weightwise experiments

code/experiments/exp-FixpointExperiment-_6511565650566781-0/log.txt

@@ -1 +0,0 @@
-{'divergent': 38, 'fix_zero': 62, 'fix_other': 0, 'fix_sec': 0, 'other': 0}

code/experiments/exp-FixpointExperiment-_6511565800569721-0/log.txt

@@ -1 +0,0 @@
-{'divergent': 0, 'fix_zero': 100, 'fix_other': 0, 'fix_sec': 0, 'other': 0}

code/experiments/exp-FixpointExperiment-_813945717034465-0/log.txt

@@ -1 +0,0 @@
-{'divergent': 3, 'fix_zero': 97, 'fix_other': 0, 'fix_sec': 0, 'other': 0}

code/setups/experiments/exp-fixpoint-density-_6511547300443771-0/log.txt

@@ -1,36 +0,0 @@
-ParticleDecorator activiation='linear' use_bias='False'
-{'divergent': 0, 'fix_zero': 0, 'fix_other': 0, 'fix_sec': 0, 'other': 100}
-
-
-ParticleDecorator activiation='linear' use_bias='False'
-{'divergent': 0, 'fix_zero': 0, 'fix_other': 0, 'fix_sec': 0, 'other': 100}
-
-
-ParticleDecorator activiation='linear' use_bias='False'
-{'divergent': 0, 'fix_zero': 0, 'fix_other': 0, 'fix_sec': 0, 'other': 100}
-
-
-ParticleDecorator activiation='sigmoid' use_bias='False'
-{'divergent': 0, 'fix_zero': 0, 'fix_other': 0, 'fix_sec': 0, 'other': 100}
-
-
-ParticleDecorator activiation='sigmoid' use_bias='False'
-{'divergent': 0, 'fix_zero': 0, 'fix_other': 0, 'fix_sec': 0, 'other': 100}
-
-
-ParticleDecorator activiation='sigmoid' use_bias='False'
-{'divergent': 0, 'fix_zero': 0, 'fix_other': 0, 'fix_sec': 0, 'other': 100}
-
-
-ParticleDecorator activiation='relu' use_bias='False'
-{'divergent': 0, 'fix_zero': 0, 'fix_other': 0, 'fix_sec': 0, 'other': 100}
-
-
-ParticleDecorator activiation='relu' use_bias='False'
-{'divergent': 0, 'fix_zero': 0, 'fix_other': 0, 'fix_sec': 0, 'other': 100}
-
-
-ParticleDecorator activiation='relu' use_bias='False'
-{'divergent': 0, 'fix_zero': 0, 'fix_other': 0, 'fix_sec': 0, 'other': 100}
-
-

code/setups/experiments/exp-known-fixpoint-variation-_813943796847257-0/log.txt

@@ -1,30 +0,0 @@
-variation 10e-0
-avg time to vergence 3.72
-avg time as fixpoint 0
-variation 10e-1
-avg time to vergence 5.13
-avg time as fixpoint 0
-variation 10e-2
-avg time to vergence 6.53
-avg time as fixpoint 0
-variation 10e-3
-avg time to vergence 8.09
-avg time as fixpoint 0
-variation 10e-4
-avg time to vergence 9.81
-avg time as fixpoint 0.06
-variation 10e-5
-avg time to vergence 11.43
-avg time as fixpoint 1.51
-variation 10e-6
-avg time to vergence 13.15
-avg time as fixpoint 3.34
-variation 10e-7
-avg time to vergence 14.57
-avg time as fixpoint 4.79
-variation 10e-8
-avg time to vergence 22.41
-avg time as fixpoint 12.37
-variation 10e-9
-avg time to vergence 26.17
-avg time as fixpoint 16.11

code/setups/experiments/exp-mixed-self-fixpoints-_3255826099701415-0/log.txt

@@ -1,8 +0,0 @@
-ParticleDecorator activiation='linear' use_bias=False
-{'xs': [0, 100, 200, 300, 400, 500, 600, 700, 800, 900, 1000], 'ys': [0.45, 0.4, 0.6, 0.8, 0.95, 0.85, 0.95, 0.85, 0.9, 1.0, 0.8]}
-
-
-ParticleDecorator activiation='linear' use_bias=False
-{'xs': [0, 100, 200, 300, 400, 500, 600, 700, 800, 900, 1000], 'ys': [0.95, 0.9, 0.9, 0.9, 0.95, 0.8, 0.9, 0.9, 0.85, 0.85, 0.9]}
-
-

code/setups/fixpoint-density.py

@@ -35,8 +35,8 @@ if __name__ == '__main__':
         exp.epsilon = 1e-4
         net_generators = []
         for activation in ['linear', 'sigmoid', 'relu']:
-            net_generators += [lambda activation=activation: WeightwiseNeuralNetwork(width=2, depth=2).with_keras_params(activation=activation, use_bias=False)]
+            # net_generators += [lambda activation=activation: WeightwiseNeuralNetwork(width=2, depth=2).with_keras_params(activation=activation, use_bias=False)]
-            # net_generators += [lambda activation=activation: AggregatingNeuralNetwork(aggregates=4, width=2, depth=2).with_keras_params(activation=activation, use_bias=False)]
+            net_generators += [lambda activation=activation: AggregatingNeuralNetwork(aggregates=4, width=2, depth=2).with_keras_params(activation=activation, use_bias=False)]
             # net_generators += [lambda activation=activation: FFTNeuralNetwork(aggregates=4, width=2, depth=2).with_keras_params(activation=activation, use_bias=False)]
             # net_generators += [lambda activation=activation: RecurrentNeuralNetwork(width=2, depth=2).with_keras_params(activation=activation, use_bias=False)]
         all_counters = []

