I'm using nnet.bn.batch_normalization_train() and
nnet.bn.batch_normalization_test() for batch normalization, however during
test phase, nnet.bn.batch_normalization_test() produces wrong results. For
the time being, I just use nnet.bn.batch_normalization_train() with
*running_average_factor
*set to zero for test phase as:
if deterministic is False: # train phase
normalized, input_mean, input_inv_std, self.mean, self.var =
T.nnet.bn.batch_normalization_train(input, self.gamma, self.beta, self.axes,
self.epsilon, self.alpha, self.mean, self.var)
else: # test phase
# normalized = T.nnet.bn.batch_normalization_test(input, self.gamma,
self.beta, self.mean, self.var, self.axes, self.epsilon)
normalized, _, _, _, _ = T.nnet.bn.batch_normalization_train(input,
self.gamma, self.beta, self.axes, self.epsilon, 0.0, self.mean, self.var)
return normalized
My theano version is
'0.9.0beta1.dev-b2afa088d1cb416b4507348019af34adae908b73', CUDA 8.0 and
CuDNN 5.1
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