01/13/2012. From a lecture by Professor John Ousterhout at Stanford, class CS140
Here's today's thought for the weekend. A little bit of slope makes up for a lot of Y-intercept.
[Laughter]
Note: I'm currently taking a break from this course to focus on my studies so I can finally graduate
""" | |
client.py - AsyncIO Server using StreamReader and StreamWriter | |
This will create 200 client connections to a server running server.py | |
It will handshake and run similar to this: | |
Server: HELLO | |
Client: WORLD |
##VGG16 model for Keras
This is the Keras model of the 16-layer network used by the VGG team in the ILSVRC-2014 competition.
It has been obtained by directly converting the Caffe model provived by the authors.
Details about the network architecture can be found in the following arXiv paper:
Very Deep Convolutional Networks for Large-Scale Image Recognition
K. Simonyan, A. Zisserman
from bitsandbytes.nn.modules import Linear8bitLt, Linear4bit | |
from contextlib import contextmanager | |
def noop (x=None, *args, **kwargs): | |
"Do nothing" | |
return x | |
@contextmanager | |
def no_kaiming(): | |
old_iku = init.kaiming_uniform_ |
Taught by Brad Knox at the MIT Media Lab in 2014. Course website. Lecture and visiting speaker notes.
Install deps
$ sudo pip install cogapp
$ sudo pip install jinja2
Run COG