DarthAffe/stable-diffusion.cpp
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feat: add verbose logging and log-level selection (#1941)

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leejet authored and GitHub committed 2026-09-06 23:14:03 +08:00
1 parent 462d675018
commit dbb611264e
69 files changed
+551 -484
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src/model/vae/auto_encoder_kl.hpp
+2 -2
View File
@@ -864,7 +864,7 @@ struct AutoEncoderKL : public VAE {
GGML_ASSERT(!out_opt.empty());
out = std::move(out_opt);
print_sd_tensor(out);
LOG_DEBUG("encode test done in %lldms", t1 - t0);
LOG_VERBOSE("encode test done in %lldms", t1 - t0);
}
if (false) {
@@ -884,7 +884,7 @@ struct AutoEncoderKL : public VAE {
GGML_ASSERT(!out_opt.empty());
out = std::move(out_opt);
print_sd_tensor(out);
LOG_DEBUG("decode test done in %lldms", t1 - t0);
LOG_VERBOSE("decode test done in %lldms", t1 - t0);
}
};
};
src/model/vae/ltx_audio_vae.hpp
+7 -7
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@@ -172,12 +172,12 @@ namespace LTXV {
if (config.audio_channels != 2 || config.latent_channels != 8 || config.mel_bins != 64) {
return config;
}
LOG_DEBUG("ltx_audio_vae: sample_rate = %d, mel_bins = %d, latent_channels = %d, latent_frequency_bins = %d, has_bwe = %s",
config.sample_rate,
config.mel_bins,
config.latent_channels,
config.latent_frequency_bins,
config.has_bwe ? "true" : "false");
LOG_VERBOSE("ltx_audio_vae: sample_rate = %d, mel_bins = %d, latent_channels = %d, latent_frequency_bins = %d, has_bwe = %s",
config.sample_rate,
config.mel_bins,
config.latent_channels,
config.latent_frequency_bins,
config.has_bwe ? "true" : "false");
return config;
}
};
@@ -1063,7 +1063,7 @@ namespace LTXV {
GGML_ASSERT(!out.empty());
print_sd_tensor(out, false, "ltx_audio_vae_out");
LOG_DEBUG("ltx audio vae test done in %lldms", t1 - t0);
LOG_VERBOSE("ltx audio vae test done in %lldms", t1 - t0);
}
static void load_from_file_and_test(const std::string& model_path,
src/model/vae/ltx_vae.hpp
+17 -17
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@@ -1126,11 +1126,11 @@ namespace LTXVAE {
overlap, window);
overlap = window - 1;
}
LOG_DEBUG("Using temporal tiling: temporal_tile_frames = %d, temporal_tile_overlap = %d, total frames = %d, resulting in %d tiles",
window,
overlap,
(int)T,
(T + window - overlap - 1) / (window - overlap));
LOG_VERBOSE("Using temporal tiling: temporal_tile_frames = %d, temporal_tile_overlap = %d, total frames = %d, resulting in %d tiles",
window,
overlap,
(int)T,
(T + window - overlap - 1) / (window - overlap));
ggml_tensor* out = nullptr;
for (int i = 0; i < (int)T - overlap; i += (window - overlap)) {
int feat_idx = 0;
@@ -1327,21 +1327,21 @@ struct LTXVideoVAE : public VAE {
const int64_t total_frames = input.shape()[2];
auto plan = make_vae_temporal_tile_plan(total_frames, config);
LOG_DEBUG("Using streaming temporal tiling: temporal_tile_frames=%d, temporal_tile_overlap=%d, total latent frames=%lld, resulting in %d tiles",
plan.tile_frames,
plan.overlap,
(long long)total_frames,
(int)plan.tiles.size());
LOG_VERBOSE("Using streaming temporal tiling: temporal_tile_frames=%d, temporal_tile_overlap=%d, total latent frames=%lld, resulting in %d tiles",
plan.tile_frames,
plan.overlap,
(long long)total_frames,
(int)plan.tiles.size());
free_cache_ctx_and_buffer();
auto output = process_vae_temporal_tiles(input, plan, [&](const sd::Tensor<float>& z_chunk, const VAETemporalTile& tile) {
LOG_DEBUG("LTX VAE temporal tile %lld/%d: latent frames [%lld, %lld), overlap=%d",
(long long)tile.index + 1,
(int)plan.tiles.size(),
(long long)tile.start,
(long long)tile.end,
tile.overlap);
LOG_VERBOSE("LTX VAE temporal tile %lld/%d: latent frames [%lld, %lld), overlap=%d",
(long long)tile.index + 1,
(int)plan.tiles.size(),
(long long)tile.start,
(long long)tile.end,
tile.overlap);
auto get_graph = [&]() -> ggml_cgraph* {
return build_temporal_tile_graph(z_chunk,
@@ -1465,7 +1465,7 @@ struct LTXVideoVAE : public VAE {
GGML_ASSERT(!out.empty());
print_sd_tensor(out, false, "ltx_vae_out");
LOG_DEBUG("ltx vae test done in %lldms", t1 - t0);
LOG_VERBOSE("ltx vae test done in %lldms", t1 - t0);
}
static void load_from_file_and_test(const std::string& model_path,
src/model/vae/tae.hpp
