I tried to run examples/mnist-deep-classifier.py, but it fails.
UnsupervisedPretrainer.itertrain wants to copy the parameters back, but the check there for if not param.name.startswith('tied') does not work. No name starts with 'tied', and anyway the extra 'b' are not tied but extra.
So it tries to copy back hid4.b, which does not exist on the original network.
Error:
Traceback (most recent call last):
File "examples/mnist-deep-classifier.py", line 19, in <module>
train_batches=100)
File "theanets/theanets/graph.py", line 369, in train
for monitors in self.itertrain(*args, **kwargs):
File "theanets/theanets/graph.py", line 345, in itertrain
for i, monitors in enumerate(algo.itertrain(train, valid, **kwargs)):
File "theanets/theanets/trainer.py", line 337, in itertrain
self.network.find(l, p).set_value(param.get_value())
File "theanets/theanets/graph.py", line 484, in find
raise KeyError(which)
KeyError: 'hid4'
I tried to run examples/mnist-deep-classifier.py, but it fails.
UnsupervisedPretrainer.itertrain
wants to copy the parameters back, but the check there forif not param.name.startswith('tied')
does not work. No name starts with 'tied', and anyway the extra 'b' are not tied but extra.Params is this:
[hid1.w, hid1.b, hid2.w, hid2.b, hid3.w, hid3.b, hid4.b, hid5.b, out.b]
So it tries to copy back hid4.b, which does not exist on the original network.
Error: