andreyryabtsev

dvdhfnr

import torch
import torch.nn as nn


def compute_scale_and_shift(prediction, target, mask):
    # system matrix: A = [[a_00, a_01], [a_10, a_11]]
    a_00 = torch.sum(mask * prediction * prediction, (1, 2))
    a_01 = torch.sum(mask * prediction, (1, 2))
    a_11 = torch.sum(mask, (1, 2))

rxwei

See the official Differentiable Programming Manifesto instead.

thomwolf

##+++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
## Created by: Hang Zhang, Rutgers University, Email: [email protected]
## Modified by Thomas Wolf, HuggingFace Inc., Email: [email protected]
## Copyright (c) 2017-2018
##
## This source code is licensed under the MIT-style license found in the
## LICENSE file in the root directory of this source tree
##+++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++

"""Encoding Data Parallel"""

Tushar-N

import torch
import torch.nn as nn
import torch.nn.functional as F

import torchvision.models as tmodels
from functools import partial
import collections

# dummy data: 10 batches of images with batch size 16
dataset = [torch.rand(16,3,224,224).cuda() for _ in range(10)]

mcchae

# USAGE
# python image_diff.py --first images/original_01.png --second images/modified_01.png

# import the necessary packages
from skimage.measure import compare_ssim
import argparse
import imutils
import cv2

# construct the argument parse and parse the arguments

killeent

A Tour of PyTorch Internals (Part I)

The fundamental unit in PyTorch is the Tensor. This post will serve as an overview for how we implement Tensors in PyTorch, such that the user can interact with it from the Python shell. In particular, we want to answer four main questions:

1. How does PyTorch extend the Python interpreter to define a Tensor type that can be manipulated from Python code?
2. How does PyTorch wrap the C libraries that actually define the Tensor's properties and methods?
3. How does PyTorch cwrap work to generate code for Tensor methods?
4. How does PyTorch's build system take all of these components to compile and generate a workable application?

Extending the Python Interpreter

PyTorch defines a new package torch. In this post we will consider the ._C module. This module is known as an "extension module" - a Python module written in C. Such modules allow us to define new built-in object types (e.g. the Tensor) and to call C/C++ functions.

nickkraakman

FFmpeg Cheat Sheet for 360º video

Brought to you by Headjack

 
FFmpeg is one of the most powerful tools for video transcoding and manipulation, but it's fairly complex and confusing to use. That's why I decided to create this cheat sheet which shows some of the most often used commands.

 
Let's start with some basics:

• ffmpeg calls the FFmpeg application in the command line window, could also be the full path to the FFmpeg binary or .exe file

rondy

FWIW: I (@rondy) am not the creator of the content shared here, which is an excerpt from Edmond Lau's book. I simply copied and pasted it from another location and saved it as a personal note, before it gained popularity on news.ycombinator.com. Unfortunately, I cannot recall the exact origin of the original source, nor was I able to find the author's name, so I am can't provide the appropriate credits.

---

Effective Engineer - Notes

• By Edmond Lau
• Highly Recommended 👍
• http://www.theeffectiveengineer.com/

What's an Effective Engineer?

littlecodersh

#coding=utf8
import itchat
# tuling plugin can be get here:
# https://github.com/littlecodersh/EasierLife/tree/master/Plugins/Tuling
from tuling import get_response

@itchat.msg_register('Text')
def text_reply(msg):
    if u'作者' in msg['Text'] or u'主人' in msg['Text']:
        return u'你可以在这里了解他：https://github.com/littlecodersh'