diff options
| -rwxr-xr-x | extract.sh | 30 | ||||
| -rw-r--r-- | include/weights.c | 25 | ||||
| -rw-r--r-- | src/train5.py | 29 |
3 files changed, 50 insertions, 34 deletions
@@ -5,8 +5,8 @@ db_file=games_anon.db query() { query="(size == $1) and (result != '1-0') and (result != '0-1') and (result != '0-0')" selct="" - for player in rabbitboy84 fwwwwibib archvenison Simmon AaaarghBot; do - # for player in; do + # for player in rabbitboy84 fwwwwibib archvenison Simmon AaaarghBot; do + for player in; do selct="$selct(player_black == '$player') or (player_white == '$player') or " done; if [ -n "$selct" ]; then @@ -37,25 +37,27 @@ process() { echo -en "Done.\n\tGenerating training data... " ./pptdb "$size" "data/smalltak-$size" generate echo -en "\tShuffling $(wc -l data/training-$size.csv | cut -d\ -f1) samples... " - head -n 1 "data/training-$size.csv" > "data/shuf-$size.csv" - tail -n+2 "data/training-$size.csv" | shuf >> "data/shuf-$size.csv" - mv "data/shuf-$size.csv" "data/training-$size.csv" + # head -n 1 "data/training-$size.csv" > "data/shuf-$size.csv" + # tail -n+2 "data/training-$size.csv" | shuf >> "data/shuf-$size.csv" + # mv "data/shuf-$size.csv" "data/training-$size.csv" echo -en "Done.\n\tCompressing data... " - if [ -f "data/training-$size.csv.gz" ]; then - rm "data/training-$size.csv.gz" + # if [ -f "data/training-$size.csv.gz" ]; then + # rm "data/training-$size.csv.gz" + # fi + # gzip "data/training-$size.csv" + # echo "Done, available in data/training-$size.csv.gz" + if [ -f "data/validation-$size.csv.gz" ]; then + rm "data/validation-$size.csv.gz" fi - gzip "data/training-$size.csv" - echo "Done, available in data/training-$size.csv.gz" - # mv "data/training-$size.csv" "data/validation-$size.csv" - # gzip "data/validation-$size.csv" - # echo "Done, available in data/validation-$size.csv.gz" + mv "data/training-$size.csv" "data/validation-$size.csv" + gzip "data/validation-$size.csv" + echo "Done, available in data/validation-$size.csv.gz" } - make pptdb for size in 5 6; do echo extract $size notation,result - process $size 300000 + process $size 50000 done diff --git a/include/weights.c b/include/weights.c index c128ff7..9eeba07 100644 --- a/include/weights.c +++ b/include/weights.c @@ -1,7 +1,7 @@ #include "weights.h" const float conv2d_weights[KERN_NUM][KERN_SIZE][KERN_SIZE][KERN_CHAN] = - {{{{ 2.58312970e-01, -1.57649890e-02, -1.00786142e-01, 2.25934118e-01, +{{{{ 2.58312970e-01, -1.57649890e-02, -1.00786142e-01, 2.25934118e-01, 2.03468144e-01, 3.16539735e-01, -3.03449720e-01, -9.03429747e-01}, {-7.94863030e-02, -1.58257172e-01, 3.72665450e-02, -2.03835458e-01, -3.96497548e-01, -6.10545933e-01, 9.83448997e-02, -7.34975338e-01}, @@ -265,11 +265,11 @@ const float conv2d_weights[KERN_NUM][KERN_SIZE][KERN_SIZE][KERN_CHAN] = 5.70080839e-02, 2.49329448e-01, 4.34800774e-01, 1.90990448e-01}}}}; const float conv2d_biases[KERN_NUM] = - {-0.5954203, -1.0255206, 0.7012269, 0.7169469, 0.20402987, 0.29087773, - 0.5385397, 0.05127476, 0.65670264, -0.8095288, 0.57354295, -0.40450025}; +{-0.5954203, -1.0255206, 0.7012269, 0.7169469, 0.20402987, 0.29087773, + 0.5385397, 0.05127476, 0.65670264, -0.8095288, 0.57354295, -0.40450025}; const float dense1_weights[DENSE1_NUM][CONV_NUM+2] = - {{-7.94511437e-01, 5.71200252e-01, -1.40879720e-01, 1.24253288e-01, +{{-7.94511437e-01, 5.71200252e-01, -1.40879720e-01, 1.24253288e-01, -5.10804355e-01, 5.07906437e-01, -1.88285959e+00, -7.12222338e-01, -2.87340283e-01, 