Rework handling of defaults to top-level gp function
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Lee Spector
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f0424979b5
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@ -48,127 +48,153 @@
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(prn {:run-completed true})
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nil)
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(defn fill-defaults
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"Returns argmap with any unspecified values filled with defaults."
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[argmap]
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(let [defaults
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{:bmx-exchange-rate 0.5
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:bmx-gene-length-limit 10
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:bmx-gap-change-probability 0.001
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:bmx-complementary? false
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:dont-end false
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:downsample? true
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:ds-function :case-maxmin
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:downsample-rate 0.05
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:ds-parent-rate 0.01
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:ds-parent-gens 10
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:error-function (fn [& args] (println "ERROR FUNCTION NOT PROVIDED"))
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:ids-type :solved ; :solved or :elite or :soft
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:max-initial-plushy-size 100
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:max-generations 1000
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:parent-selection :lexicase
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:population-size 1000
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:single-thread-mode false
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:solution-error-threshold 0
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:step-limit 1000
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:testing-data []
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:training-data []
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:umad-rate 0.1
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:variation {:umad 1}}
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defaulted (merge defaults argmap)]
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(merge defaulted ; use the map below to include derived values in argmap
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{:bmx? (some #{:bmx :bmx-umad} (keys (:variation defaulted)))})))
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(defn gp
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"Main GP function"
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[{:keys [population-size max-generations error-function solution-error-threshold
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ds-parent-rate ds-parent-gens dont-end ids-type downsample?]
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:or {solution-error-threshold 0.0
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dont-end false
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ds-parent-rate 0
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ds-parent-gens 1
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ids-type :solved ; :solved or :elite or :soft
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downsample? false}
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:as argmap}]
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[non-default-argmap]
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(let [argmap (fill-defaults non-default-argmap)
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{:keys [population-size max-generations error-function solution-error-threshold dont-end
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downsample? ds-parent-rate ds-parent-gens ids-type]} argmap]
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;; print starting args
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(prn {:starting-args (update (update argmap :error-function str)
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:instructions
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(fn [instrs]
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(utils/not-lazy (map #(if (fn? %) (str %) %) instrs))))})
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(println)
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(prn {:starting-args (update (update argmap :error-function str)
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:instructions
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(fn [instrs]
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(utils/not-lazy (map #(if (fn? %) (str %) %) instrs))))})
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(println)
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;;
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(loop [generation 0
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evaluations 0
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population (utils/pmapallv
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(fn [_] {:plushy (genome/make-random-plushy argmap)})
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(range population-size)
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argmap)
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indexed-training-data (if downsample?
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(downsample/assign-indices-to-data (downsample/initialize-case-distances argmap) argmap)
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(:training-data argmap))]
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(let [training-data (if downsample?
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(case (:ds-function argmap)
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:case-maxmin (downsample/select-downsample-maxmin indexed-training-data argmap)
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:case-maxmin-auto (downsample/select-downsample-maxmin-adaptive indexed-training-data argmap)
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:case-rand (downsample/select-downsample-random indexed-training-data argmap)
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(do (prn {:error "Invalid Downsample Function"})
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(downsample/select-downsample-random indexed-training-data argmap)))
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indexed-training-data) ;defaults to full training set
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parent-reps (if
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(and downsample? ; if we are down-sampling
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(zero? (mod generation ds-parent-gens))) ;every ds-parent-gens generations
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(take (* ds-parent-rate (count population)) (shuffle population))
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'()) ;else just empty list
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(loop [generation 0
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evaluations 0
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population (utils/pmapallv
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(fn [_] {:plushy (genome/make-random-plushy argmap)})
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(range population-size)
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argmap)
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indexed-training-data (if downsample?
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(downsample/assign-indices-to-data (downsample/initialize-case-distances argmap) argmap)
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(:training-data argmap))]
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(let [training-data (if downsample?
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(case (:ds-function argmap)
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:case-maxmin (downsample/select-downsample-maxmin indexed-training-data argmap)
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:case-maxmin-auto (downsample/select-downsample-maxmin-adaptive indexed-training-data argmap)
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:case-rand (downsample/select-downsample-random indexed-training-data argmap)
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(do (prn {:error "Invalid Downsample Function"})
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(downsample/select-downsample-random indexed-training-data argmap)))
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indexed-training-data) ;defaults to full training set
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parent-reps (if
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(and downsample? ; if we are down-sampling
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(zero? (mod generation ds-parent-gens))) ;every ds-parent-gens generations
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(take (* ds-parent-rate (count population)) (shuffle population))
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'()) ;else just empty list
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; parent representatives for down-sampling
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rep-evaluated-pop (if downsample?
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(sort-by :total-error
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(utils/pmapallv
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(partial error-function argmap indexed-training-data)
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parent-reps
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argmap))
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'())
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evaluated-pop (sort-by :total-error
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(utils/pmapallv
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(partial error-function argmap training-data)
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population
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argmap))
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best-individual (first evaluated-pop)
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best-individual-passes-ds (and downsample? (<= (:total-error best-individual) solution-error-threshold))
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argmap (if (= (:parent-selection argmap) :epsilon-lexicase)
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(assoc argmap :epsilons (selection/epsilon-list evaluated-pop))
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argmap)] ; epsilons
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(if (:custom-report argmap)
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((:custom-report argmap) evaluations evaluated-pop generation argmap)
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(report evaluations evaluated-pop generation argmap training-data))
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rep-evaluated-pop (if downsample?
