DarthAffe/stable-diffusion.cpp
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fix: ucache: normalize reuse error (#1313)

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rmatif 2026-03-04 16:50:45 +01:00 committed by GitHub
parent 7c880f80c7
commit d95062737e
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1 changed files with 43 additions and 13 deletions
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src/ucache.hpp
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@ -19,6 +19,7 @@ struct UCacheConfig {
bool adaptive_threshold = true; bool adaptive_threshold = true;
float early_step_multiplier = 0.5f; float early_step_multiplier = 0.5f;
float late_step_multiplier = 1.5f; float late_step_multiplier = 1.5f;
float relative_norm_gain = 1.6f;
bool reset_error_on_compute = true; bool reset_error_on_compute = true;
}; };
@ -45,14 +46,16 @@ struct UCacheState {
bool has_output_prev_norm = false; bool has_output_prev_norm = false;
bool has_relative_transformation_rate = false; bool has_relative_transformation_rate = false;
float relative_transformation_rate = 0.0f; float relative_transformation_rate = 0.0f;
float cumulative_change_rate = 0.0f;
float last_input_change = 0.0f; float last_input_change = 0.0f;
bool has_last_input_change = false; bool has_last_input_change = false;
float output_change_ema = 0.0f;
bool has_output_change_ema = false;
int total_steps_skipped = 0; int total_steps_skipped = 0;
int current_step_index = -1; int current_step_index = -1;
int steps_computed_since_active = 0; int steps_computed_since_active = 0;
int expected_total_steps = 0;
int consecutive_skipped_steps = 0;
float accumulated_error = 0.0f; float accumulated_error = 0.0f;
float reference_output_norm = 0.0f;
struct BlockMetrics { struct BlockMetrics {
float sum_transformation_rate = 0.0f; float sum_transformation_rate = 0.0f;
@ -106,14 +109,16 @@ struct UCacheState {
has_output_prev_norm = false; has_output_prev_norm = false;
has_relative_transformation_rate = false; has_relative_transformation_rate = false;
relative_transformation_rate = 0.0f; relative_transformation_rate = 0.0f;
cumulative_change_rate = 0.0f;
last_input_change = 0.0f; last_input_change = 0.0f;
has_last_input_change = false; has_last_input_change = false;
output_change_ema = 0.0f;
has_output_change_ema = false;
total_steps_skipped = 0; total_steps_skipped = 0;
current_step_index = -1; current_step_index = -1;
steps_computed_since_active = 0; steps_computed_since_active = 0;
expected_total_steps = 0;
consecutive_skipped_steps = 0;
accumulated_error = 0.0f; accumulated_error = 0.0f;
reference_output_norm = 0.0f;
block_metrics.reset(); block_metrics.reset();
total_active_steps = 0; total_active_steps = 0;
} }
@ -134,6 +139,7 @@ struct UCacheState {
return; return;
} }
size_t n_steps = sigmas.size() - 1; size_t n_steps = sigmas.size() - 1;
expected_total_steps = static_cast<int>(n_steps);
size_t start_step = static_cast<size_t>(config.start_percent * n_steps); size_t start_step = static_cast<size_t>(config.start_percent * n_steps);
size_t end_step = static_cast<size_t>(config.end_percent * n_steps); size_t end_step = static_cast<size_t>(config.end_percent * n_steps);
@ -207,11 +213,15 @@ struct UCacheState {
} }
int effective_total = estimated_total_steps; int effective_total = estimated_total_steps;
if (effective_total <= 0) {
effective_total = expected_total_steps;
}
if (effective_total <= 0) { if (effective_total <= 0) {
effective_total = std::max(20, steps_computed_since_active * 2); effective_total = std::max(20, steps_computed_since_active * 2);
} }
float progress = (effective_total > 0) ? (static_cast<float>(steps_computed_since_active) / effective_total) : 0.0f; float progress = (effective_total > 0) ? (static_cast<float>(steps_computed_since_active) / effective_total) : 0.0f;
