yzh119

from __future__ import print_function
import torch
import torch.nn as nn
import torch.nn.functional as F
from torch.autograd import Variable

def sample_gumbel(shape, eps=1e-20):
    U = torch.rand(shape).cuda()
    return -Variable(torch.log(-torch.log(U + eps) + eps))

ajbrock

# PyTorch code For implementing the mixture of softmaxes layer from 
# "Breaking the Softmax Bottleneck: A High-Rank RNN Language Model"
# https://arxiv.org/abs/1711.03953
context = self.fc(out)
        
# Non-log version
priors = F.softmax(context[:,-self.n_components:])
mixtures = torch.stack([priors[:,i].unsqueeze(1) * F.softmax(context[:, i * self.nClasses : (i + 1) * self.nClasses]) for i in range(self.n_components)],1)
out = torch.log(mixtures.sum(1))

codekansas

/* Binarized neural network inference example.
   This shows a simple C++ program for doing inference on
   binarized neural networks. To do this efficiently, the code
   below makes use of the "bitset" class, which uses the "popcnt"
   instruction to count the number of 1's that show up in the
   matrix product, in constant time. This means that a matrix
   multiplication between a (A, B) and (B, C) matrix takes
   O(A * C) time; in other words, each value in the output matrix
   is computed in constant time.
 */

ankurk91

elementaryOS Apps and Configs

⚠️ No longer maintained! ⚠️

This guide has been updated for elementaryOS v5.0+.

Enbale PPA support

sudo apt-get update
sudo apt-get -y install software-properties-common

install-faiss-with-mkl.sh

#!/usr/bin/env bash

# The following assumes you have a pyenv virtualenv named faiss. Tested on
# Ubuntu 16.04.

set -eox pipefail

# shellcheck disable=SC1090
source "${HOME}/.pyenv.sh"

lirnli

timvieira

"""
Simple example of manually performing "automatic" differentiation
"""
import numpy as np
from numpy import exp, sin, cos


def f(x, with_grad=False):
    # Need to cache intermediates from forward pass (might not use all of them).
    a = exp(x)

eamartin

yanaiela

#!/bin/bash

# usage: 
# first make the file executable
# ./word2vec-download300model.sh output-file

OUTPUT=$( wget --save-cookies cookies.txt --keep-session-cookies --no-check-certificate 'https://docs.google.com/uc?export=download&id=0B7XkCwpI5KDYNlNUTTlSS21pQmM' -O- | sed -rn 's/.*confirm=([0-9A-Za-z_]+).*/Code: \1\n/p' )
CODE=${OUTPUT##*Code: }
echo $CODE

mjdietzx

# http://www.nvidia.com/download/driverResults.aspx/117079/en-us
wget http://us.download.nvidia.com/tesla/375.51/nvidia-driver-local-repo-ubuntu1604_375.51-1_amd64.deb
sudo dpkg -i nvidia-driver-local-repo-ubuntu1604_375.51-1_amd64.deb
sudo apt-get update
sudo apt-get -y install cuda-drivers

echo "Reboot required."