Deepnet | Python实现的一些基本算法

I want to use some of the parameters of the original deepnet package, so I set up a custom model. I read Caret's documentation (Custom Model), but it doesn't work.

Here is my code for setting up the customized model:

I tried to train my neural network, and then evaluate it's testing accuracy. I am using the code at the bottom of this post to train. The fact is that for other neural networks, I can evaluate the testing accuracy with my code without issue. However, for this neural network (which I constructed correctly according to the description of the neural network paper), I can't evaluate the testing accuracy properly and its giving me the traceback below. So maybe something's wrong in my forward pass?

Here is the training and testing code:

I am trying to train my neural network, which is written in PyTorch, but I got the following traceback because of incorrect dimensions. Got the following traceback

This is a model based on the description on page 12, section B.3 of the paper https://arxiv.org/pdf/1609.04836.pdf

I have Upgraded the Android application from 26 to 28 SDK.

It works well in 23 - 27 version.

But the new version will crash in SDK 28.

this is the exception stack:

I'm trying to translate code from deepnet to mxnet, but I'm not sure what am I doing wrong. I'm getting an error message that says:

I am testing most of the models caret supports on a bunch of PCs. Unfortunately caret "suggested" packages do not include most of the model packages available to caret. Every time a new version of R comes out I have to sit in front of each PC and wait for each prompt to press the 1 button and Enter. Is there an option I could set to tell R or Rstudio to just install anything asked for? A for every a/s/n prompt too.

I'm surprised at the number of R neural network packages that don't appear to have a parameter for regularization/lambda/weight decay. I'm assuming I'm missing something obvious. When I use a package like MLR and look at the integrated learners, I don't see parameters for regularization.

For example: nnTrain from the deepnet package:
list of params

I see parameters for just about everything - even drop out - but not lambda or anything else that looks like regularization.

My understanding of both caret and mlr is that they basically organize other ML packages and try to provide a consistent way to interact with them. I'm not finding L1/L2 regularization in any of them.

I've also done 20 google searches looking for R packages with regularization but found nothing. What am I missing? Thanks!