code/setups/known-fixpoint-variation.py

@@ -26,7 +26,8 @@ def generate_fixpoint_weights():
 
 
 def generate_fixpoint_net():
-    net = WeightwiseNeuralNetwork(width=2, depth=2).with_keras_params(activation='sigmoid')
+    # net = WeightwiseNeuralNetwork(width=2, depth=2).with_keras_params(activation='sigmoid')
+    net = AggregatingNeuralNetwork(width=2, depth=2).with_keras_params(activation='sigmoid')
     net.set_weights(generate_fixpoint_weights())
     return net
 

code/setups/learn_from_soup.py

@@ -68,8 +68,8 @@ with SoupExperiment('learn-from-soup') as exp:
     net_generators = []
     for activation in ['sigmoid']: #['linear', 'sigmoid', 'relu']:
         for use_bias in [False]:
-            net_generators += [lambda activation=activation, use_bias=use_bias: WeightwiseNeuralNetwork(width=2, depth=2).with_keras_params(activation=activation, use_bias=use_bias)]
+            # net_generators += [lambda activation=activation, use_bias=use_bias: WeightwiseNeuralNetwork(width=2, depth=2).with_keras_params(activation=activation, use_bias=use_bias)]
-            # net_generators += [lambda activation=activation, use_bias=use_bias: AggregatingNeuralNetwork(aggregates=4, width=2, depth=2).with_keras_params(activation=activation, use_bias=use_bias)]
+            net_generators += [lambda activation=activation, use_bias=use_bias: AggregatingNeuralNetwork(aggregates=4, width=2, depth=2).with_keras_params(activation=activation, use_bias=use_bias)]
             # net_generators += [lambda activation=activation, use_bias=use_bias: RecurrentNeuralNetwork(width=2, depth=2).with_keras_params(activation=activation, use_bias=use_bias)]
 
     all_names = []

code/setups/mixed-self-fixpoints.py

@@ -60,8 +60,8 @@ if __name__ == '__main__':
         net_generators = []
         for activation in ['linear']:  # , 'sigmoid', 'relu']:
             for use_bias in [False]:
-                net_generators += [lambda activation=activation, use_bias=use_bias: WeightwiseNeuralNetwork(width=2, depth=2).with_keras_params(activation=activation, use_bias=use_bias)]
+                # net_generators += [lambda activation=activation, use_bias=use_bias: WeightwiseNeuralNetwork(width=2, depth=2).with_keras_params(activation=activation, use_bias=use_bias)]
-                # net_generators += [lambda activation=activation, use_bias=use_bias: AggregatingNeuralNetwork(aggregates=4, width=2, depth=2).with_keras_params(activation=activation, use_bias=use_bias)]
+                net_generators += [lambda activation=activation, use_bias=use_bias: AggregatingNeuralNetwork(aggregates=4, width=2, depth=2).with_keras_params(activation=activation, use_bias=use_bias)]
                 # net_generators += [lambda activation=activation, use_bias=use_bias: FFTNeuralNetwork(aggregates=4, width=2, depth=2).with_keras_params(activation=activation, use_bias=use_bias)]
                 # net_generators += [lambda activation=activation, use_bias=use_bias: RecurrentNeuralNetwork(width=2, depth=2).with_keras_params(activation=activation, use_bias=use_bias)]
 

code/setups/mixed-soup.py

@@ -62,8 +62,8 @@ with Experiment('mixed-self-fixpoints') as exp:
     net_generators = []
     for activation in ['linear']: #['linear', 'sigmoid', 'relu']:
         for use_bias in [False]:
-            net_generators += [lambda activation=activation, use_bias=use_bias: WeightwiseNeuralNetwork(width=2, depth=2).with_keras_params(activation=activation, use_bias=use_bias)]
+            # net_generators += [lambda activation=activation, use_bias=use_bias: WeightwiseNeuralNetwork(width=2, depth=2).with_keras_params(activation=activation, use_bias=use_bias)]
-            # net_generators += [lambda activation=activation, use_bias=use_bias: AggregatingNeuralNetwork(aggregates=4, width=2, depth=2).with_keras_params(activation=activation, use_bias=use_bias)]
+            net_generators += [lambda activation=activation, use_bias=use_bias: AggregatingNeuralNetwork(aggregates=4, width=2, depth=2).with_keras_params(activation=activation, use_bias=use_bias)]
             # net_generators += [lambda activation=activation, use_bias=use_bias: RecurrentNeuralNetwork(width=2, depth=2).with_keras_params(activation=activation, use_bias=use_bias)]
 
