As the models are built using a wrapped layer, traditional method of getting intermediate layer features is not working. Can you propose an alternative?
Thank you for your interest in the competition. Would you mind clarifying what you mean by layer features ? A small example of what you want to accomplish and what would be the expected output would be very helpful.
Thanks!Posted by: pforet @ July 30, 2020, 4:23 p.m.
Thanks for your reply, by intermediate layer features, I mean the network output at a given layer.
how do we do: clipModel = tf.keras.Model(inputs = model.inputs, outputs = model.layers[-1].output) ?
in current setup: model.inputs =  and throws " AttributeError: Layer wrapped_layer has no inbound nodes."
Also, can you clarify how to scoring script locally? what should these paths **path/to/prediction** and **path/to/output**` point to?
Thank youPosted by: deepq-lab @ July 30, 2020, 4:29 p.m.
Thanks for the clarification.
You can access this using some_layer._last_seen_input (this is used in the jacobian norm baseline we provided, you can refer to it for a full working example). The reason we don't use some_layer.output as you suggest it that it doesn't play nicely with the autograd, so that computing gradients with respect to some_layer._last_seen_input would work but some_layer.output would not.
thanks! this worksPosted by: deepq-lab @ July 30, 2020, 4:58 p.m.
"path to prediction" refers to the where the output of your ingestion program lies and "path to output" is anywhere you want to final score to be.
thanks for clarifyingPosted by: deepq-lab @ July 31, 2020, 5:23 a.m.
Hi, ydjiang. May I know whether it is possible to get the output of GlobalPooling layer in network in network model? The method 'some_layer._last_seen_input' will only get the output of layers before the GlobalPooling layer in network in network model. Naturally, we could use method 'some_layer.output', but it seems it doesn't work in TensorFlow 2.2. It would be great if you could give me some advice.
Moreover, do you know where I could find any documents about method '_last_seen_input' and 'wrapped layer'? Thanks.Posted by: LinZhang @ Oct. 17, 2020, 3:29 p.m.
Re: Outoput of global average pooling in Nin
This is just the logit of the model. I am not sure why you would need a special method to access it.
Re: wrapped layer
This is not officially in Tensorflow. It's just a wrapper we made so people can get the input to each layer.
The code is only a couple lines. You can find it in "wrap_layer" in "model_utils.py" in ingestion program.
Thanks for the response. I realize that I could add a GlobalPooling operation myself. I read the "model_utils.py" and it is clear. Thanks.