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fix: ucache: normalize reuse error #1313

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Merged
leejet merged 2 commits into from
Mar 4, 2026
Merged

fix: ucache: normalize reuse error #1313

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e082a01
ucache: normalize error scaling
rmatif Mar 3, 2026
0461b83
format code
leejet Mar 4, 2026
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56 changes: 43 additions & 13 deletions src/ucache.hpp
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Original file line number Diff line number Diff line change
Expand Up @@ -19,6 +19,7 @@ struct UCacheConfig {
bool adaptive_threshold = true;
float early_step_multiplier = 0.5f;
float late_step_multiplier = 1.5f;
float relative_norm_gain = 1.6f;
bool reset_error_on_compute = true;
};

Expand All @@ -45,14 +46,16 @@ struct UCacheState {
bool has_output_prev_norm = false;
bool has_relative_transformation_rate = false;
float relative_transformation_rate = 0.0f;
float cumulative_change_rate = 0.0f;
float last_input_change = 0.0f;
bool has_last_input_change = false;
float output_change_ema = 0.0f;
bool has_output_change_ema = false;
int total_steps_skipped = 0;
int current_step_index = -1;
int steps_computed_since_active = 0;
int expected_total_steps = 0;
int consecutive_skipped_steps = 0;
float accumulated_error = 0.0f;
float reference_output_norm = 0.0f;

struct BlockMetrics {
float sum_transformation_rate = 0.0f;
Expand Down Expand Up @@ -106,14 +109,16 @@ struct UCacheState {
has_output_prev_norm = false;
has_relative_transformation_rate = false;
relative_transformation_rate = 0.0f;
cumulative_change_rate = 0.0f;
last_input_change = 0.0f;
has_last_input_change = false;
output_change_ema = 0.0f;
has_output_change_ema = false;
total_steps_skipped = 0;
current_step_index = -1;
steps_computed_since_active = 0;
expected_total_steps = 0;
consecutive_skipped_steps = 0;
accumulated_error = 0.0f;
reference_output_norm = 0.0f;
block_metrics.reset();
total_active_steps = 0;
}
Expand All @@ -133,7 +138,8 @@ struct UCacheState {
if (!initialized || sigmas.size() < 2) {
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 end_step = static_cast<size_t>(config.end_percent * n_steps);
Expand Down Expand Up @@ -207,11 +213,15 @@ struct UCacheState {
}

int effective_total = estimated_total_steps;
if (effective_total <= 0) {
effective_total = expected_total_steps;
}
if (effective_total <= 0) {
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;
progress = std::max(0.0f, std::min(1.0f, progress));

float multiplier = 1.0f;
if (progress < 0.2f) {
Expand Down Expand Up @@ -309,17 +319,31 @@ struct UCacheState {

if (has_output_prev_norm && has_relative_transformation_rate &&
last_input_change > 0.0f && output_prev_norm > 0.0f) {
float approx_output_change_rate = (relative_transformation_rate * last_input_change) / output_prev_norm;
accumulated_error = accumulated_error * config.error_decay_rate + approx_output_change_rate;
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;

float effective_threshold = get_adaptive_threshold();
if (config.use_relative_threshold && reference_output_norm > 0.0f) {
effective_threshold = effective_threshold * reference_output_norm;
if (!config.use_relative_threshold && output_prev_norm > 0.0f) {
effective_threshold = effective_threshold * output_prev_norm;
}

if (accumulated_error < effective_threshold) {
skip_current_step = true;
total_steps_skipped++;
consecutive_skipped_steps++;
apply_cache(cond, input, output);
return true;
} else if (config.reset_error_on_compute) {
Expand All @@ -340,6 +364,8 @@ struct UCacheState {
if (cond != anchor_condition) {
return;
}
steps_computed_since_active++;
consecutive_skipped_steps = 0;

size_t ne = static_cast<size_t>(ggml_nelements(input));
float* in_data = (float*)input->data;
Expand All @@ -359,6 +385,14 @@ struct UCacheState {
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);
for (size_t i = 0; i < ne; ++i) {
Expand All @@ -373,10 +407,6 @@ struct UCacheState {
output_prev_norm = (ne > 0) ? (mean_abs / static_cast<float>(ne)) : 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) {
float rate = output_change / last_input_change;
if (std::isfinite(rate)) {
Expand Down
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