> Traceback (most recent call last):


 "clipnorm_issue.py", line 21, in <module>

m.fit(x,y)


 "/home/..../keras/engine/training.py", line 1008, in fit

self._make_train_function()


 "/home/..../keras/engine/training.py", line 497, in _make_train_function

loss=self.total_loss)


 "/home/..../keras/legacy/interfaces.py", line 91, in wrapper

return func(*args, **kwargs)


 "/home/..../keras/optimizers.py", line 367, in get_updates

grads = self.get_gradients(loss, params)


 "/home/..../keras/optimizers.py", line 86, in get_gradients

norm = K.sqrt(sum([K.sum(K.square(g)) for g in grads]))


 "/home/..../keras/backend/tensorflow_backend.py", line 1473, in sqrt

zero = _to_tensor(0., x.dtype.base_dtype)
AttributeError: 'int' object has no attribute 'dtype'

Traceback (most recent call last): 
 "/home/edh/Projects/abs/letsencrypt-git/src/letsencrypt-0.0.0.dev20151006/letsencrypt/tests/cli_test.py", line 78, in test_help
self.assertTrue("--nginx-ctl" in out)AssertionError: False is not true