"sigmoid.0 is not in list" error when I run example/mnist_gan.py

[AlexZhou1995]

Hi,
Thank you for develop this and gandlf looks really good. But I met "sigmoid.0 is not in list" error when I run example/mnist_gan.py.

error logs shows as follow:

And many same errors like:

And in the end:

[AlexZhou1995]

I got the same error in xor.py without using GPU.

I install gandlf from pip and update keras from 1.1.2 to 1.2.2.

[smartsystems4u]

Same here, while trying the MNIST example.
using:
Theano: 0.8.2
Keras: 1.2.2
Gandlf: 0.0.5

error

Downloading data from https://s3.amazonaws.com/img-datasets/mnist.pkl.gz

ValueError Traceback (most recent call last)
in ()
310 y_train_ohe = np.eye(10)[np.squeeze(y_train)]
311
--> 312 model = train_model(args, X_train, y_train, y_train_ohe)
313
314 if args.plot:

in train_model(args, X_train, y_train, y_train_ohe)
243 inputs += [X_train]
244
--> 245 model.fit(inputs, outputs, nb_epoch=args.nb_epoch, batch_size=args.nb_batch)
246
247 return model

/Users/willem/dev/ml/keras/mlpy/lib/python2.7/site-packages/gandlf/models.pyc in fit(self, x, y, batch_size, nb_epoch, verbose, callbacks, validation_split, validation_data, shuffle, class_weight, sample_weight, initial_epoch)
891 output_names, output_shapes, False, batch_size)
892
--> 893 self._make_train_function()
894 train_fn = self.train_function
895

/Users/willem/dev/ml/keras/mlpy/lib/python2.7/site-packages/gandlf/models.pyc in _make_train_function(self)
562 self._collected_trainable_weights[0],
563 self.constraints,
--> 564 self.generator_loss)
565
566 # Gets the discriminator updates.

/Users/willem/dev/ml/keras/mlpy/lib/python2.7/site-packages/keras/optimizers.pyc in get_updates(self, params, constraints, loss)
414
415 def get_updates(self, params, constraints, loss):
--> 416 grads = self.get_gradients(loss, params)
417 self.updates = [K.update_add(self.iterations, 1)]
418

/Users/willem/dev/ml/keras/mlpy/lib/python2.7/site-packages/keras/optimizers.pyc in get_gradients(self, loss, params)
80
81 def get_gradients(self, loss, params):
---> 82 grads = K.gradients(loss, params)
83 if hasattr(self, 'clipnorm') and self.clipnorm > 0:
84 norm = K.sqrt(sum([K.sum(K.square(g)) for g in grads]))

/Users/willem/dev/ml/keras/mlpy/lib/python2.7/site-packages/keras/backend/theano_backend.pyc in gradients(loss, variables)
971
972 def gradients(loss, variables):
--> 973 return T.grad(loss, variables)
974
975

/Users/willem/dev/ml/keras/mlpy/lib/python2.7/site-packages/theano/gradient.pyc in grad(cost, wrt, consider_constant, disconnected_inputs, add_names, known_grads, return_disconnected, null_gradients)
458
459 var_to_app_to_idx = _populate_var_to_app_to_idx(
--> 460 outputs, wrt, consider_constant)
461
462 # build a dict mapping var to the gradient of cost with respect to var

/Users/willem/dev/ml/keras/mlpy/lib/python2.7/site-packages/theano/gradient.pyc in _populate_var_to_app_to_idx(outputs, wrt, consider_constant)
885 # add all variables that are true ancestors of the cost
886 for output in outputs:
--> 887 account_for(output)
888
889 # determine which variables have elements of wrt as a true

/Users/willem/dev/ml/keras/mlpy/lib/python2.7/site-packages/theano/gradient.pyc in account_for(var)
881 if i not in idx:
882 idx.append(i)
--> 883 account_for(ipt)
884
885 # add all variables that are true ancestors of the cost

/Users/willem/dev/ml/keras/mlpy/lib/python2.7/site-packages/theano/gradient.pyc in account_for(var)
881 if i not in idx:
882 idx.append(i)
--> 883 account_for(ipt)
884
885 # add all variables that are true ancestors of the cost

