Hi,
is there a way to visualize the activation grid for a custom model with nested modules, which are not explicitely named as a model's attribute?
E.g. when I call get_model_layers(), you can see the following output for this custom model:
I followed your notebook on the activation grid (https://colab.research.google.com/github/greentfrapp/lucent-notebooks/blob/master/notebooks/activation_grids.ipynb#scrollTo=BDH9cXnSuu5Q).
For example, I choose layer = "net_down1_maxpool_conv" (is there some kind of syntax for specifying the layers?)
I also rewrote the get_layer() helper function to parse the networks layer from the string, because that layer is not a direct attribute of the network class. But when I then try to use the rendering function, there is an error in the first line of the objective function: In lines 203-206 of render.py either one of the assertions is thrown, depending on how I choose the layer string.
Can you help me with this problem?
Many thanks!
Hi,
is there a way to visualize the activation grid for a custom model with nested modules, which are not explicitely named as a model's attribute?
E.g. when I call get_model_layers(), you can see the following output for this custom model:
I followed your notebook on the activation grid (https://colab.research.google.com/github/greentfrapp/lucent-notebooks/blob/master/notebooks/activation_grids.ipynb#scrollTo=BDH9cXnSuu5Q).
For example, I choose
layer = "net_down1_maxpool_conv"(is there some kind of syntax for specifying the layers?)I also rewrote the get_layer() helper function to parse the networks layer from the string, because that layer is not a direct attribute of the network class. But when I then try to use the rendering function, there is an error in the first line of the objective function: In lines 203-206 of render.py either one of the assertions is thrown, depending on how I choose the layer string.
Can you help me with this problem?
Many thanks!