Loosely ordered with the commands I use most towards the top. Sublime also offer full documentation.
Ctrl+C | copy current line (if no selection) |
Ctrl+X | cut current line (if no selection) |
Ctrl+⇧+K | delete line |
Ctrl+↩ | insert line after |
""" 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 |
Loosely ordered with the commands I use most towards the top. Sublime also offer full documentation.
Ctrl+C | copy current line (if no selection) |
Ctrl+X | cut current line (if no selection) |
Ctrl+⇧+K | delete line |
Ctrl+↩ | insert line after |
The goal of this example is to show how an existing C codebase for numerical computing (here c_code.c) can be wrapped in Cython to be exposed in Python.
The meat of the example is that the data is allocated in C, but exposed in Python without a copy using the PyArray_SimpleNewFromData numpy
/* | |
working with | |
javax.json.jar | |
joda-time.jar | |
jollyday.jar | |
stanford-corenlp-3.5.1-models.jar | |
stanford-corenlp-3.5.1.jar | |
ejml-0.23.jar | |
in build path | |
*/ |