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(sort-by :total-error
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(utils/pmapallv
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(partial error-function argmap indexed-training-data)
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parent-reps
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argmap))
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'())
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evaluated-pop (sort-by :total-error
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(utils/pmapallv
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(partial error-function argmap training-data)
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population
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argmap))
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best-individual (first evaluated-pop)
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best-individual-passes-ds (and downsample? (<= (:total-error best-individual) solution-error-threshold))
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argmap (if (= (:parent-selection argmap) :epsilon-lexicase)
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(assoc argmap :epsilons (selection/epsilon-list evaluated-pop))
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argmap)] ; epsilons
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(if (:custom-report argmap)
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((:custom-report argmap) evaluations evaluated-pop generation argmap)
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(report evaluations evaluated-pop generation argmap training-data))
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;; Did the indvidual pass all cases in ds?
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(when best-individual-passes-ds
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(prn {:semi-success-generation generation}))
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(cond
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(when best-individual-passes-ds
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(prn {:semi-success-generation generation}))
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(cond
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;; If either the best individual on the ds passes all training cases, or best individual on full
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;; sample passes all training cases, we verify success on test cases and exit, succeeding
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(if (or (and best-individual-passes-ds
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(<= (:total-error (error-function argmap indexed-training-data best-individual))
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solution-error-threshold))
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(and (not downsample?)
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(<= (:total-error best-individual)
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solution-error-threshold)))
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(do (prn {:success-generation generation})
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(prn {:successful-plushy (:plushy best-individual)})
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(prn {:successful-program (genome/plushy->push (:plushy best-individual) argmap)})
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(prn {:total-test-error
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(:total-error (error-function argmap (:testing-data argmap) best-individual))})
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(when (:simplification? argmap)
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(let [simplified-plushy (simplification/auto-simplify-plushy (:plushy best-individual) error-function argmap)]
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(prn {:total-test-error-simplified
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(:total-error (error-function argmap (:testing-data argmap) {:plushy simplified-plushy}))})
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(prn {:simplified-plushy simplified-plushy})
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(prn {:simplified-program (genome/plushy->push simplified-plushy argmap)})))
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(if dont-end false true))
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false)
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(cleanup)
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(if (or (and best-individual-passes-ds
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(<= (:total-error (error-function argmap indexed-training-data best-individual))
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solution-error-threshold))
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(and (not downsample?)
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(<= (:total-error best-individual)
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solution-error-threshold)))
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(do (prn {:success-generation generation})
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(prn {:successful-plushy (:plushy best-individual)})
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(prn {:successful-program (genome/plushy->push (:plushy best-individual) argmap)})
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(prn {:total-test-error
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(:total-error (error-function argmap (:testing-data argmap) best-individual))})
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(when (:simplification? argmap)
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(let [simplified-plushy (simplification/auto-simplify-plushy (:plushy best-individual) error-function argmap)]
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(prn {:total-test-error-simplified
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(:total-error (error-function argmap (:testing-data argmap) {:plushy simplified-plushy}))})
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(prn {:simplified-plushy simplified-plushy})
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(prn {:simplified-program (genome/plushy->push simplified-plushy argmap)})))
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(if dont-end false true))
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false)
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(cleanup)
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;; If we've evolved for as many generations as the parameters allow, exit without succeeding
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(or (and (not downsample?)
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(>= generation max-generations))
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(and downsample?
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(>= evaluations (* max-generations population-size (count indexed-training-data)))))
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(cleanup)
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(or (and (not downsample?)
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(>= generation max-generations))
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(and downsample?
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(>= evaluations (* max-generations population-size (count indexed-training-data)))))
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(cleanup)
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;; Otherwise, evolve for another generation
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:else (recur (inc generation)
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(+ evaluations
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(* population-size (count training-data)) ;every member evaluated on the current sample
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(if (zero? (mod generation ds-parent-gens))
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(* (count parent-reps)
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(- (count indexed-training-data)
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(count training-data)))
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0) ; the parent-reps not evaluted already on down-sample
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(if best-individual-passes-ds
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(- (count indexed-training-data) (count training-data))
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0)) ; if we checked for generalization or not
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(if (:elitism argmap) ; elitism maintains the most-fit individual
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(conj (utils/pmapallv (fn [_] (variation/new-individual evaluated-pop argmap))
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(range (dec population-size))
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argmap)
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(first evaluated-pop))
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(utils/pmapallv (fn [_] (variation/new-individual evaluated-pop argmap))
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(range population-size)
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argmap))
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(if downsample?
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(if (zero? (mod generation ds-parent-gens))
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:else (recur (inc generation)
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(+ evaluations
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(* population-size (count training-data)) ;every member evaluated on the current sample
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(if (zero? (mod generation ds-parent-gens))
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(* (count parent-reps)
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(- (count indexed-training-data)
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(count training-data)))
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0) ; the parent-reps not evaluted already on down-sample
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(if best-individual-passes-ds
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(- (count indexed-training-data) (count training-data))
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0)) ; if we checked for generalization or not
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(if (:elitism argmap) ; elitism maintains the most-fit individual
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(conj (utils/pmapallv (fn [_] (variation/new-individual evaluated-pop argmap))
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(range (dec population-size))
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argmap)
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(first evaluated-pop))
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(utils/pmapallv (fn [_] (variation/new-individual evaluated-pop argmap))
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(range population-size)
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argmap))
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(if downsample?
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(if (zero? (mod generation ds-parent-gens))
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; update distances every ds-parent-gens generations
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(downsample/update-case-distances rep-evaluated-pop
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indexed-training-data
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indexed-training-data
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ids-type
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(/ solution-error-threshold
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(count indexed-training-data)))
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indexed-training-data)
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indexed-training-data))))))
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(downsample/update-case-distances rep-evaluated-pop
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indexed-training-data
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indexed-training-data
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ids-type
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(/ solution-error-threshold
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(count indexed-training-data)))
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indexed-training-data)
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indexed-training-data)))))))
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