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

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leejet
2026-09-06 23:14:03 +08:00
committed by GitHub
parent 462d675018
commit dbb611264e
69 changed files with 551 additions and 484 deletions
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src/runtime/denoiser.hpp
+8 -8
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@@ -311,7 +311,7 @@ struct BetaScheduler : SigmaScheduler {
explicit BetaScheduler(const char* extra_sample_args = nullptr) {
parse_extra_sample_args(extra_sample_args);
LOG_DEBUG("Beta scheduler: alpha=%.4f, beta=%.4f", alpha, beta);
LOG_VERBOSE("Beta scheduler: alpha=%.4f, beta=%.4f", alpha, beta);
}
void parse_extra_sample_args(const char* extra_sample_args) {
@@ -692,7 +692,7 @@ struct LTX2Scheduler : SigmaScheduler {
float exp_shift = std::exp(sigma_shift);
float target_terminal = std::clamp(terminal, 0.0f, 0.99f);
LOG_DEBUG("LTX2 scheduler: tokens=%d, shift=%.4f, stretch=%d, terminal=%.4f", token_count, sigma_shift, stretch ? 1 : 0, target_terminal);
LOG_VERBOSE("LTX2 scheduler: tokens=%d, shift=%.4f, stretch=%d, terminal=%.4f", token_count, sigma_shift, stretch ? 1 : 0, target_terminal);
sigmas.reserve(n + 1);
for (uint32_t i = 0; i <= n; ++i) {
@@ -760,7 +760,7 @@ struct FluxScheduler : SigmaScheduler {
sigmas.reserve(n + 1);
float mu = compute_mu();
LOG_DEBUG("Flux scheduler: image_seq_len=%d, steps=%u, mu=%.3f", image_seq_len, n, mu);
LOG_VERBOSE("Flux scheduler: image_seq_len=%d, steps=%u, mu=%.3f", image_seq_len, n, mu);
if (n == 0) {
sigmas.push_back(1.0f);
@@ -811,7 +811,7 @@ struct Flux2Scheduler : SigmaScheduler {
sigmas.reserve(n + 1);
float mu = compute_empirical_mu(image_seq_len, n);
LOG_DEBUG("Flux2 scheduler: image_seq_len=%d, steps=%u, mu=%.3f", image_seq_len, n, mu);
LOG_VERBOSE("Flux2 scheduler: image_seq_len=%d, steps=%u, mu=%.3f", image_seq_len, n, mu);
if (n == 0) {
sigmas.push_back(1.0f);
@@ -1413,8 +1413,8 @@ struct SefiFlowDenoiser : public FluxFlowDenoiser {
sem_sigmas.push_back(sigma_sem);
tex_sigmas.push_back(sigma_tex);
}
LOG_DEBUG("SefiFlowDenoiser: built %u-step dual schedule (alpha=%.2f delta_t=%.2f)",
n, timestep_shift_alpha, delta_t);
LOG_VERBOSE("SefiFlowDenoiser: built %u-step dual schedule (alpha=%.2f delta_t=%.2f)",
n, timestep_shift_alpha, delta_t);
return tex_sigmas;
}
};
@@ -2690,7 +2690,7 @@ static sd::Tensor<float> sample_lms(denoise_cb_t model,
int steps = static_cast<int>(sigmas.size()) - 1;
max_order = std::min(max_order, steps); // history can not be larger than steps
LOG_DEBUG("linear multi-step sampler: lms_max_order = %i, lms_shift = %i, lms_divisions = %i", max_order, shift, divisions);
LOG_VERBOSE("linear multi-step sampler: lms_max_order = %i, lms_shift = %i, lms_divisions = %i", max_order, shift, divisions);
std::vector<float> lms_coeff(max_order);
std::vector<sd::Tensor<float>> hist = {};
@@ -2793,7 +2793,7 @@ static sd::Tensor<float> sample_gradient_estimation(denoise_cb_t model,
LOG_WARN("ignoring invalid euler_ge extra sample arg '%s=%s'", key.c_str(), value.c_str());
continue;
}
LOG_DEBUG("setting euler_ge gamma to %.2f", parsed);
LOG_VERBOSE("setting euler_ge gamma to %.2f", parsed);
ge_gamma = parsed;
}
}