progress = std::max(0.0f, std::min(1.0f, progress));
float multiplier = 1.0f; float multiplier = 1.0f;
if (progress < 0.2f) { if (progress < 0.2f) {
@ -309,17 +319,31 @@ struct UCacheState {
if (has_output_prev_norm && has_relative_transformation_rate && if (has_output_prev_norm && has_relative_transformation_rate &&
last_input_change > 0.0f && output_prev_norm > 0.0f) { last_input_change > 0.0f && output_prev_norm > 0.0f) {
float approx_output_change_rate = (relative_transformation_rate * last_input_change) / output_prev_norm; float approx_output_change = relative_transformation_rate * last_input_change;
float approx_output_change_rate;
if (config.use_relative_threshold) {
float base_scale = std::max(output_prev_norm, 1e-6f);
float dyn_scale = has_output_change_ema
? std::max(output_change_ema * std::max(1.0f, config.relative_norm_gain), 1e-6f)
: base_scale;
float scale = std::sqrt(base_scale * dyn_scale);
approx_output_change_rate = approx_output_change / scale;
} else {
approx_output_change_rate = approx_output_change;
}
// Increase estimated error with skip horizon to avoid long extrapolation streaks
approx_output_change_rate *= (1.0f + 0.50f * consecutive_skipped_steps);
accumulated_error = accumulated_error * config.error_decay_rate + approx_output_change_rate; accumulated_error = accumulated_error * config.error_decay_rate + approx_output_change_rate;
float effective_threshold = get_adaptive_threshold(); float effective_threshold = get_adaptive_threshold();
if (config.use_relative_threshold && reference_output_norm > 0.0f) { if (!config.use_relative_threshold && output_prev_norm > 0.0f) {
effective_threshold = effective_threshold * reference_output_norm; effective_threshold = effective_threshold * output_prev_norm;
} }
if (accumulated_error < effective_threshold) { if (accumulated_error < effective_threshold) {
skip_current_step = true; skip_current_step = true;
total_steps_skipped++; total_steps_skipped++;
consecutive_skipped_steps++;
apply_cache(cond, input, output); apply_cache(cond, input, output);
return true; return true;
} else if (config.reset_error_on_compute) { } else if (config.reset_error_on_compute) {
@ -340,6 +364,8 @@ struct UCacheState {
if (cond != anchor_condition) { if (cond != anchor_condition) {
return; return;
} }
steps_computed_since_active++;
consecutive_skipped_steps = 0;
size_t ne = static_cast<size_t>(ggml_nelements(input)); size_t ne = static_cast<size_t>(ggml_nelements(input));
float* in_data = (float*)input->data; float* in_data = (float*)input->data;
@ -359,6 +385,14 @@ struct UCacheState {
output_change /= static_cast<float>(ne); output_change /= static_cast<float>(ne);
} }
} }
if (std::isfinite(output_change) && output_change > 0.0f) {
if (!has_output_change_ema) {
output_change_ema = output_change;
has_output_change_ema = true;
} else {
output_change_ema = 0.8f * output_change_ema + 0.2f * output_change;
}
}
prev_output.resize(ne); prev_output.resize(ne);
for (size_t i = 0; i < ne; ++i) { for (size_t i = 0; i < ne; ++i) {
@ -373,10 +407,6 @@ struct UCacheState {
output_prev_norm = (ne > 0) ? (mean_abs / static_cast<float>(ne)) : 0.0f; output_prev_norm = (ne > 0) ? (mean_abs / static_cast<float>(ne)) : 0.0f;
has_output_prev_norm = output_prev_norm > 0.0f; has_output_prev_norm = output_prev_norm > 0.0f;
if (reference_output_norm == 0.0f) {
reference_output_norm = output_prev_norm;
}
if (has_last_input_change && last_input_change > 0.0f && output_change > 0.0f) { if (has_last_input_change && last_input_change > 0.0f && output_change > 0.0f) {
float rate = output_change / last_input_change; float rate = output_change / last_input_change;
if (std::isfinite(rate)) { if (std::isfinite(rate)) {