import matplotlib.pyplot as plt if __name__ == "__main__": dataX = np.linspace(0, 2 * 3.14, 1000).reshape(1000, 1) dataY = np.sin(dataX) nNL = [1, 10, 10, 1] # Number of neurons per every hidden layer. actFunc = ANN.ReLU() actFuncFinal = ANN.Act_dummy() fcann = ANN.FCANN(nNL, actFunc, actFuncFinal) fcann.make_random_w_b(0.1, -0.05, 0.0001) lossFunc = ANN.SumOfSquares() fcann.train(dataX, dataY, 200, 0.02,\ randomizeData = True, showFigure = True,\ lossFunc = lossFunc) pathName = "/home/yaoyu/SourceCodes/NN/SimpleANN/SavedANN" fcann.save_to_file(pathName) # Test. print("========== Test. ==============") dataX = np.linspace(0, 2 * 3.14, 2000) dataY = np.sin(dataX)