     all_names = []

code/setups/training-fixpoints.py

@@ -39,8 +39,8 @@ if __name__ == '__main__':
         net_generators = []
         for activation in ['linear']:  # , 'sigmoid', 'relu']:
             for use_bias in [False]:
-                net_generators += [lambda activation=activation, use_bias=use_bias: WeightwiseNeuralNetwork(width=2, depth=2).with_keras_params(activation=activation, use_bias=use_bias)]
+                # net_generators += [lambda activation=activation, use_bias=use_bias: WeightwiseNeuralNetwork(width=2, depth=2).with_keras_params(activation=activation, use_bias=use_bias)]
-                # net_generators += [lambda activation=activation, use_bias=use_bias: AggregatingNeuralNetwork(aggregates=4, width=2, depth=2).with_keras_params(activation=activation, use_bias=use_bias)]
+                net_generators += [lambda activation=activation, use_bias=use_bias: AggregatingNeuralNetwork(aggregates=4, width=2, depth=2).with_keras_params(activation=activation, use_bias=use_bias)]
                 # net_generators += [lambda activation=activation, use_bias=use_bias: RecurrentNeuralNetwork(width=2, depth=2).with_keras_params(activation=activation, use_bias=use_bias)]
         all_counters = []
         all_notable_nets = []

code/weightwise_experiments/exp-fixpoint-density-_3256002726938743-0/log.txt

@@ -0,0 +1,12 @@
+ParticleDecorator activiation='linear' use_bias='False'
+{'divergent': 0, 'fix_zero': 0, 'fix_other': 0, 'fix_sec': 0, 'other': 100}
+
+
+ParticleDecorator activiation='sigmoid' use_bias='False'
+{'divergent': 0, 'fix_zero': 0, 'fix_other': 0, 'fix_sec': 0, 'other': 100}
+
+
+ParticleDecorator activiation='relu' use_bias='False'
+{'divergent': 0, 'fix_zero': 0, 'fix_other': 0, 'fix_sec': 0, 'other': 100}
+
+

code/weightwise_experiments/exp-known-fixpoint-variation-_3256002757529753-0/log.txt

@@ -0,0 +1,30 @@
+variation 10e-0
+avg time to vergence 3.65
+avg time as fixpoint 0
+variation 10e-1
+avg time to vergence 5.07
+avg time as fixpoint 0
+variation 10e-2
+avg time to vergence 6.49
+avg time as fixpoint 0
+variation 10e-3
+avg time to vergence 7.97
+avg time as fixpoint 0
+variation 10e-4
+avg time to vergence 9.81
+avg time as fixpoint 0.04
+variation 10e-5
+avg time to vergence 11.4
+avg time as fixpoint 1.51
+variation 10e-6
+avg time to vergence 13.14
+avg time as fixpoint 3.26
+variation 10e-7
+avg time to vergence 14.63
+avg time as fixpoint 4.95
+variation 10e-8
+avg time to vergence 21.35
+avg time as fixpoint 11.47
+variation 10e-9
+avg time to vergence 26.36
+avg time as fixpoint 16.3

code/weightwise_experiments/exp-learn-from-soup-_6512006057392099-0/log.txt

@@ -0,0 +1,4 @@
+TrainingNeuralNetworkDecorator activiation='sigmoid' use_bias=False
+{'xs': [0, 10, 20, 30, 40, 50, 60, 70, 80, 90, 100], 'ys': [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], 'zs': [0.0, 1.0, 3.4, 7.0, 8.3, 9.3, 9.9, 9.5, 9.7, 9.9, 10.0]}
+
+

code/weightwise_experiments/exp-mixed-self-fixpoints-_3256025691277105-0/log.txt

@@ -0,0 +1,4 @@
+TrainingNeuralNetworkDecorator activiation='linear' use_bias=False
+{'xs': [0, 10, 20, 30, 40, 50, 60, 70, 80, 90, 100], 'ys': [0.2, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.2, 0.0, 0.0], 'zs': [0.0, 0.0, 0.6, 2.2, 3.5, 4.8, 5.6, 7.1, 8.3, 7.5, 9.0]}
+
+

code/weightwise_experiments/exp-mixed-self-fixpoints-_6512040991372981-0/log.txt

@@ -0,0 +1,4 @@
+ParticleDecorator activiation='linear' use_bias=False
+{'xs': [0, 100, 200, 300, 400, 500, 600, 700, 800, 900, 1000], 'ys': [0.4, 0.45, 0.7, 0.9, 1.0, 0.9, 0.9, 1.0, 0.9, 0.9, 0.9]}
+
+

code/weightwise_experiments/exp-training_fixpoint-_6512069271603393-0/log.txt

@@ -2,7 +2,3 @@ ParticleDecorator activiation='linear' use_bias=False
 {'divergent': 0, 'fix_zero': 0, 'fix_other': 19, 'fix_sec': 0, 'other': 1}
 
 
-ParticleDecorator activiation='linear' use_bias=False
-{'divergent': 0, 'fix_zero': 0, 'fix_other': 0, 'fix_sec': 0, 'other': 20}
-
-