I'm currently using Keras to solve a regression problem.
And I want the weights of my layers (embedding layers).
I'm using layer.get_weights() from keras, but it doesn't show me the full output.
Already tried to save_weights() but when I try to convert the hdf5 file it says that is empty.
Any solution?
Related
I'm trying to translate a neural network that I wrote in Keras Python, but Matlab says that I can't use the Flatten layer together with the Image Input Layer. How can I solve this problem
?
Unfortunately, I could not find an answer to my question on the Internet.
How to reverse an output tensor in a layer to an input image? I can imagine the reversed input image will be different than the original one because of the dropout, etc. However, I want to do an experiment so I appreciate a possible method in PyTorch. I am currently using the pre-trained ResNet. If the answer involves some knowledge in a paper, kindly provide a citation or link.
I have a .h5 file I want to upload to Matlab using the import tool for TensorFlow in matlab, like this:
layers = importKerasLayers('myModel.h5');
But I get the following error:
Option to import Keras networks containing LSTM layers is not yet
supported.
layers =importKerasLayers('myModel.h5');
I've tried this in 2018a, and apperantly all layers related to LSTM are available in this version after the toolbox is downloaded, but I keep getting the error. In this link, you can see the toolbox has support for LSTM layers, but not sure what's causing the error then.
Is there any workaround to solve this? What could be causing the error?
Your link is for R2018b documentation. This is the R2018a documentation and it shows no support for LSTM! So probably switch versions and try!
I couldn't find any full example of an autoencoder in DL4J documentation. I see a good general description of Autoencoders here with a small piece of code for just the MultiLayerConfiguration, but the code is not full. Is there any full example where a dataset is loaded, pre-processed and then inserted into the network and a prediction is generated? For example, an example working with the Movielens dataset, or any other. Thank you.
You have an example of a deep auto encoder using the mnist dataset here:
https://deeplearning4j.konduit.ai/deeplearning4j/reference/auto-encoders
With code here:
https://github.com/eclipse/deeplearning4j-examples/blob/master/dl4j-examples/src/main/java/org/deeplearning4j/examples/quickstart/modeling/feedforward/unsupervised/MNISTAutoencoder.java
I want to use NN toolbox in matlab
my input is a 42*3 and my target is 42*1
i Have 42 samples with 3 features
but I cant load the target and it hasn't any error but it doesn't load
can anyone help me
Try to load an example dataset first. Matlab provides six example data sets, you can choose in the GUI. If you have no problems with those, the problem is with your data.