R Language - How to Use Torch Package

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In this post, we look at How to Use Torch Package in Machine Learning Framework. This package is based on the Pytorch which is being used for the machine learning and deep learning.

Previously I have covered one more package named Iris. This is a dataset and it is often used for the stats and other similar exercises. So if you have not read about it yet. I'd recommend checking out the post- Iris Dataset in R.

If you want to read about the official site of the torch package. You can take a look at the page here. And also you would be reading about other support packages from the same makers where you can read about how they can be useful for your project.

I also covered the RStudio IDE for those who are not yet used it or wish to learn about it. I covered it in the video. Something you may want to keep tab on. It's a good IDE for the R language learning. You can read my post on the RStudio IDE for R Language.

I have created a video to give you an overview on how to use the Torch Package for the data science work. You should give this one a try.



Torch package can teach you a lot of interesting things. If you are not following along the video then below text based short tutorial can point you to installation and few pointers. Once you get those done you are good to proceed on your own.

So let's first get started with how to install this package.

If you are using the RStudio and you know how to use console, check the following command.

install.packages("torch")

This command should install the torch package. And now we are reading to create the code that would help us create tensors and also the arrays to use in the programs.

You can call for this package using the below code.

library(torch)

torch.png

How do you create tensors here?


You can create tensors now that you have started using this library. So we start with one example where we can add the content.

x <- torch_tensor(c(1,2,3))
x

We can also access various attributes of the tensors. Like say shape, size, type etc. In order to find the type you can check the below code.

x <- torch_randn(2,2)
x$dtype

Let's take a look at how to find the shape of the tensor and for that you can take a look at the below code.

x$shape

You can read the rest of the official document tour here.

As this torch package is based on the pytorch, it'd do all those things that are being designed for pytorch. And it's open source and free. So you are in safe hands when it comes to new updates, bugs fixing and also getting the proper output as per the industry standard.

It also makes sure to run your code lot faster as it uses the GPU acceleration. So you write the code that would analyses and manipulate it and torch package does the faster processing. This package is being used by many companies and also a lot of labs are using it for their daily work. So it's kind of a proven package for you to use.

I hope that you are enjoying some of my R language and data science tutorials. I hope that some of my coverage on this topic would be helpful to you.

If you happen to like this content, do give me feedback over there and that would help me improve my efforts in near future.



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