JasonKessler

url = 'https://openreview.net/notes?invitation=ICLR.cc%2F2018%2FConference%2F-%2FBlind_Submission&offset=0&limit=1000'
df = pd.DataFrame(requests.get(url).json()['notes']) # Each row in this data frame is a paper.
forum_content = []
for i, forum_id in list(enumerate(df.forum)): # Each forum_id is a review, comment, or acceptance decision about a paper.
  forum_content.append(requests.get('https://openreview.net/notes?forum={}&trash=true'.format(forum_id)).json())
  time.sleep(.3)
df['forumContent'] = pd.Series(forum_content)

wangruohui

In this article, I will share some of my experience on installing NVIDIA driver and CUDA on Linux OS. Here I mainly use Ubuntu as example. Comments for CentOS/Fedora are also provided as much as I can.

Table of Contents

• Install NVIDIA Graphics Driver via apt-get
• Install NVIDIA Graphics Driver via runfile
  • Remove Previous Installations (Important)
  • Download the Driver
  • Install Dependencies
  • Creat Blacklist for Nouveau Driver

• Stop lightdm/gdm/kdm

karpathy

""" Trains an agent with (stochastic) Policy Gradients on Pong. Uses OpenAI Gym. """
import numpy as np
import cPickle as pickle
import gym

# hyperparameters
H = 200 # number of hidden layer neurons
batch_size = 10 # every how many episodes to do a param update?
learning_rate = 1e-4
gamma = 0.99 # discount factor for reward

sangheestyle

Install and using numba on mac

• Mac version: 10.11.3
• Python version: 3.5.1

Install

$ brew tap homebrew/versions
$ brew install llvm37

danoneata

import numpy as np


def fvecs_read(filename, c_contiguous=True):
    fv = np.fromfile(filename, dtype=np.float32)
    if fv.size == 0:
        return np.zeros((0, 0))
    dim = fv.view(np.int32)[0]
    assert dim > 0
    fv = fv.reshape(-1, 1 + dim)