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func.py
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func.py
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from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import numpy as np
import deepxde as dde
def main():
def func(x):
"""
x: array_like, N x D_in
y: array_like, N x D_out
"""
return x * np.sin(5 * x)
geom = dde.geometry.Interval(-1, 1)
num_train = 16
num_test = 100
data = dde.data.Func(geom, func, num_train, num_test)
activation = "tanh"
initializer = "Glorot uniform"
net = dde.maps.FNN([1] + [20] * 3 + [1], activation, initializer)
model = dde.Model(data, net)
model.compile("adam", lr=0.001, metrics=["l2 relative error"])
losshistory, train_state = model.train(epochs=10000)
dde.saveplot(losshistory, train_state, issave=True, isplot=True)
if __name__ == "__main__":
main()