9.12622809e-01, -5.71415201e-02, 6.10791564e-01, -6.00090921e-01, 3.95308174e-02, 5.66913188e-01, -6.05273545e-02, @@ -523,11 +523,11 @@ const float dense1_weights[DENSE1_NUM][CONV_NUM+2] = 3.57535362e+00, 1.32344556e+00}}; const float dense1_biases[DENSE1_NUM] = - { 0.4636547, 0.13360201, -0.9697346, -1.0855523, 1.0256653, 0.5478138, - 0.7192499, 0.22356796, 1.3530691 }; +{ 0.4636547, 0.13360201, -0.9697346, -1.0855523, 1.0256653, 0.5478138, + 0.7192499, 0.22356796, 1.3530691, }; const float dense2_weights[DENSE2_NUM][DENSE1_NUM] = - {{-0.07496518, -1.219598, -0.77743036, -0.5582114, 0.3379165, 0.38208017, +{{-0.07496518, -1.219598, -0.77743036, -0.5582114, 0.3379165, 0.38208017, 0.7843754, 0.6464907, 0.4145456, }, {-1.2022296, -1.0770698, -0.28290233, 0.9415246, -0.0248992, -0.4531845, -0.43938553, -0.99121296, 1.058052, }, @@ -547,11 +547,12 @@ const float dense2_weights[DENSE2_NUM][DENSE1_NUM] = 0.56897026, -1.0157181, -0.41018486}}; const float dense2_biases[DENSE2_NUM] = - {-0.65758836, 0.11515713, -1.8776059, -0.5293117, -2.9236703, -0.8128398, - 2.5789695, -1.0744314, 0.810859, }; +{-0.65758836, 0.11515713, -1.8776059, -0.5293117, -2.9236703, -0.8128398, + 2.5789695, -1.0744314, 0.810859, }; const float output_weights[DENSE2_NUM] = - { 0.20715837, 0.4751412, 0.14602005, 0.24578023, -0.44211808, 0.22129269, - -0.8266294, -0.22375038, -0.35583553}; +{ 0.20715837, 0.4751412, 0.14602005, 0.24578023, -0.44211808, 0.22129269, + -0.8266294, -0.22375038, -0.35583553}; -const float output_bias = -0.9296964; +const float output_bias = +-0.9296964; diff --git a/src/train5.py b/src/train5.py index adb81a5..71a8652 100644 --- a/src/train5.py +++ b/src/train5.py @@ -119,20 +119,33 @@ def write_weights(model): string = re.sub(r'([0-9]+)\n', r'\1,\n', string) string = re.sub(r'([0-9]+) ', r'\1, ', string) return string - f = open("weights.txt", "w") + # Prepare everything in a sane memory order conv2d_weights = np.array(transpose(model.trainable_variables[0], perm=[3, 1, 0, 2])) conv2d_biases = np.array(model.trainable_variables[1]) dense1_weights = np.array(transpose(model.trainable_variables[2], perm=[1, 0])) dense1_biases = np.array(model.trainable_variables[3]) dense2_weights = np.array(transpose(model.trainable_variables[4], perm=[1, 0])) dense2_biases = np.array(model.trainable_variables[5]) - output_weights = np.array(transpose(model.trainable_variables[6], perm=[1, 0])) - output_biases = np.array(model.trainable_variables[7]) - for v in [conv2d_weights, conv2d_biases, - dense1_weights, dense1_biases, - dense2_weights, dense2_biases, - output_weights, output_biases]: - f.write(fix(str(v))+"\n\n") + output_weights = np.array(transpose(model.trainable_variables[6], perm=[1, 0])[0]) + output_bias = np.array(model.trainable_variables[7][0]) + # Prepare formatting + names = ["conv2d_weights[KERN_NUM][KERN_SIZE][KERN_SIZE][KERN_CHAN]", + "conv2d_biases[KERN_NUM]", + "dense1_weights[DENSE1_NUM][CONV_NUM+2]", + "dense1_biases[DENSE1_NUM]", + "dense2_weights[DENSE2_NUM][DENSE1_NUM]", + "dense2_biases[DENSE2_NUM]", + "output_weights[DENSE2_NUM]", + "output_bias"] + variables = [conv2d_weights, conv2d_biases, + dense1_weights, dense1_biases, + dense2_weights, dense2_biases, + output_weights, output_bias] + # Write to file + f = open("weights.c", "w") + f.write("#include \"weights.h\"\n\n") + for (name, val) in zip(names, variables): + f.write("const float "+name+" =\n"+fix(str(val))+";\n\n") f.close() |