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

mjdietzx

import torch
from torch.autograd import Variable
import torch.nn as nn


class Bottleneck(nn.Module):
    cardinality = 32  # the size of the set of transformations

    def __init__(self, nb_channels_in, nb_channels, nb_channels_out, stride=1):
        super().__init__()

mjdietzx

from keras import layers
from keras import models
import tensorflow as tf


#
# generator input params
#

rand_dim = (1, 1, 2048)  # dimension of the generator's input tensor (gaussian noise)

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."

normalize_image.ipynb

xmfbit

import os
import torch
import torch.nn as nn
from torch.autograd import Variable
import torchvision.datasets as dset
import torchvision.transforms as transforms
import torch.nn.functional as F
import torch.optim as optim
## load mnist dataset
use_cuda = torch.cuda.is_available()

autosquid

# from: http://blender.stackexchange.com/questions/40650/blender-camera-from-3x4-matrix?rq=1
# And: http://blender.stackexchange.com/questions/38009/3x4-camera-matrix-from-blender-camera


# Input: P 3x4 numpy matrix
# Output: K, R, T such that P = K*[R | T], det(R) positive and K has positive diagonal
#
# Reference implementations: 
#   - Oxford's visual geometry group matlab toolbox 
#   - Scilab Image Processing toolbox

tdeboissiere

import torch
from torch.autograd import Variable
import torch.nn as nn
import numpy as np
import torch.optim as optim
import torch.nn.functional as F
import time
from torchvision.models import vgg

# Initialize network

gelim

Installing ShareLaTex on Ubuntu 16.04

Use this as-is without any warranty, and don't bug ShareLatex project members if there are problems with my instructions. They officialy support docker installation only.

This gist summarize the actions I did to setup a pure ShareLaTex community edition on a bare linux ubuntu 16.04 server (no docker). I intentionnaly tried to stick to distribution practice for running daemons (via runit, and not via a custom my_init + setuser wrapper).

I basically took ShareLaTeX receipt to build their docker and adapted it.

• Install