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from tensorboardX import SummaryWriter
import time
import random
hparam = {'lr': [0.1, 0.01, 0.001],
'bsize': [1, 2, 4],
'n_hidden': [100, 200]}
metrics = {'accuracy', 'loss'}
def train(lr, bsize, n_hidden):
x = random.random()
return x, x*5
with SummaryWriter() as w:
for lr in hparam['lr']:
for bsize in hparam['bsize']:
for n_hidden in hparam['n_hidden']:
accu, loss = train(lr, bsize, n_hidden)
w.add_hparams({'lr': lr, 'bsize': bsize, 'n_hidden': n_hidden},
{'accuracy': accu, 'loss': loss})
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