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[D] Are you using PyTorch or TensorFlow going into 2022?
6 projects | reddit.com/r/MachineLearning | 14 Dec 2021
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
[D] Colab TPU low performance
2 projects | reddit.com/r/MachineLearning | 18 Nov 2021
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.
[D] How to avoid CPU bottlenecking in PyTorch - training slowed by augmentations and data loading?
2 projects | reddit.com/r/MachineLearning | 10 Nov 2021
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
[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!
2 projects | reddit.com/r/MachineLearning | 25 Apr 2021
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
2 projects | reddit.com/r/pytorch | 24 Apr 2021
[D] Advanced Takeaways from fast.ai book
2 projects | reddit.com/r/MachineLearning | 23 Mar 2021
Lower precision training can help and on pytorch lightning is just a simple flag you can set
[D] How to be more productive while doing Deep Learning experiments?
10 projects | reddit.com/r/MachineLearning | 25 Feb 2021
First of all, use high-level ML frameworks (AllenNLP, PyTorch-Lightning). No need to write boilerplate code and implement standard ML approaches from scratch. Here are some suggestions (thought more NLP-focused) that I feel improved my research coding experience a lot.
DDP with model parallelism with multi host multi GPU system
1 project | reddit.com/r/pytorch | 7 Feb 2021
PyTorch Lightning Flash appears to be copying fastai (without any credit) [D]
2 projects | reddit.com/r/MachineLearning | 5 Feb 2021
According to the README it's patent pending, but I learned about that from this HN thread. Funny thing is I didn't even remember there was a snafu about patents, but looked it up because of some vague recollection of the PL founder getting into a tussle about some other trivial topic (apparently it was how well PyTorch works on TPUs).
[D] Training 10x Larger Models and Accelerating Training with ZeRO-Offloading
3 projects | reddit.com/r/MachineLearning | 25 Jan 2021
I also asked for the respective support in PytorchLightning in this issue: Add deepspeed support · Issue #817 · PyTorchLightning/pytorch-lightning (github.com)
When to go for an 'easy' time-series model vs. using a complex deep learning model (when having experience with the latter)
1 project | reddit.com/r/datascience | 29 Nov 2021
I'm a data trainee at this organisation. I wrote my master thesis about using an event clustering mechanism to enrich an existing dataset to improve short-term demand predictions, using Pytorch Forecasting using the temporal fusion transformer component, and LightGBM (and compare the models with and w/o the event feature, so 4 runs in total).
A python library for easy manipulation and forecasting of time series.
3 projects | reddit.com/r/algotrading | 12 Aug 2021
Darts is a pretty nice one. I've recently been using pytorch-forecasting for larger models like the Temporal Fusion Transformer. https://github.com/jdb78/pytorch-forecasting
What are some alternatives?
detectron2 - Detectron2 is a platform for object detection, segmentation and other visual recognition tasks.
mmdetection - OpenMMLab Detection Toolbox and Benchmark
darts - A python library for easy manipulation and forecasting of time series.
pytorch-grad-cam - Many Class Activation Map methods implemented in Pytorch for CNNs and Vision Transformers. Including Grad-CAM, Grad-CAM++, Score-CAM, Ablation-CAM and XGrad-CAM
Prophet - Tool for producing high quality forecasts for time series data that has multiple seasonality with linear or non-linear growth.
Sacred - Sacred is a tool to help you configure, organize, log and reproduce experiments developed at IDSIA.
metaflow - :rocket: Build and manage real-life data science projects with ease!
Keras - Deep Learning for humans
DeepSpeed - DeepSpeed is a deep learning optimization library that makes distributed training easy, efficient, and effective.
guildai - Experiment tracking, ML developer tools
tmux - tmux source code
omegaconf - Flexible Python configuration system. The last one you will ever need.