Keras Reshape Error in Flatten Operation at Runtime - python-2.7

Question

I have a problem using keras with either backend (tf or theano).
When I execute my model which is defined like this:
model = Sequential()
model.add(Conv1D(filters=2, kernel_size=15, padding="valid", input_shape=(training_feature_maps.shape[1], training_feature_maps.shape[2]), kernel_constraint=maxnorm(3)))
model.add(Activation('relu'))
model.add(Dropout(rate=0.5))
model.add(MaxPooling1D(pool_size=2))
model.add(Flatten())
model.add(Dense(128, kernel_constraint=maxnorm(3)))
model.add(Activation('relu'))
model.add(Dense(2))
model.add(Activation('softmax'))
print model.summary()
model.compile(loss='categorical_crossentropy', optimizer='adam', metrics=['accuracy'])
model.fit(training_feature_maps, y_train, batch_size=100, epochs=50, validation_data=(testing_feature_maps, y_test), shuffle=True)
The input feature maps have shapes (~26000, 1050, 4) and (~8000, 1050, 4).
The summary is printed and looks good:
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
dropout_1 (Dropout) (None, 1050, 4) 0
_________________________________________________________________
conv1d_1 (Conv1D) (None, 1036, 2) 122
_________________________________________________________________
activation_1 (Activation) (None, 1036, 2) 0
_________________________________________________________________
dropout_2 (Dropout) (None, 1036, 2) 0
_________________________________________________________________
max_pooling1d_1 (MaxPooling1 (None, 518, 2) 0
_________________________________________________________________
flatten_1 (Flatten) (None, 1036) 0
_________________________________________________________________
dense_1 (Dense) (None, 128) 132736
_________________________________________________________________
activation_2 (Activation) (None, 128) 0
_________________________________________________________________
dense_2 (Dense) (None, 2) 258
_________________________________________________________________
activation_3 (Activation) (None, 2) 0
=================================================================
Total params: 133,116.0
Trainable params: 133,116.0
Non-trainable params: 0.0
_________________________________________________________________
But during run-time, I get the following error using Tensorflow as backend:
Caused by op u'flatten_1/Reshape', defined at:
File "load_data.py", line 598, in <module>
model.add(Flatten())
File "/home/sasse/.local/lib/python2.7/site-packages/keras/models.py", line 455, in add
output_tensor = layer(self.outputs[0])
File "/home/sasse/.local/lib/python2.7/site-packages/keras/engine/topology.py", line 554, in __call__
output = self.call(inputs, **kwargs)
File "/home/sasse/.local/lib/python2.7/site-packages/keras/layers/core.py", line 495, in call
return K.batch_flatten(inputs)
File "/home/sasse/.local/lib/python2.7/site-packages/keras/backend/tensorflow_backend.py", line 1744, in batch_flatten
x = tf.reshape(x, tf.stack([-1, prod(shape(x)[1:])]))
File "/home/sasse/.local/lib/python2.7/site-packages/tensorflow/python/ops/gen_array_ops.py", line 2630, in reshape
name=name)
File "/home/sasse/.local/lib/python2.7/site-packages/tensorflow/python/framework/op_def_library.py", line 763, in apply_op
op_def=op_def)
File "/home/sasse/.local/lib/python2.7/site-packages/tensorflow/python/framework/ops.py", line 2327, in create_op
original_op=self._default_original_op, op_def=op_def)
File "/home/sasse/.local/lib/python2.7/site-packages/tensorflow/python/framework/ops.py", line 1226, in __init__
self._traceback = _extract_stack()
InvalidArgumentError (see above for traceback): size 1 must be non-negative, not -31193103
[[Node: flatten_1/Reshape = Reshape[T=DT_FLOAT, Tshape=DT_INT32, _device="/job:localhost/replica:0/task:0/gpu:0"](max_pooling1d_1/Squeeze, flatten_1/stack)]]
[[Node: mul_2/_45 = _Recv[client_terminated=false, recv_device="/job:localhost/replica:0/task:0/cpu:0", send_device="/job:localhost/replica:0/task:0/gpu:0", send_device_incarnation=1, tensor_name="edge_870_mul_2", tensor_type=DT_FLOAT, _device="/job:localhost/replica:0/task:0/cpu:0"]()]]
When using theano instead, I get the following error:
RuntimeError: c_extract: Some CudaNdarray has dim 2 on broadcastable dimension 2
Apply node that caused the error: GPU_mrg_uniform{CudaNdarrayType(float32, 3D),inplace}(<CudaNdarrayType(float32, vector)>, MakeVector{dtype='int64'}.0)
Toposort index: 52
Inputs types: [CudaNdarrayType(float32, vector), TensorType(int64, vector)]
Inputs shapes: [(92160,), (3,)]
Inputs strides: [(1,), (8,)]
Inputs values: ['not shown', array([ 100, 1036, 2])]
Outputs clients: [['output'], [GpuElemwise{Composite{Cast{float32}(LT(i0, i1))}}[(0, 0)](GPU_mrg_uniform{CudaNdarrayType(float32, 3D),inplace}.1, CudaNdarrayConstant{[[[ 0.5]]]})]
I'm running on a Titan X GPU with CUDA 8.0.44 and CuDNN 5105.
Strangely enough, all works fine when I use only one filter in the convolution.
Do you have any idea, why this is happening?
Best regards,
Roman