/Users/willem/dev/ml/keras/mlpy/lib/python2.7/site-packages/theano/gradient.pyc in account_for(var)
881 if i not in idx:
882 idx.append(i)
--> 883 account_for(ipt)
884
885 # add all variables that are true ancestors of the cost

/Users/willem/dev/ml/keras/mlpy/lib/python2.7/site-packages/theano/gradient.pyc in account_for(var)
881 if i not in idx:
882 idx.append(i)
--> 883 account_for(ipt)
884
885 # add all variables that are true ancestors of the cost

/Users/willem/dev/ml/keras/mlpy/lib/python2.7/site-packages/theano/gradient.pyc in account_for(var)
881 if i not in idx:
882 idx.append(i)
--> 883 account_for(ipt)
884
885 # add all variables that are true ancestors of the cost

/Users/willem/dev/ml/keras/mlpy/lib/python2.7/site-packages/theano/gradient.pyc in account_for(var)
881 if i not in idx:
882 idx.append(i)
--> 883 account_for(ipt)
884
885 # add all variables that are true ancestors of the cost

/Users/willem/dev/ml/keras/mlpy/lib/python2.7/site-packages/theano/gradient.pyc in account_for(var)
881 if i not in idx:
882 idx.append(i)
--> 883 account_for(ipt)
884
885 # add all variables that are true ancestors of the cost

/Users/willem/dev/ml/keras/mlpy/lib/python2.7/site-packages/theano/gradient.pyc in account_for(var)
881 if i not in idx:
882 idx.append(i)
--> 883 account_for(ipt)
884
885 # add all variables that are true ancestors of the cost

/Users/willem/dev/ml/keras/mlpy/lib/python2.7/site-packages/theano/gradient.pyc in account_for(var)
881 if i not in idx:
882 idx.append(i)
--> 883 account_for(ipt)
884
885 # add all variables that are true ancestors of the cost

/Users/willem/dev/ml/keras/mlpy/lib/python2.7/site-packages/theano/gradient.pyc in account_for(var)
881 if i not in idx:
882 idx.append(i)
--> 883 account_for(ipt)
884
885 # add all variables that are true ancestors of the cost

/Users/willem/dev/ml/keras/mlpy/lib/python2.7/site-packages/theano/gradient.pyc in account_for(var)
881 if i not in idx:
882 idx.append(i)
--> 883 account_for(ipt)
884
885 # add all variables that are true ancestors of the cost

/Users/willem/dev/ml/keras/mlpy/lib/python2.7/site-packages/theano/gradient.pyc in account_for(var)
881 if i not in idx:
882 idx.append(i)
--> 883 account_for(ipt)
884
885 # add all variables that are true ancestors of the cost

/Users/willem/dev/ml/keras/mlpy/lib/python2.7/site-packages/theano/gradient.pyc in account_for(var)
881 if i not in idx:
882 idx.append(i)
--> 883 account_for(ipt)
884
885 # add all variables that are true ancestors of the cost

/Users/willem/dev/ml/keras/mlpy/lib/python2.7/site-packages/theano/gradient.pyc in account_for(var)
881 if i not in idx:
882 idx.append(i)
--> 883 account_for(ipt)
884
885 # add all variables that are true ancestors of the cost

/Users/willem/dev/ml/keras/mlpy/lib/python2.7/site-packages/theano/gradient.pyc in account_for(var)
881 if i not in idx:
882 idx.append(i)
--> 883 account_for(ipt)
884
885 # add all variables that are true ancestors of the cost

/Users/willem/dev/ml/keras/mlpy/lib/python2.7/site-packages/theano/gradient.pyc in account_for(var)
881 if i not in idx:
882 idx.append(i)
--> 883 account_for(ipt)
884
885 # add all variables that are true ancestors of the cost

/Users/willem/dev/ml/keras/mlpy/lib/python2.7/site-packages/theano/gradient.pyc in account_for(var)
858 connection_pattern = _node_to_pattern(app)
859
--> 860 var_idx = app.outputs.index(var)
861
862 for i, ipt in enumerate(app.inputs):

ValueError: sigmoid.0 is not in list

[codekansas]

This seems like a Keras issue. After the new updates Gandlf is totally broken, though... It's disheartening

[smartsystems4u]

Reading The Keras blog the 2.x API change is for the ages :)