pykale
pytorch-lightning
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pykale | pytorch-lightning | |
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2 | 19 | |
427 | 19,188 | |
1.6% | - | |
9.1 | 9.9 | |
about 1 month ago | almost 2 years ago | |
Python | Python | |
MIT License | Apache License 2.0 |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
pykale
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PyKale Preprint: Knowledge-Aware Machine Learning from Multiple Sources in Python [P][R]
A 10-page preprint is on arXiv to describe the green machine learning design principles behind our pipeline-based API below as well as features and examples in our PyKale library for multimodal learning and transfer learning with deep learning and dimensionality reduction on graphs, images, texts, and videos to enable and accelerate interdisciplinary research: [2106.09756] PyKale: Knowledge-Aware Machine Learning from Multiple Sources in Python (arxiv.org)
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[P] An introduction to PyKale https://github.com/pykale/pykale, a PyTorch library that provides a unified pipeline-based API for knowledge-aware multimodal learning and transfer learning on graphs, images, texts, and videos to accelerate interdisciplinary research. Welcome feedback/contribution!
Thank you LargeYellowBus for your valuable feedback! That's really helpful. It is weird to hear that the GitHub link was broken when you tried. It is here https://github.com/pykale/pykale and there have been 100+ unique visitors today. So it might be temporary on your side and you may try again.
pytorch-lightning
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Problem with pytorch lightning and optuna with multiple callbacks
def on_validation_end(self, trainer: Trainer, pl_module: LightningModule) -> None: # Trainer calls `on_validation_end` for sanity check. Therefore, it is necessary to avoid # calling `trial.report` multiple times at epoch 0. For more details, see # https://github.com/PyTorchLightning/pytorch-lightning/issues/1391. if trainer.sanity_checking: return
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Please comment on my planned research project structure
Under the hood, the ModelWrapper object will create a ML model based on the config (so far, an XGBoost model and a PyTorch Lightning model). Each of those will have a wrapper that conducts training and evaluation (since from my understanding of Lightning, Trainers are required to be outside of the class). In lack of a better name, I call these wrappers Fitters. For uniformity, I thought about adding a common interface IFitter, which is inherited by all model wrappers as outlined below.
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Watch out for the (PyTorch) Lightning
Join their Slack to ask the community questions and check out the GitHub here.
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[P] Composer: a new PyTorch library to train models ~2-4x faster with better algorithms
Pytorch lightning benchmarks against pytorch on every PR (benchmarks to make sure that it is mot slower.
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[D] What Repetitive Tasks Related to Machine Learning do You Hate Doing?
There is already a ton of momentum around automating ML workflows. I would suggest you contribute to a preexisting project like, for instance, PyTorch Lightning or fast.ai.
- PyTorch Lightening
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[D] Are you using PyTorch or TensorFlow going into 2022?
Is the problem the sheer number of options, or the fact that they are all together in one place? Would it be better if they were organized into the different trainer entrypoints (fit, validate, ...)? If that is the case, there was an RFC proposing this which you might find interesting, feel free to drop by and comment on the issue: https://github.com/PyTorchLightning/pytorch-lightning/issues/10444
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[D] Colab TPU low performance
I wanted to make a quick performance comparison between the GPU (Tesla K80) and TPU (v2-8) available in Google Colab with PyTorch. To do so quickly, I used an MNIST example from pytorch-lightning that trains a simple CNN.
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[D] How to avoid CPU bottlenecking in PyTorch - training slowed by augmentations and data loading?
We've noticed GPU 0 on our 3 GPU system is sometimes idle (which would explain performance differences). However its unclear to us why that may be. Similar to this issue
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[P] An introduction to PyKale https://github.com/pykale/pykale, a PyTorch library that provides a unified pipeline-based API for knowledge-aware multimodal learning and transfer learning on graphs, images, texts, and videos to accelerate interdisciplinary research. Welcome feedback/contribution!
If you want a good example for reference, take a look at Pytorch Lightning's readme (https://github.com/PyTorchLightning/pytorch-lightning) It answers the 3 questions of "what is this", "why should I care", and "how do i use it" almost instantly
What are some alternatives?
EasyOCR - Ready-to-use OCR with 80+ supported languages and all popular writing scripts including Latin, Chinese, Arabic, Devanagari, Cyrillic and etc.
mmdetection - OpenMMLab Detection Toolbox and Benchmark
AdaTime - [TKDD 2023] AdaTime: A Benchmarking Suite for Domain Adaptation on Time Series Data
pytorch-grad-cam - Advanced AI Explainability for computer vision. Support for CNNs, Vision Transformers, Classification, Object detection, Segmentation, Image similarity and more.
Multimodal-Toolkit - Multimodal model for text and tabular data with HuggingFace transformers as building block for text data
detectron2 - Detectron2 is a platform for object detection, segmentation and other visual recognition tasks.
Meta-SelfLearning - Meta Self-learning for Multi-Source Domain Adaptation: A Benchmark
fastai - The fastai deep learning library
social-balance - A library-agnostic project for calculating exactly and efficiently social balance, based on the Aref, Mason and Wilson paper (https://arxiv.org/abs/1611.09030)
composer - Supercharge Your Model Training
open_flamingo - An open-source framework for training large multimodal models.
sparktorch - Train and run Pytorch models on Apache Spark.