OneHot Indices issues

[andrewasche]

Got this issue both when running the Exercise+3b from Coursera's Practical Deep Learning class. I have also got this issue on the 02 VGG Fine-Tuning.ipynb. I got this issue on neon 2.2 and aeon 1.0 . I haven't been successful finding any other info on this issue.

Evaluating the model
We can now compute the misclassification on the test set to see how well we did.

Check the performance on the supplied test set

from neon.transforms import Misclassification

​

error_pct = 100 * model.eval(test_set, metric=Misclassification())

print 'Misclassification error = %.1f%%' % error_pct

---

AssertionError Traceback (most recent call last)
in ()
2 from neon.transforms import Misclassification
3
----> 4 error_pct = 100 * model.eval(test_set, metric=Misclassification())
5 print 'Misclassification error = %.1f%%' % error_pct

/home/andrew/anaconda2/envs/neon/lib/python2.7/site-packages/neon-2.2.0-py2.7.egg/neon/models/model.pyc in eval(self, dataset, metric)
267 else:
268 ndata = dataset.ndata
--> 269 for x, t in dataset:
270 x = self.fprop(x, inference=True)
271

/home/andrew/anaconda2/envs/neon/lib/python2.7/site-packages/neon-2.2.0-py2.7.egg/neon/data/dataloader_transformers.pyc in iter(self)
25
26 def iter(self):
---> 27 for tup in self.dataloader:
28 if self.index is None:
29 yield self.transform(tup)

/home/andrew/anaconda2/envs/neon/lib/python2.7/site-packages/neon-2.2.0-py2.7.egg/neon/data/dataloader_transformers.pyc in iter(self)
25
26 def iter(self):
---> 27 for tup in self.dataloader:
28 if self.index is None:
29 yield self.transform(tup)

/home/andrew/anaconda2/envs/neon/lib/python2.7/site-packages/neon-2.2.0-py2.7.egg/neon/data/dataloader_transformers.pyc in iter(self)
29 yield self.transform(tup)
30 else:
---> 31 ret = self.transform(tup[self.index])
32 if ret is None:
33 raise ValueError(

/home/andrew/anaconda2/envs/neon/lib/python2.7/site-packages/neon-2.2.0-py2.7.egg/neon/data/dataloader_transformers.pyc in transform(self, t)
54
55 def transform(self, t):
---> 56 self.output[:] = self.be.onehot(t, axis=0)
57 return self.output
58

/home/andrew/anaconda2/envs/neon/lib/python2.7/site-packages/neon-2.2.0-py2.7.egg/neon/backends/backend.pyc in onehot(self, indices, axis, out)
1533 raise ValueError("bad axis for onehot")
1534 #print(indices)
-> 1535 #assert (indices.dtype in [np.dtype(np.int32), np.dtype(np.uint32)]), "onehot indices "
1536 # "should be int32 or uint32, got " + str(indices.dtype)
1537 return OpTreeNode.build("onehot", None, None, idx=indices, axis=axis, out=out)

AssertionError: onehot indices should be int32 or uint32, got float32