train_model.py

import numpy as np
from alexnet import alexnet

WIDTH=80
HEIGHT=60
LR=1e-3
EPOCHS=8

MODEL_NAME='pygta5-car-{}-{}-{}-epochs.model'.format(LR, 'alexnetv2', EPOCHS)

model = alexnet(WIDTH, HEIGHT, LR)

train_data=np.load('training_data_v4.npy')

train=train_data[:-5000]
test=train_data[-5000:]

X=np.array([i[0] for i in train]).reshape(-1, WIDTH, HEIGHT, 1)
Y=([i[1] for i in train])

test_x=np.array([i[0] for i in test]).reshape(-1, WIDTH, HEIGHT, 1)
test_y=([i[1] for i in test])

model.fit({'input':X}, {'targets' : Y}, n_epoch=EPOCHS,
            validation_set=({'input':test_x}, {'targets':test_y}),
            snapshot_step=5000, show_metric=True, run_id=MODEL_NAME)



model.save(MODEL_NAME)