mjpost

#!/usr/bin/env python3

"""
This is code to take a trained Fairseq model and discard the ADAM optimizer state,
which is not needed at test time. It can reduce a model size by ~70%.

Original author: Brian Thompson
"""

from fairseq import checkpoint_utils

zhaoguangxiang

import sys
import os
import hashlib
import struct
import subprocess
import collections
import codecs
# import tensorflow as tf
# from tensorflow.core.example import example_pb2
# import sys

peterjliu

Shortlink: goo.gl/wSuuS9

Supplementary Materials for Generating Wikipedia by Summarizing Long Sequences

The github repository can be found at https://github.com/tensorflow/tensor2tensor/tree/master/tensor2tensor/data_generators/wikisum

hscspring

- a 形容词  
	- ad 副形词  
	- ag 形容词性语素  
	- an 名形词  
- b 区别词  
- c 连词  
- d 副词  
	- df   
	- dg 副语素  
- e 叹词  

kylemcdonald

Liam0205

%!TEX program = xelatex
% Font Size:
%   10pt, 11pt, 12pt
% Paper Size:
%   a4paper, letterpaper, a5paper, leagalpaper, executivepaper, landscape
% Font Family:
%   roman, sans
\documentclass[12pt, a4paper, roman]{moderncv}

% Style:

fchollet

'''This script goes along the blog post
"Building powerful image classification models using very little data"
from blog.keras.io.
It uses data that can be downloaded at:
https://www.kaggle.com/c/dogs-vs-cats/data
In our setup, we:
- created a data/ folder
- created train/ and validation/ subfolders inside data/
- created cats/ and dogs/ subfolders inside train/ and validation/
- put the cat pictures index 0-999 in data/train/cats

fchollet

'''This script goes along the blog post
"Building powerful image classification models using very little data"
from blog.keras.io.
It uses data that can be downloaded at:
https://www.kaggle.com/c/dogs-vs-cats/data
In our setup, we:
- created a data/ folder
- created train/ and validation/ subfolders inside data/
- created cats/ and dogs/ subfolders inside train/ and validation/
- put the cat pictures index 0-999 in data/train/cats

bennylope

How to Add a Watermark to Video

FFMPEG filters provide a powerful way to programmatically enhance or alter videos, and it’s fairly simple to add a watermark to a video using the overlay filter. The easiest way to install ffmpeg is to download a pre-built binary for your specific platform. Then you don’t have to worry about including and installing all the right dependencies and codecs you will be using.

Once you have ffmpeg installed, adding a watermark is as easy as passing your existing source through an overlay filter like so:

ffmpeg -i test.mp4 -i watermark.png -filter_complex "overlay=10:10" test1.mp4

Basically, we’re passing in the original video, and an overlay image as inputs, then passing it through the filter, and saving the output as test1.mp4.

albertomontesg