When loading this model with Chainer and attempting to evaluate a batch of images it complains that the eps param in batch-norm is < 1e-5
RuntimeError Traceback (most recent call last)
in ()
1 dta = fake_input_data_cf[:8]
----> 2 pred = sym(inputs={'data':dta}, outputs=['fc6'])
/anaconda/envs/py35/lib/python3.5/site-packages/chainer/links/caffe/caffe_function.py in call(self, inputs, outputs, disable, **kwargs)
218 func = self.forwards[func_name]
219 input_vars = tuple(variables[blob] for blob in bottom)
--> 220 output_vars = func(*input_vars)
221 if not isinstance(output_vars, collections.Iterable):
222 output_vars = output_vars,
/anaconda/envs/py35/lib/python3.5/site-packages/chainer/links/caffe/caffe_function.py in call(self, x)
567
568 def call(self, x):
--> 569 return self.func(x, *self.args, **self.kwargs)
570
571
/anaconda/envs/py35/lib/python3.5/site-packages/chainer/links/caffe/caffe_function.py in call(self, *xs, **kwargs)
606
607 def call(self, *xs, **kwargs):
--> 608 return self.caffe_func[self.name](*xs, **kwargs)
609
610
/anaconda/envs/py35/lib/python3.5/site-packages/chainer/links/normalization/batch_normalization.py in call(self, x, **kwargs)
142 ret = functions.batch_normalization(
143 x, gamma, beta, eps=self.eps, running_mean=self.avg_mean,
--> 144 running_var=self.avg_var, decay=decay)
145 else:
146 # Use running average statistics or fine-tuned statistics.
/anaconda/envs/py35/lib/python3.5/site-packages/chainer/functions/normalization/batch_normalization.py in batch_normalization(x, gamma, beta, **kwargs)
527 ('running_var', None), ('decay', 0.9))
528
--> 529 return BatchNormalization(eps, running_mean, running_var, decay).apply(
530 (x, gamma, beta))[0]
531
/anaconda/envs/py35/lib/python3.5/site-packages/chainer/functions/normalization/batch_normalization.py in init(self, eps, mean, var, decay)
30 if eps < 1e-5:
31 msg = 'cuDNN does not allow an eps value less than 1e-5.'
---> 32 raise RuntimeError(msg)
33 self.decay = decay
34
RuntimeError: cuDNN does not allow an eps value less than 1e-5.