VividNet/NeuralNetPhiR.py at master · Kayzaks/VividNet · GitHub

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from NeuralNet import NeuralNet

import keras
from keras.models import Sequential
from keras.layers import Dense, Dropout, Activation, Flatten, BatchNormalization
from keras.layers import Conv2D, MaxPooling2D
from keras import backend


class NeuralNetPhiR(NeuralNet):

    def beginTraining(self):
        self.setTrainingParameters(200000, 1000, 128, 40)


    def defineModel(self, inputShape : tuple, outputSize : int):
        model = Sequential()

        model.add(Dense(1024, activation='relu', input_shape=inputShape))
        model.add(Dense(512, activation='relu'))
        model.add(Dense(256, activation='relu'))
        model.add(Dense(256, activation='relu'))
        model.add(Dense(128, activation='relu'))
        model.add(Dense(128, activation='relu'))
        model.add(Dense(64, activation='relu'))

        model.add(Dense(outputSize, activation='linear'))

        return model