diff --git a/src/propeller/gp.cljc b/src/propeller/gp.cljc index 9ceac05..6fdd558 100644 --- a/src/propeller/gp.cljc +++ b/src/propeller/gp.cljc @@ -50,8 +50,8 @@ (defn gp-loop "Main GP loop." - [{:keys [population-size max-generations error-function instructions - max-initial-plushy-size solution-error-threshold ds-parent-rate ds-parent-gens dont-end ids-type downsample?] + [{:keys [population-size max-generations error-function instructions max-initial-plushy-size + solution-error-threshold ds-parent-rate ds-parent-gens dont-end ids-type downsample?] :or {solution-error-threshold 0.0 dont-end false ds-parent-rate 0 @@ -59,9 +59,9 @@ ids-type :solved ; :solved or :elite or :soft downsample? false} :as argmap}] - ;; - (prn {:starting-args (update (update argmap :error-function str) - :instructions + ;; print starting args + (prn {:starting-args (update (update argmap :error-function str) + :instructions (fn [instrs] (utils/not-lazy (map #(if (fn? %) (str %) %) instrs))))}) (println) @@ -69,16 +69,19 @@ (loop [generation 0 evaluations 0 population (utils/pmapallv - (fn [_] {:plushy (genome/make-random-plushy instructions max-initial-plushy-size)}) - (range population-size) + (fn [_] {:plushy (genome/make-random-plushy instructions max-initial-plushy-size)}) + (range population-size) argmap) - indexed-training-data (if downsample? (downsample/assign-indices-to-data (downsample/initialize-case-distances argmap) argmap) (:training-data argmap))] + indexed-training-data (if downsample? + (downsample/assign-indices-to-data (downsample/initialize-case-distances argmap) argmap) + (:training-data argmap))] (let [training-data (if downsample? (case (:ds-function argmap) :case-maxmin (downsample/select-downsample-maxmin indexed-training-data argmap) :case-maxmin-auto (downsample/select-downsample-maxmin-adaptive indexed-training-data argmap) :case-rand (downsample/select-downsample-random indexed-training-data argmap) - (do (prn {:error "Invalid Downsample Function"}) (downsample/select-downsample-random indexed-training-data argmap))) + (do (prn {:error "Invalid Downsample Function"}) + (downsample/select-downsample-random indexed-training-data argmap))) indexed-training-data) ;defaults to full training set parent-reps (if (and downsample? ; if we are down-sampling @@ -106,46 +109,63 @@ (if (:custom-report argmap) ((:custom-report argmap) evaluations evaluated-pop generation argmap) (report evaluations evaluated-pop generation argmap training-data)) - ;;did the indvidual pass all cases in ds? + ;; Did the indvidual pass all cases in ds? (when best-individual-passes-ds (prn {:semi-success-generation generation})) (cond - ;; If either the best individual on the ds passes all training cases, or best individual on full sample passes all training cases - ;; We verify success on test cases and end evolution - (if (or (and best-individual-passes-ds (<= (:total-error (error-function argmap indexed-training-data best-individual)) solution-error-threshold)) + ;; If either the best individual on the ds passes all training cases, or best individual on full + ;; sample passes all training cases, we verify success on test cases and exit, succeeding + (if (or (and best-individual-passes-ds + (<= (:total-error (error-function argmap indexed-training-data best-individual)) + solution-error-threshold)) (and (not downsample?) - (<= (:total-error best-individual) solution-error-threshold))) + (<= (:total-error best-individual) + solution-error-threshold))) (do (prn {:success-generation generation}) (prn {:total-test-error (:total-error (error-function argmap (:testing-data argmap) best-individual))}) (when (:simplification? argmap) (let [simplified-plushy (simplification/auto-simplify-plushy (:plushy best-individual) error-function argmap)] - (prn {:total-test-error-simplified (:total-error (error-function argmap (:testing-data argmap) (hash-map :plushy simplified-plushy)))}))) + (prn {:total-test-error-simplified + (:total-error (error-function argmap (:testing-data argmap) {:plushy simplified-plushy}))}))) (if dont-end false true)) false) (cleanup) - ;; - (and (not downsample?) (>= generation max-generations)) + ;; If we've evolved for as many generations as the parameters allow, exit without succeeding + (or (and (not downsample?) + (>= generation max-generations)) + (and downsample? + (>= evaluations (* max-generations population-size (count indexed-training-data))))) (cleanup) - ;; - (and downsample? (>= evaluations (* max-generations population-size (count indexed-training-data)))) - (cleanup) - ;; + ;; Otherwise, evolve for another generation :else (recur (inc generation) - (+ evaluations (* population-size (count training-data)) ;every member evaluated on the current sample - (if (zero? (mod generation ds-parent-gens)) (* (count parent-reps) (- (count indexed-training-data) (count training-data))) 0) ; the parent-reps not evaluted already on down-sample - (if best-individual-passes-ds (- (count indexed-training-data) (count training-data)) 0)) ; if we checked for generalization or not - (if (:elitism argmap) - (conj (utils/pmapallv (fn [_] (variation/new-individual evaluated-pop argmap)) - (range (dec population-size)) - argmap) - (first evaluated-pop)) ;elitism maintains the most-fit individual - (utils/pmapallv (fn [_] (variation/new-individual evaluated-pop argmap)) - (range population-size) - argmap)) + (+ evaluations + (* population-size (count training-data)) ;every member evaluated on the current sample + (if (zero? (mod generation ds-parent-gens)) + (* (count parent-reps) + (- (count indexed-training-data) + (count training-data))) + 0) ; the parent-reps not evaluted already on down-sample + (if best-individual-passes-ds + (- (count indexed-training-data) (count training-data)) + 0)) ; if we checked for generalization or not + (if (:elitism argmap) ; elitism maintains the most-fit individual + (conj (utils/pmapallv (fn [_] (variation/new-individual evaluated-pop argmap)) + (range (dec population-size)) + argmap) + (first evaluated-pop)) + (utils/pmapallv (fn [_] (variation/new-individual evaluated-pop argmap)) + (range population-size) + argmap)) (if downsample? (if (zero? (mod generation ds-parent-gens)) - (downsample/update-case-distances rep-evaluated-pop indexed-training-data indexed-training-data ids-type (/ solution-error-threshold (count indexed-training-data))) ; update distances every ds-parent-gens generations + ; update distances every ds-parent-gens generations + (downsample/update-case-distances rep-evaluated-pop + indexed-training-data + indexed-training-data + ids-type + (/ solution-error-threshold + (count indexed-training-data))) indexed-training-data) indexed-training-data))))))