kingsj0405

Latency numbers every programmer should know

L1 cache reference ......................... 0.5 ns
Branch mispredict ............................ 5 ns
L2 cache reference ........................... 7 ns
Mutex lock/unlock ........................... 25 ns
Main memory reference ...................... 100 ns             
Compress 1K bytes with Zippy ............. 3,000 ns  =   3 µs
Send 2K bytes over 1 Gbps network ....... 20,000 ns  =  20 µs
SSD random read ........................ 150,000 ns  = 150 µs

Read 1 MB sequentially from memory ..... 250,000 ns = 250 µs

kingsj0405

# Forked from vgg perceptual loss
# https://gist.github.com/alper111/8233cdb0414b4cb5853f2f730ab95a49
import torch
import torchvision


class VGGFeatureExtractor(torch.nn.Module):
    def __init__(self, resize=True):
        super(VGGFeatureExtractor, self).__init__()
        blocks = []

kingsj0405

Including iframe of an github (gists) embled script

So for include a github embled iframe into an iframe You may use hex code

see this exemple :
The github embled link : <script src="https://gist.github.com/lostsh/dfb8a51aeb3ad5d7e3cefbc66d72fa53.js"></script> and ths iframe who contain this embled :

kingsj0405

#!/bin/bash
#
# script to extract ImageNet dataset
# ILSVRC2012_img_train.tar (about 138 GB)
# ILSVRC2012_img_val.tar (about 6.3 GB)
# make sure ILSVRC2012_img_train.tar & ILSVRC2012_img_val.tar in your current directory
#
#  https://github.com/facebook/fb.resnet.torch/blob/master/INSTALL.md
# 
#  train/