steffen/self-replicating-neural-networks
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Si11ium
2019-03-15 18:59:50 +01:00
parent 809f178e2f
commit 869833da3b
39 changed files with 275 additions and 120 deletions
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6
code/setups/training-fixpoints.py
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@@ -40,8 +40,8 @@ if __name__ == '__main__':
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: 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)]
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 = []
all_names = []
@@ -51,7 +51,7 @@ if __name__ == '__main__':
for _ in tqdm(range(exp.trials)):
net = ParticleDecorator(net_generator())
net = TrainingNeuralNetworkDecorator(net).with_params(epsilon=exp.epsilon)
name = str(net.net.__class__.__name__) + " activiation='" + str(net.get_keras_params().get('activation')) + "' use_bias=" + str(net.get_keras_params().get('use_bias'))
name = str(net.net.net.__class__.__name__) + " activiation='" + str(net.get_keras_params().get('activation')) + "' use_bias=" + str(net.get_keras_params().get('use_bias'))
for run_id in range(exp.run_count):
loss = net.compiled().train(epoch=run_id+1)
count(counters, net, notable_nets)