pytorch-tutorial
pytorch-exercise
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| pytorch-tutorial | pytorch-exercise | |
|---|---|---|
| 3 | 1 | |
| 29,128 | 271 | |
| - | - | |
| 0.0 | 0.0 | |
| 9 months ago | almost 6 years ago | |
| Python | Jupyter Notebook | |
| MIT License | - |
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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
pytorch-exercise
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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
What are some alternatives?
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
InceptionTime - InceptionTime: Finding AlexNet for Time Series Classification
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-grad-cam - Advanced AI Explainability for computer vision. Support for CNNs, Vision Transformers, Classification, Object detection, Segmentation, Image similarity and more.
BigGAN-PyTorch - The author's officially unofficial PyTorch BigGAN implementation.
bonito - A PyTorch Basecaller for Oxford Nanopore Reads
OpenNMT-py - Open Source Neural Machine Translation and (Large) Language Models in PyTorch
pycox - Survival analysis with PyTorch
a-PyTorch-Tutorial-to-Image-Captioning - Show, Attend, and Tell | a PyTorch Tutorial to Image Captioning
composer - Supercharge Your Model Training
maxout - Maxout Networks