pytorch-tutorial
a-PyTorch-Tutorial-to-Image-Captioning
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| pytorch-tutorial | a-PyTorch-Tutorial-to-Image-Captioning | |
|---|---|---|
| 3 | 1 | |
| 29,128 | 2,657 | |
| - | - | |
| 0.0 | 0.0 | |
| 9 months ago | almost 2 years ago | |
| Python | Python | |
| MIT License | 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
a-PyTorch-Tutorial-to-Image-Captioning
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[R] end-to-end image captioning
I have found this repository: https://github.com/sgrvinod/a-PyTorch-Tutorial-to-Image-Captioning that, seemingly, requires only images and captions, but this is quite old (3 years ago), and is based on LSTMs. I was hoping there are transformers-based implementations that I could use.
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
meshed-memory-transformer - Meshed-Memory Transformer for Image Captioning. CVPR 2020
InceptionTime - InceptionTime: Finding AlexNet for Time Series Classification
BLIP - PyTorch code for BLIP: Bootstrapping Language-Image Pre-training for Unified Vision-Language Understanding and Generation
Conv-TasNet - A PyTorch implementation of Conv-TasNet described in "TasNet: Surpassing Ideal Time-Frequency Masking for Speech Separation" with Permutation Invariant Training (PIT).
image-to-latex - Convert images of LaTex math equations into LaTex code.
pytorch-grad-cam - Advanced AI Explainability for computer vision. Support for CNNs, Vision Transformers, Classification, Object detection, Segmentation, Image similarity and more.
catr - Image Captioning Using Transformer
BigGAN-PyTorch - The author's officially unofficial PyTorch BigGAN implementation.
clip-glass - Repository for "Generating images from caption and vice versa via CLIP-Guided Generative Latent Space Search"
bonito - A PyTorch Basecaller for Oxford Nanopore Reads
blip - A tool for seeing your Internet latency. Try it at http://gfblip.appspot.com/