO("upscaling from (%i x %i) to (%i x %i)",
input_image.width, input_image.height, output_width, output_height);
@@ -62,15 +63,11 @@ struct UpscalerGGML {
ggml_tensor* upscaled = ggml_new_tensor_4d(upscale_ctx, GGML_TYPE_F32, output_width, output_height, 3, 1);
auto on_tiling = [&](ggml_tensor* in, ggml_tensor* out, bool init) {
if (init) {
esrgan_upscaler.alloc_compute_buffer(in);
} else {
esrgan_upscaler.compute(out, n_threads, in);
}
esrgan_upscaler->compute(n_threads, in, &out);
};
int64_t t0 = ggml_time_ms();
sd_tiling(input_image_tensor, upscaled, esrgan_upscaler.scale, esrgan_upscaler.tile_size, 0.25f, on_tiling);
esrgan_upscaler.free_compute_buffer();
sd_tiling(input_image_tensor, upscaled, esrgan_upscaler->scale, esrgan_upscaler->tile_size, 0.25f, on_tiling);
esrgan_upscaler->free_compute_buffer();
ggml_tensor_clamp(upscaled, 0.f, 1.f);
uint8_t* upscaled_data = sd_tensor_to_image(upscaled);
ggml_free(upscale_ctx);