start new:
tmux
start new with session name:
tmux new -s myname
王 | |
江 | |
周 | |
胡 | |
刘 | |
李 | |
吴 | |
毛 | |
温 | |
习 |
sudo find /private/var/folders/ -name com.apple.dock.iconcache -exec rm {} \; |
var waitForEl = function(selector, callback) { | |
if (jQuery(selector).length) { | |
callback(); | |
} else { | |
setTimeout(function() { | |
waitForEl(selector, callback); | |
}, 100); | |
} | |
}; |
''' Script for downloading all GLUE data. | |
Note: for legal reasons, we are unable to host MRPC. | |
You can either use the version hosted by the SentEval team, which is already tokenized, | |
or you can download the original data from (https://download.microsoft.com/download/D/4/6/D46FF87A-F6B9-4252-AA8B-3604ED519838/MSRParaphraseCorpus.msi) and extract the data from it manually. | |
For Windows users, you can run the .msi file. For Mac and Linux users, consider an external library such as 'cabextract' (see below for an example). | |
You should then rename and place specific files in a folder (see below for an example). | |
mkdir MRPC | |
cabextract MSRParaphraseCorpus.msi -d MRPC |
#! /usr/bin/env python | |
import tensorflow as tf | |
def inference_fn(x, training=False): | |
net = x | |
net = tf.layers.flatten(net) | |
net = tf.layers.dense(net, 512, activation=tf.nn.relu) | |
net = tf.layers.dropout(net, 0.2, training=training) |