Upload opt_tester.sh

opt_tester.sh

@@ -0,0 +1,53 @@
+#!/bin/bash
+
+# Using each optimiser, generate images using a range of learning rates
+# Produce a labelled montage to easily view the results
+
+TEXT="A painting in the style of Paul Gauguin"
+OUT_DIR="/home/nerdy/github/VQGAN-CLIP/Saves/OptimiserTesting-60it-Noise-NPW-1"
+ITERATIONS=60
+SAVE_EVERY=60
+HEIGHT=256
+WIDTH=256
+SEED=`shuf -i 1-9999999999 -n 1` # Keep the same seed each epoch for more deterministic runs
+
+# Main
+#################
+
+export CUBLAS_WORKSPACE_CONFIG=:4096:8
+mkdir -p "$OUT_DIR"
+
+function do_optimiser_test () {
+  OPTIMISER="$1"
+  LR="$2"
+  STEP="$3"
+  NPW="$4"
+  for i in {1..10}
+  do
+    PADDED_COUNT=$(printf "%03d" "$COUNT")
+    echo "Loop for $OPTIMISER - $LR"
+    python generate.py -p "$TEXT" -in pixels -o "$OUT_DIR"/"$PADDED_COUNT"-"$OPTIMISER"-"$LR"-"$NPW".png -opt "$OPTIMISER" -lr "$LR" -i "$ITERATIONS" -se "$SAVE_EVERY" -s "$HEIGHT" "$WIDTH" --seed "$SEED" -d True -iw 1 -nps 666 -npw "$NPW" -d True
+    LR=$(echo $LR + $STEP | bc)
+    ((COUNT++))
+  done
+}
+
+# Test optimisers
+COUNT=0
+do_optimiser_test "Adam" .1 .1 1
+COUNT=10
+do_optimiser_test "AdamW" .1 .1 1
+COUNT=20
+do_optimiser_test "Adamax" .1 .1 1
+COUNT=30
+do_optimiser_test "Adagrad" .1 .25 1
+COUNT=40
+do_optimiser_test "AdamP" .1 .25 1
+COUNT=50
+do_optimiser_test "RAdam" .1 .25 1
+COUNT=60
+do_optimiser_test "DiffGrad" .1 .25 1
+
+# Make montage
+mogrify -font Liberation-Sans -fill white -undercolor '#00000080' -pointsize 14 -gravity NorthEast -annotate +10+10 %t "$OUT_DIR"/*.png
+montage "$OUT_DIR"/*.png -geometry 256x256+1+1 -tile 10x7 collage.jpg