Debug Pytorch GAN Code and add block of inception and residual network
Budget: £20 – £250 GBP
I am in need of a savvy individual who can resolve a pesky architecture issue with my Pytorch code. My code handles a generative adversarial network but it is returning a runtime error that seems to be related to the model architecture.
Ideally, you should possess:
- Profound experience in Pytorch.
- Specialized knowledge in Generative Adversarial Networks (GANs).
- Ability to identify and rectify code errors, without the use of pre-trained models.
Your task will be:
- Diagnose and fix the RuntimeError: Given transposed=1, weight of size [192, 64, 4, 4], expected input [8, 252, 258, 258] to have 192 channels, but got 252 channels instead.
- Finalize the three remaining components of the code adding inception blocks and residual block + transpose convolution.
The right candidate will be rewarded with the opportunity for further related tasks. Get in touch and let's get this project rolling.
Ideally, you should possess:
- Profound experience in Pytorch.
- Specialized knowledge in Generative Adversarial Networks (GANs).
- Ability to identify and rectify code errors, without the use of pre-trained models.
Your task will be:
- Diagnose and fix the RuntimeError: Given transposed=1, weight of size [192, 64, 4, 4], expected input [8, 252, 258, 258] to have 192 channels, but got 252 channels instead.
- Finalize the three remaining components of the code adding inception blocks and residual block + transpose convolution.
The right candidate will be rewarded with the opportunity for further related tasks. Get in touch and let's get this project rolling.
Related categories:
Machine Learning (ML)
Pytorch
Generative AI
Generative Model
Generative Adversarial Network