HudsonHuang

1. Using CUDA in correct way：

• 确定性卷积：（把所有操作的seed=0，以便重现，会变慢） torch.backends.cudnn.deterministic https://oldpan.me/archives/pytorch-conmon-problem-in-training

  添加torch.cuda.get_device_name和torch.cuda.get_device_capability实现如下功能。例：

  torch.cuda.get_device_name(0) 'Quadro GP100' torch.cuda.get_device_capability(0) (6, 0)

AruniRC

{0: u'__background__',
 1: u'person',
 2: u'bicycle',
 3: u'car',
 4: u'motorcycle',
 5: u'airplane',
 6: u'bus',
 7: u'train',
 8: u'truck',
 9: u'boat',

normalize_image.ipynb

yrevar

{0: 'tench, Tinca tinca',
 1: 'goldfish, Carassius auratus',
 2: 'great white shark, white shark, man-eater, man-eating shark, Carcharodon carcharias',
 3: 'tiger shark, Galeocerdo cuvieri',
 4: 'hammerhead, hammerhead shark',
 5: 'electric ray, crampfish, numbfish, torpedo',
 6: 'stingray',
 7: 'cock',
 8: 'hen',
 9: 'ostrich, Struthio camelus',

Glench

"""
We want to run a function asychronously and run a
callback function with multiple parameters when it
returns!

In this example, we are pretending we're analyzing
the names and ages of some people. We want to print
out:

jack 0

willurd

Each of these commands will run an ad hoc http static server in your current (or specified) directory, available at http://localhost:8000. Use this power wisely.

Discussion on reddit.

Python 2.x

$ python -m SimpleHTTPServer 8000