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- # membuat model sine yang berbasis nn dan konversi ke C array
- # mesti pakai everyml
- import math
- import numpy as np
- from tensorflow.keras.models import Sequential
- from tensorflow.keras.layers import Dense
- # generate data antara 0 sd 2pi sebanyak 1000 data
- X=np.random.uniform(low=0, high=2*math.pi, size=1000)
- y=np.sin(X)
- model=Sequential()
- model.add(Dense(16, activation='relu',input_dim=1))
- model.add(Dense(16, activation='relu'))
- # bila tidak dituliskan activationny linear
- model.add(Dense(1))
- model.compile(optimizer='adam',loss='mse', metrics=['mse'])
- model.fit(X,y,epochs=100, batch_size=16)
- print (model.summary())
- from everywhereml.code_generators.tensorflow import tf_porter
- cpp_code = tf_porter(model, X,y).to_cpp(instance_name='sineNN')
- print(cpp_code)
- file = open ('sineNN.h',"w+")
- content= str(cpp_code)
- file.write(content)
- file.close
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