+1 -1
View File
@@ -65,7 +65,7 @@ public:
if (n_in != n_out) {
auto skip = std::dynamic_pointer_cast<Conv2d>(blocks["skip"]);
LOG_DEBUG("skip");
LOG_VERBOSE("skip");
x = skip->forward(ctx, x);
}
src/model/vae/vae.hpp
+16 -16
View File
@@ -54,23 +54,23 @@ protected:
}
auto plan = make_vae_temporal_tile_plan(input.shape()[2], resolved_config);
LOG_DEBUG("%s temporal tiling: tile_frames=%d, overlap=%d, total_frames=%lld, tiles=%d",
get_desc().c_str(),
plan.tile_frames,
plan.overlap,
(long long)input.shape()[2],
(int)plan.tiles.size());
LOG_VERBOSE("%s temporal tiling: tile_frames=%d, overlap=%d, total_frames=%lld, tiles=%d",
get_desc().c_str(),
plan.tile_frames,
plan.overlap,
(long long)input.shape()[2],
(int)plan.tiles.size());
return process_vae_temporal_tiles_blended(
input,
plan,
output_scale,
[&](const sd::Tensor<float>& input_tile, const VAETemporalTile& tile) {
LOG_DEBUG("%s temporal tile %d/%d: input frames [%lld, %lld)",
get_desc().c_str(),
tile.index + 1,
(int)plan.tiles.size(),
(long long)tile.start,
(long long)tile.end);
LOG_VERBOSE("%s temporal tile %d/%d: input frames [%lld, %lld)",
get_desc().c_str(),
tile.index + 1,
(int)plan.tiles.size(),
(long long)tile.start,
(long long)tile.end);
return _compute(n_threads, input_tile, true);
});
}
@@ -230,7 +230,7 @@ public:
const float encode_tile_factor = sd_version_is_minimax_h3(version) ? 1.f : (sd_version_is_wan(version) || sd_version_is_hunyuan_video(version) || sd_version_is_ltxav(version)) ? 1.30539f
: 2.0f;
get_tile_sizes(tile_size_x, tile_size_y, tile_overlap, tiling_params, W, H, encode_tile_factor);
LOG_DEBUG("VAE Tile size: %dx%d", tile_size_x, tile_size_y);
LOG_VERBOSE("VAE Tile size: %dx%d", tile_size_x, tile_size_y);
output = tiled_compute(input,
n_threads,
static_cast<int>(W),
@@ -258,7 +258,7 @@ public:
return {};
}
int64_t t1 = ggml_time_ms();
LOG_DEBUG("computing vae encode graph completed, taking %.2fs", (t1 - t0) * 1.0f / 1000);
LOG_VERBOSE("computing vae encode graph completed, taking %.2fs", (t1 - t0) * 1.0f / 1000);
return std::move(output);
}
@@ -281,7 +281,7 @@ public:
int tile_size_x, tile_size_y;
get_tile_sizes(tile_size_x, tile_size_y, tile_overlap, tiling_params, input.shape()[0], input.shape()[1]);
if (!silent) {
LOG_DEBUG("VAE Tile size: %dx%d", tile_size_x, tile_size_y);
LOG_VERBOSE("VAE Tile size: %dx%d", tile_size_x, tile_size_y);
}
output = tiled_compute(
input,
@@ -315,7 +315,7 @@ public:
scale_tensor_to_0_1(&output);
}
int64_t t1 = ggml_time_ms();
LOG_DEBUG("computing vae decode graph completed, taking %.2fs", (t1 - t0) * 1.0f / 1000);
LOG_VERBOSE("computing vae decode graph completed, taking %.2fs", (t1 - t0) * 1.0f / 1000);
return std::move(output);
}
src/model/vae/wan_vae.hpp
+11 -11
View File
@@ -1278,7 +1278,7 @@ namespace WAN {
}
}
if (is_2D) {
LOG_DEBUG("USING 2D VAE");
LOG_VERBOSE("USING 2D VAE");
}
ae = WanVAE(decode_only, version, is_2D);
ae.init(params_ctx, tensor_storage_map, prefix);
@@ -1409,20 +1409,20 @@ namespace WAN {
stateful_config.overlap = 0;
auto plan = make_vae_temporal_tile_plan(input.shape()[2], stateful_config);
LOG_DEBUG("Wan VAE stateful temporal tiling: tile_frames=%d, total latent frames=%lld, tiles=%d",
plan.tile_frames,
(long long)input.shape()[2],
(int)plan.tiles.size());
LOG_VERBOSE("Wan VAE stateful temporal tiling: tile_frames=%d, total latent frames=%lld, tiles=%d",
plan.tile_frames,
(long long)input.shape()[2],
(int)plan.tiles.size());
free_cache_ctx_and_buffer();
ae.clear_cache();
auto output = process_vae_temporal_tiles(input, plan, [&](const sd::Tensor<float>& input_tile, const VAETemporalTile& tile) {
LOG_DEBUG("Wan VAE temporal tile %d/%d: latent frames [%lld, %lld)",
tile.index + 1,
(int)plan.tiles.size(),
(long long)tile.start,
(long long)tile.end);
LOG_VERBOSE("Wan VAE temporal tile %d/%d: latent frames [%lld, %lld)",
tile.index + 1,
(int)plan.tiles.size(),
(long long)tile.start,
(long long)tile.end);
auto get_graph = [&]() -> ggml_cgraph* {
return build_temporal_tile_graph(input_tile, static_cast<int>(tile.start));
};
@@ -1479,7 +1479,7 @@ namespace WAN {
GGML_ASSERT(!out_opt.empty());
out = std::move(out_opt);
print_sd_tensor(out);
LOG_DEBUG("decode test done in %ldms", t1 - t0);
LOG_VERBOSE("decode test done in %ldms", t1 - t0);
}
};