swyoon

import numpy as np
import tensorflow as tf

__author__ = "Sangwoong Yoon"

def np_to_tfrecords(X, Y, file_path_prefix, verbose=True):
    """
    Converts a Numpy array (or two Numpy arrays) into a tfrecord file.
    For supervised learning, feed training inputs to X and training labels to Y.
    For unsupervised learning, only feed training inputs to X, and feed None to Y.

victor-shepardson

Code

https://gist.github.com/victor-shepardson/5b3d3087dc2b4817b9bffdb8e87a57c4

Setup

I'm using Ubuntu 16.04 with a GTX 1060

install CUDA

victor-shepardson

from contextlib import contextmanager
import numpy as np
import torch
from torch import Tensor, ByteTensor
import torch.nn.functional as F
from torch.autograd import Variable
import pycuda.driver
from pycuda.gl import graphics_map_flags
from glumpy import app, gloo, gl

janoliver

In this short article, I show you how to create nice scientific presentations using a combination of Inkscape and LaTex, made possible by two small tools I wrote.

The Tools

• Inkscape: Our main vector graphics editor to draw the presentation.
• InkSlides: The python script to convert an Inkscape SVG file to a PDF presentation. Heavily inspired and partly copied from inkscapeslide.

deeplook

"""
Run the algorithm below using CPython, Cython, PyPy and Numba and compare 
their performance. (This is implementing a spigot algorithm by A. Sale, 
D. Saada, S. Rabinowitz, mentioned on
http://mail.python.org/pipermail/edu-sig/2012-December/010721.html).
"""

def pi_digits(n):
    "Generate n digits of Pi."
    k, a, b, a1, b1 = 2, 4, 1, 12, 4