[x] Check that you are up-to-date with the master branch of keras-vis. You can update with:
pip install git+git://github.com/raghakot/keras-vis.git --upgrade --no-deps
[x] If running on TensorFlow, check that you are up-to-date with the latest version. The installation instructions can be found here.
[x] If running on Theano, check that you are up-to-date with the master branch of Theano. You can update with:
pip install git+git://github.com/Theano/Theano.git --upgrade --no-deps
[ ] Provide a link to a GitHub Gist of a Python script that can reproduce your issue (or just copy the script here if it is short).
I am trying to do activation maximization in my Keras neural network.
My network is very simple.
input layer (240-long vector)
dense layer (1740 units, Relu)
dense layer (3240 units, Linear, name='output')
I would like to do activation-maximization to visualize what inputs activate a particular neuron in the output layer. With layer_idx=-1 and filter_indices=neuron_index :
[x] Check that you are up-to-date with the master branch of keras-vis. You can update with: pip install git+git://github.com/raghakot/keras-vis.git --upgrade --no-deps
[x] If running on TensorFlow, check that you are up-to-date with the latest version. The installation instructions can be found here.
[x] If running on Theano, check that you are up-to-date with the master branch of Theano. You can update with: pip install git+git://github.com/Theano/Theano.git --upgrade --no-deps
[ ] Provide a link to a GitHub Gist of a Python script that can reproduce your issue (or just copy the script here if it is short).
I am trying to do activation maximization in my Keras neural network.
My network is very simple.
I would like to do activation-maximization to visualize what inputs activate a particular neuron in the output layer. With layer_idx=-1 and filter_indices=neuron_index :
max_input = visualize_activation(model, layer_idx, filter_indices,input_range = (0., 1.))
returns me
AttributeError: Layer output has multiple inbound nodes, hence the notion of "layer output" is ill-defined. Use `get_output_at(node_index)` instead.
Thank you.