y0ast

# Now available here: https://github.com/y0ast/pytorch-snippets/tree/main/subset_of_imagenet

y0ast

# Now available here: https://github.com/y0ast/pytorch-snippets/tree/main/minimal_cifar

sbarratt

def get_jacobian(net, x, noutputs):
    x = x.squeeze()
    n = x.size()[0]
    x = x.repeat(noutputs, 1)
    x.requires_grad_(True)
    y = net(x)
    y.backward(torch.eye(noutputs))
    return x.grad.data

apaszke

import torch                                                                                          
                                                                                                      
def jacobian(y, x, create_graph=False):                                                               
    jac = []                                                                                          
    flat_y = y.reshape(-1)                                                                            
    grad_y = torch.zeros_like(flat_y)                                                                 
    for i in range(len(flat_y)):                                                                      
        grad_y[i] = 1.                                                                                
        grad_x, = torch.autograd.grad(flat_y, x, grad_y, retain_graph=True, create_graph=create_graph)
        jac.append(grad_x.reshape(x.shape))                                                      

talkingmoose

(*

----------------------------------------------------------------------------------

ABOUT THIS SCRIPT

Written by:William Smith
Professional Services Engineer
Jamf
bill@talkingmoose.net

apaszke

def Rop(y, x, v):
  """Computes an Rop.
  
  Arguments:
    y (Variable): output of differentiated function
    x (Variable): differentiated input
    v (Variable): vector to be multiplied with Jacobian from the right
  """
  w = torch.ones_like(y, requires_grad=True)
  return torch.autograd.grad(torch.autograd.grad(y, x, w), w, v)

noopkat

⚠️ this is now stupidly out of date

Computers

• 13" Macbook Pro 3.3 GHz i7 (late 2016)
• Microsoft Surface Book (2016)

Peripherals

• Dell up3216q 32" monitor

dapperfu

#!/usr/bin/env bash

# Config
MAINTAINER="Jed Frey"
VERSION=3.2.0

# Adapted from http://www.pyimagesearch.com/2016/10/24/ubuntu-16-04-how-to-install-opencv/
apt-get install --yes libjpeg-dev libtiff5-dev libjasper-dev libpng12-dev libavcodec-dev libavformat-dev \
			libswscale-dev libxvidcore-dev libx264-dev libv4l-dev liblapacke-dev libgtk-3-dev \
			libopenblas-dev libhdf5-dev libtesseract-dev libleptonica-dev \

alexlee-gk

This was tested on a ThinkPad P70 laptop with an Intel integrated graphics and an NVIDIA GPU:

lspci | egrep 'VGA|3D'
00:02.0 VGA compatible controller: Intel Corporation Device 191b (rev 06)
01:00.0 VGA compatible controller: NVIDIA Corporation GM204GLM [Quadro M3000M] (rev a1)

A reason to use the integrated graphics for display is if installing the NVIDIA drivers causes the display to stop working properly. In my case, Ubuntu would get stuck in a login loop after installing the NVIDIA drivers. This happened regardless if I installed the drivers from the "Additional Drivers" tab in "System Settings" or the ppa:graphics-drivers/ppa in the command-line.

soply

import matplotlib.pyplot as plt
import numpy as np

def show_images(images, cols = 1, titles = None):
    """Display a list of images in a single figure with matplotlib.
    
    Parameters
    ---------
    images: List of np.arrays compatible with plt.imshow.