chpatrick

import numpy as np
import re
import sys

'''
Load a PFM file into a Numpy array. Note that it will have
a shape of H x W, not W x H. Returns a tuple containing the
loaded image and the scale factor from the file.
'''
def load_pfm(file):

victorgan

# Literally, from a completely fresh install, except for system updates.
# START TUTORIAL: http://wiki.ros.org/indigo/Installation/Ubuntu
# Note: In Ubuntu 9.04 (Jaunty) and later, the main, universe, restricted and multiverse repositories are enabled by default.
  
# accept software from ROS sources
sudo sh -c 'echo "deb http://packages.ros.org/ros/ubuntu trusty main" > /etc/apt/sources.list.d/ros-latest.list'

# set up keys
wget https://raw.githubusercontent.com/ros/rosdistro/master/ros.key -O - | sudo apt-key add -

samiraguiar

Note for newcomers:

In the shortcuts below, "C" stands for CTRL and "A" stands for "ALT". This is a convention
used in the Midnight Commander documentation and was kept here.

You can also use "ESC" instead of "ALT", which is useful on Macbooks.

Main View
---------------------------------------------------------------
- File/directory operations

0xjac

The repository for the assignment is public and Github does not allow the creation of private forks for public repositories.

The correct way of creating a private frok by duplicating the repo is documented here.

For this assignment the commands are:

1. Create a bare clone of the repository. (This is temporary and will be removed so just do it wherever.)

git clone --bare git@github.com:usi-systems/easytrace.git

apaszke

from graphviz import Digraph
import torch
from torch.autograd import Variable, Function

def iter_graph(root, callback):
    queue = [root]
    seen = set()
    while queue:
        fn = queue.pop()
        if fn in seen:

apaszke

from graphviz import Digraph
import torch
from torch.autograd import Variable, Function

def iter_graph(root, callback):
    queue = [root]
    seen = set()
    while queue:
        fn = queue.pop()
        if fn in seen:

kendricktan

"""
Dynamic Routing Between Capsules
https://arxiv.org/abs/1710.09829
"""

import torch
import torch.nn as nn
import torch.optim as optim
import torch.nn.functional as F
import torchvision.transforms as transforms

NegatioN

def _to_one_hot(y, num_classes):
    scatter_dim = len(y.size())
    y_tensor = y.view(*y.size(), -1)
    zeros = torch.zeros(*y.size(), num_classes, dtype=y.dtype)
        
    return zeros.scatter(scatter_dim, y_tensor, 1)


print(_to_one_hot(torch.as_tensor([2, 4, 7]), num_classes=10))
print(_to_one_hot(torch.as_tensor([[1, 5 ,6], [2, 4, 7]]), num_classes=10))

mhubii

PyTorch C++ API Ubuntu Installation Guide

The best way to get a clean installation of PyTorch, is to install the pre-compiled binaries from the Anaconda distribution. Therefore, we need to setup Anaconda first.

Step 1: Install Anaconda

• Go to the download section and download your desired Anaconda version for Linux

• Run the downloaded shell script and follow the install instruction, do

immuntasir