- A simple note for how to start multi-node-training on slurm scheduler with PyTorch.
- Useful especially when scheduler is too busy that you cannot get multiple GPUs allocated, or you need more than 4 GPUs for a single job.
- Requirement: Have to use PyTorch DistributedDataParallel(DDP) for this purpose.
- Warning: might need to re-factor your own code.
- Warning: might be secretly condemned by your colleagues because using too many GPUs.
Anirudh Thatipelli Anirudh257
Geoyi
/ install virtualenv ubuntu 16.04.md
Created
September 16, 2017 12:19
— forked from frfahim/install virtualenv ubuntu 16.04.md
How to install virtual environment on ubuntu 16.04
zhanwenchen
/ Install NVIDIA Driver and CUDA.md
Last active
March 13, 2024 23:42
— forked from wangruohui/Install NVIDIA Driver and CUDA.md
Install NVIDIA CUDA 9.0 on Ubuntu 16.04.4 LTS
Updated 4/11/2018
Here's my experience of installing the NVIDIA CUDA kit 9.0 on a fresh install of Ubuntu Desktop 16.04.4 LTS.
thanasi
/ jupyter_local_video.py
Last active
February 15, 2022 08:48
Embed a local video file in a Jupyter Notebook
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| ######################################### | |
| # using cell magic | |
| ######################################### | |
| %%HTML | |
| <div align="middle"> | |
| <video width="80%" controls> | |
| <source src="path/to/my.mp4" type="video/mp4"> | |
| </video></div> | |
| ######################################### |
frfahim
/ install virtualenv ubuntu 16.04.md
Last active
November 19, 2024 06:11
How to install virtual environment on ubuntu 16.04
akiross
/ Convolutional Arithmetic.ipynb
Last active
October 24, 2024 07:04
Few experiments on how convolution and transposed convolution (deconvolution) should work in tensorflow.
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mstankie
/ import-plt.py
Created
June 15, 2016 19:33
Two images side-by-side using matplotlib (pylab)
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| import matplotlib.pyplot as plt |
bikz05
/ important-robotics-links.md
Last active
January 15, 2025 07:10
Robotics, Computer Vision and Machine Learning stuff -- Compiled by @bikz05 -- www.andrew.cmu.edu/user/bhanzra
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| ./cache/flic_win/LMDB/LMDB_val_patches/casino-royale-00039871_00000001_000001.jpg 1 | |
| ./cache/flic_win/LMDB/LMDB_val_patches/casino-royale-00039871_00000001_000002.jpg 1823 | |
| ./cache/flic_win/LMDB/LMDB_val_patches/casino-royale-00039871_00000001_000003.jpg 2903 | |
| ./cache/flic_win/LMDB/LMDB_val_patches/casino-royale-00039871_00000001_000004.jpg 4470 | |
| ./cache/flic_win/LMDB/LMDB_val_patches/casino-royale-00039871_00000001_000005.jpg 4698 | |
| ./cache/flic_win/LMDB/LMDB_val_patches/casino-royale-00039871_00000001_000006.jpg 4797 | |
| ./cache/flic_win/LMDB/LMDB_val_patches/casino-royale-00039871_00000001_000007.jpg 4917 | |
| ./cache/flic_win/LMDB/LMDB_val_patches/casino-royale-00039871_00000001_000008.jpg 5072 | |
| ./cache/flic_win/LMDB/LMDB_val_patches/casino-royale-00039871_00000001_000009.jpg 5177 | |
| ./cache/flic_win/LMDB/LMDB_val_patches/casino-royale-00039871_00000001_000010.jpg 5271 |
nhmc
/ calc_bg.py
Created
November 16, 2012 10:43
Calculate the background and RMS of an astronomical image
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| import numpy as np | |
| def calc_bg(a): | |
| """ Estimate the background level and rms. """ | |
| good = ~np.isnan(a) | |
| assert good.sum(), 'no good pixels!' | |
| # poor man's source detection... | |
| vmax = np.percentile(a[good], 80) | |
| c0 = a[good] < vmax | |
| temp = a[good][c0] |
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