EdisonLeeeee

import torch
import tensorflow as tf

########## PyTorch Version 1 ################
x = torch.randn(5, 6)
norm_th = x/torch.norm(x, p=2, dim=1, keepdim=True)
norm_th[torch.isnan(norm_th)] = 0 # to avoid nan

########## PyTorch Version 2 ################
norm_th = torch.nn.functional.normalize(x, p=2, dim=1)

RuolinZheng08

def is_valid_state(state):
    # check if it is a valid solution
    return True

def get_candidates(state):
    return []

def search(state, solutions):
    if is_valid_state(state):
        solutions.append(state.copy())

imflash217

import torch

input = torch.randn(1, 2, 1025); input

##### ENCODER
# layer-1
downsample_1a = torch.nn.Conv1d(2, 20, 5 , stride=1, padding=0)
downsample_1b = torch.nn.Conv1d(2, 20, 50 , stride=1, padding=0)
downsample_1c = torch.nn.Conv1d(2, 20, 256 , stride=1, padding=0)
downsample_1d = torch.nn.Conv1d(2, 20, 512 , stride=1, padding=0)

umidjons

Download Audio from YouTube

-i - ignore errors

-c - continue

-t - use video title as file name

--extract-audio - extract audio track

otkrsk

Step 1: Generate first ssh key Type the following command to generate your first public and private key on a local workstation. Next provide the required input or accept the defaults. Please do not change the filename and directory location.

workstation 1 $ ssh-keygen -t rsa

Finally, copy your public key to your remote server using scp

wangruohui

In this article, I will share some of my experience on installing NVIDIA driver and CUDA on Linux OS. Here I mainly use Ubuntu as example. Comments for CentOS/Fedora are also provided as much as I can.

Table of Contents

• Install NVIDIA Graphics Driver via apt-get
• Install NVIDIA Graphics Driver via runfile
  • Remove Previous Installations (Important)
  • Download the Driver
  • Install Dependencies
  • Creat Blacklist for Nouveau Driver

• Stop lightdm/gdm/kdm

ishu3101

Transfer a gist to a GitHub repository

clone the gist

git clone https://gist.github.com/ishu3101/6fb35afd237e42ef25f9

rename the directory

mv 6fb35afd237e42ef25f9 ConvertTo-Markdown

change the working directory to the newly renamed directory

cd ConvertTo-Markdown

rponte

# The command finds the most recent tag that is reachable from a commit.
# If the tag points to the commit, then only the tag is shown.
# Otherwise, it suffixes the tag name with the number of additional commits on top of the tagged object 
# and the abbreviated object name of the most recent commit.
git describe

# With --abbrev set to 0, the command can be used to find the closest tagname without any suffix:
git describe --abbrev=0

# other examples

Chaser324

Whether you're trying to give back to the open source community or collaborating on your own projects, knowing how to properly fork and generate pull requests is essential. Unfortunately, it's quite easy to make mistakes or not know what you should do when you're initially learning the process. I know that I certainly had considerable initial trouble with it, and I found a lot of the information on GitHub and around the internet to be rather piecemeal and incomplete - part of the process described here, another there, common hangups in a different place, and so on.

In an attempt to coallate this information for myself and others, this short tutorial is what I've found to be fairly standard procedure for creating a fork, doing your work, issuing a pull request, and merging that pull request back into the original project.

Creating a Fork

Just head over to the GitHub page and click the "Fork" button. It's just that simple. Once you've done that, you can use your favorite git client to clone your repo or j

mycodeschool

/* Doubly Linked List implementation */
#include<stdio.h>
#include<stdlib.h>

struct Node  {
	int data;
	struct Node* next;
	struct Node* prev;
};