Multi-GPU Training on TensorFlow with Keras

https://medium.com/@kuza55/transparent-multi-gpu-training-on-tensorflow-with-keras-8b0016fd9012

https://github.com/kuza55/keras-extras/blob/master/utils/multi_gpu.py

import numpy as np
import keras
from keras.models import Sequential
from keras.layers import Dense

model = Sequential()
model.add(Dense(4000, input_dim=8000, activation='tanh'))
model.add(Dense(2000, input_dim=8000, activation='relu'))
model.add(Dense(500, activation='relu'))
model.add(Dense(300, activation='relu'))
model.add(Dense(1, activation='sigmoid'))

print (model.summary())

model = make_parallel(model, 4)
optimizer = keras.optimizers.Adam(lr=0.0001)
model.compile(loss='binary_crossentropy', optimizer=optimizer, metrics=['accuracy'])

x = np.random.rand(131072, 8000)
y = np.random.randint(0, 2, (131072, 1))

model.fit(x, y, batch_size=2048*4)