I must be idiot but I can’t realise how to do very basic… no Convolution, RNN, gates,… just a basic plain feed-forward neural network design/testing/validation in Flux. Somethink like: l1 = FullyConnectedLayer(tanh,2,3,w=ones(3,2), wb=zeros(3)) l2 = FullyConnectedLayer(tanh,3,2, w=ones(2,3), wb=ze…

[image] sylvaticus: using Flux xtrain = [0.1 0.2; 0.3 0.5; 0.4 0.1; 0.5 0.4; 0.7 0.9; 0.2 0.1] ytrain = [0.3; 0.8; 0.5; 0.9; 1.6; 0.3] xtest = [0.5 0.6; 0.14 0.2; 0.3 0.7] ytest = [1.1; 0.36; 1.0] # Direct way. Error: “Output should be scalar”: model = Chain(Dense(2, 1)) loss(x, y) = Flux.mse,(m…

Did you check the Flux model_zoo for examples? I see they updated it quite recently. They also have the 60min blitz which could be useful.

Thank you, that’s the clearer example I could find. Still I can’t get it working with toy data: using Flux xtrain = [0.1 0.2; 0.3 0.5; 0.4 0.1; 0.5 0.4; 0.7 0.9; 0.2 0.1] ytrain = [0.3; 0.8; 0.5; 0.9; 1.6; 0.3] xtest = [0.5 0.6; 0.14 0.2; 0.3 0.7] ytest = [1.1; 0.36; 1.0] # Direct…

That is a great example and ran smoothly. I tried using DataLoader for batching but then I got errors about the dimensions. data_batch = Flux.Data.DataLoader((xtrain', ytrain'), batchsize=6) Flux.@epochs 100 Flux.train!(loss, ps, data_batch, opt) ┌ Info: Epoch 1 └ @ Main C:\Users\shawn\.julia\pac…

DataLoader was supposed to be the following I think: data_batch = Flux.Data.DataLoader((xtrain’, ytrain), batchsize=6)

How to train/predict a very simple feed-forward neural network in Flux?

Specific Domains Machine Learning

Albert_Zevelev May 16, 2020, 3:19am 3

@sylvaticus maybe my code will help:
Generic Function to train NN w/ Flux

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How to train/predict a very simple feed-forward neural network in Flux?

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