Pytorch Conditional GAN Tutorial

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In this video we take a look at a way of also deciding what the output from the GAN should be. Specifically the output is conditioned on the labels that we send in and as an example we take a look at training on MNIST (of course) ;) But these ideas extend to any dataset you're working with really!

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OUTLINE:
0:00 - Introduction
0:56 - Modifying Generator and Discriminator
6:58 - Modifying Gradient Penalty
7:35 - Modifying Training
10:43 - Evaluation & Ending

Aladdin Persson

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When re-watching this video I realize there are some (short) parts where the audio was damaged and when figuring it out I realize it was because my phone was close to the microphone, sorry about that. I also haven't done many videos where I modify previous written code and I think making a bullet list explaining what we wanted to change could have made things clearer! Hopefully you can ignore the mistakes of this video and I'll learn and promise to improve moving forward :) Also if you have recommendations on GANs you think would make this into an even better resource for people wanting to learn about GANs let me know in the comments below and I'll try to do it!

I learned a lot and was inspired to make these GAN videos by the GAN specialization on coursera which I recommend. Below you'll find both affiliate and non-affiliate links, the pricing for you is the same but a small commission goes back to the channel if you buy it through the affiliate link.

Here's the outline for the video:
0:00 - Introduction
0:56 - Modifying Generator and Discriminator
6:58 - Modifying Gradient Penalty
7:35 - Modifying Training
10:43 - Evaluation & Ending

AladdinPersson

Thanks! I played GAN in tensorflow before. Now I'm study GAN in pytorch. This really helps me a lot.

何品潔-yr

Cannot find this code snippet on the code repo mentioned

nikhilmugganawar

i found your channel today and the content is awesome

lifeafteraleekx

Very nice videos, really helpfull especially for people like me who havent studied Computer Science previously. You could maybe make a video where you use a Variational Autoencoder to get the latent space representation of a dataset and then use this representation for clustering. Thanks again for the videos, really helpfull.

aggelostamvakis

Best wishes for you and thanks for you giving so amazing tutorial for us. Learning a lot with your video!

andyjames

Dunno what I'm watching, but It’s good. I'm gonna hop into it

bugRanger

That's a very good and helpful video! Thanks!

Barandur

Hey sir please make some tutorials on reinforcement learning

arnabsarkar

Nice video as usual! Just a question, how would one go about building a conditional regression GANs?

For example, instead of having a class label, have a float label age and generate faces with that corresponding age.

wilsonthurmanteng

Nice video! Will there be a video about ACGAN??

ShihyuanLin

Hi I need to know whether we can make any kind of GAN conditional. I'm doing a project using a modified cyclegan(cyclegan vc) currently it's made for 1 to 1 conversions, will it be possible to make this model conditional?

kay

Thanks for a great tutorial! Can you please upload the tutorial file on your page too?

ulugbekdjuraev

awesome ! can you please make a video in text to images using GANs please

deepudeepak

can you do text to image GAN or say how we can do it

donfeto

Please add this to your GITHUB, Thanks

respair

can u tell me please, how to handle large data with limiting amount of ram

Rohankumar-ddss

I tried replicationg this exact code but I'm getting the following error: "return torch.embedding(weight, input, padding_idx, scale_grad_by_freq, sparse)
IndexError: index out of range in self"

avirupdey

Sir how does nn.Embedding work for this

hackercop

Can someone explain to me why are we passing label to Discriminator too, instead of just passing it to generator? What about using softmax as an activation function for discriminator?

criccode

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