b033923756
- Remove executable permissions from configuration files (.editorconfig, .env.example, .gitignore) - Remove executable permissions from documentation files (README.md, LICENSE, SECURITY.md) - Remove executable permissions from web assets (HTML, CSS, JS files) - Remove executable permissions from data files (JSON, SQL, YAML, requirements.txt) - Remove executable permissions from source code files across all apps - Add executable permissions to Python
87 lines
2.9 KiB
Plaintext
87 lines
2.9 KiB
Plaintext
pragma circom 2.0.0;
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template ParameterUpdate() {
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signal input current_param;
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signal input gradient;
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signal input learning_rate;
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signal output new_param;
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new_param <== current_param - learning_rate * gradient;
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}
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template VectorParameterUpdate(PARAM_COUNT) {
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signal input current_params[PARAM_COUNT];
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signal input gradients[PARAM_COUNT];
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signal input learning_rate;
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signal output new_params[PARAM_COUNT];
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component updates[PARAM_COUNT];
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for (var i = 0; i < PARAM_COUNT; i++) {
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updates[i] = ParameterUpdate();
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updates[i].current_param <== current_params[i];
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updates[i].gradient <== gradients[i];
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updates[i].learning_rate <== learning_rate;
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new_params[i] <== updates[i].new_param;
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}
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}
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template LossConstraint() {
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signal input predicted_loss;
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signal input actual_loss;
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signal input tolerance;
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signal diff;
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diff <== predicted_loss - actual_loss;
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signal diff_squared;
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diff_squared <== diff * diff;
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signal tolerance_squared;
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tolerance_squared <== tolerance * tolerance;
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diff_squared * (1 - diff_squared / tolerance_squared) === 0;
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}
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template LearningRateValidation() {
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signal input learning_rate;
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}
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template TrainingEpoch(PARAM_COUNT) {
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signal input epoch_params[PARAM_COUNT];
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signal input epoch_gradients[PARAM_COUNT];
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signal input learning_rate;
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signal output next_epoch_params[PARAM_COUNT];
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component param_update = VectorParameterUpdate(PARAM_COUNT);
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param_update.current_params <== epoch_params;
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param_update.gradients <== epoch_gradients;
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param_update.learning_rate <== learning_rate;
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next_epoch_params <== param_update.new_params;
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}
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template ModularTrainingVerification(PARAM_COUNT, EPOCHS) {
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signal input initial_parameters[PARAM_COUNT];
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signal input learning_rate;
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signal output final_parameters[PARAM_COUNT];
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signal output training_complete;
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component lr_validator = LearningRateValidation();
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lr_validator.learning_rate <== learning_rate;
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signal current_params[EPOCHS + 1][PARAM_COUNT];
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for (var i = 0; i < PARAM_COUNT; i++) {
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current_params[0][i] <== initial_parameters[i];
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}
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component epochs[EPOCHS];
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for (var e = 0; e < EPOCHS; e++) {
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epochs[e] = TrainingEpoch(PARAM_COUNT);
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for (var i = 0; i < PARAM_COUNT; i++) {
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epochs[e].epoch_params[i] <== current_params[e][i];
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}
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for (var i = 0; i < PARAM_COUNT; i++) {
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epochs[e].epoch_gradients[i] <== 1;
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}
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epochs[e].learning_rate <== learning_rate;
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for (var i = 0; i < PARAM_COUNT; i++) {
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current_params[e + 1][i] <== epochs[e].next_epoch_params[i];
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}
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}
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for (var i = 0; i < PARAM_COUNT; i++) {
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final_parameters[i] <== current_params[EPOCHS][i];
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}
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training_complete <== 1;
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}
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component main = ModularTrainingVerification(4, 3);
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