BigGAN-PyTorch
pytorch-tutorial
BigGAN-PyTorch | pytorch-tutorial | |
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4 | 3 | |
2,802 | 29,160 | |
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0.0 | 0.0 | |
10 months ago | 9 months ago | |
Python | Python | |
MIT License | MIT License |
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BigGAN-PyTorch
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[D] Pre-trained weights for GANs online?
The second link gives you the entire source code for training the model https://github.com/ajbrock/BigGAN-PyTorch/tree/master . Looks like BigGAN.py and BigGANdeep.py are the two files that define the architecture. Can you work with that?
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I'm looking for an AI Art generator from images
BigGAN (https://github.com/ajbrock/BigGAN-PyTorch) - This is a PyTorch implementation of the BigGAN model for generating high-resolution images. It is trained on a large dataset and can generate a wide range of images, including photographs of animals, objects, and landscapes.
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[D] Using activity regularization instead of batch norm.
Tangentially, theoretically you can't use BN in the discriminator for WGAN-GP anyway (assuming that you're using the Gulrajani work) because it breaks the sample independence assumptions of the GP. If you have a relatively structured dataset (eg all faces, all cars, all giraffes, etc.) and no class conditioning, look into StyleGAN2-ADA for the best results. If you have a dataset with a lot of variation and a lot of classes try using the BigGAN repo.
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Έφτιαξα ένα AI που παράγει εικόνες από μερικές λέξεις. Να τι έφτιαξε όταν του είπα να σκεφτεί ένα "Αφηρημένο Πορτρέτο"
BigGan και Deep Dream https://github.com/ajbrock/BigGAN-PyTorch https://github.com/google/deepdream
pytorch-tutorial
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PyTorch - What does contiguous() do?
I was going through this example of a LSTM language model on github (link).What it does in general is pretty clear to me. But I'm still struggling to understand what calling contiguous() does, which occurs several times in the code.
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How to 'practice' pytorch after finishing its basic tutorial?
I tried to move straight to practicing implementing papers and trying to understand other people's codes but failed miserably. I feel like there was too much of a gap between the basic tutorial and being able to implement ideas into code....hence the question: Is there any resource/way to practice pytorch in general? I did find this and this, but I just wanted to hear what others have gone through to become better at PyTorch up to the point they can build stuff from their own ideas
- [P] Probabilistic Machine Learning: An Introduction, Kevin Murphy's 2021 e-textbook is out
What are some alternatives?
stylegan2-ada-pytorch - StyleGAN2-ADA - Official PyTorch implementation
mixture-of-experts - PyTorch Re-Implementation of "The Sparsely-Gated Mixture-of-Experts Layer" by Noam Shazeer et al. https://arxiv.org/abs/1701.06538
PyTorch-StudioGAN - StudioGAN is a Pytorch library providing implementations of representative Generative Adversarial Networks (GANs) for conditional/unconditional image generation.
InceptionTime - InceptionTime: Finding AlexNet for Time Series Classification
transfer-learning-conv-ai - 🦄 State-of-the-Art Conversational AI with Transfer Learning
Conv-TasNet - A PyTorch implementation of Conv-TasNet described in "TasNet: Surpassing Ideal Time-Frequency Masking for Speech Separation" with Permutation Invariant Training (PIT).
pytorch-forecasting - Time series forecasting with PyTorch
pytorch-grad-cam - Advanced AI Explainability for computer vision. Support for CNNs, Vision Transformers, Classification, Object detection, Segmentation, Image similarity and more.
code-generator - Web Application to generate your training scripts with PyTorch Ignite
bonito - A PyTorch Basecaller for Oxford Nanopore Reads
pytorch-CycleGAN-and-pix2pix - Image-to-Image Translation in PyTorch
OpenNMT-py - Open Source Neural Machine Translation and (Large) Language Models in PyTorch