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inp = Input(shape=(maxlen,), name="text_input") # featureized text comes in here
x = Embedding(embedding_matrix.shape[0], embed_size, weights=[embedding_matrix], trainable=True)(inp)
x = Dense(some_num_here, activation="relu")(x)
extra_data = Input(shape=(1,), name="extra_data") # your continous features comes in here
combined = concatenate([x, extra_data])
# maybe some ReLu + Dropout here
nlothian /
Created Nov 23, 2017
Convert a FastText model to a form suitable for viewing in Tensorboard
from tensorflow.contrib.tensorboard.plugins import projector
import tensorflow as tf
import numpy as np
import os
meta_file = "g2x_metadata.tsv"
output_path = "./projections"
# read embedding file into list and get the size
with open('./ft_model.vec', 'r') as embedding_file:
View M.2 256GB Samsung 950 EVO
sudo fio --filename=./testfile --direct=1 --sync=1 --rw=read --bs=4k --numjobs=8 --iodepth=32 --runtime=60 --time_based --group_reporting --size=1G --name=journal-test
journal-test: (groupid=0, jobs=8): err= 0: pid=3092: Thu Jun 2 22:48:23 2016
read : io=21433MB, bw=365792KB/s, iops=91447, runt= 60001msec
clat (usec): min=11, max=15999, avg=86.72, stdev=34.31
lat (usec): min=11, max=15999, avg=86.81, stdev=34.31
clat percentiles (usec):
| 1.00th=[ 60], 5.00th=[ 63], 10.00th=[ 66], 20.00th=[ 75],
| 30.00th=[ 78], 40.00th=[ 80], 50.00th=[ 82], 60.00th=[ 90],
from flask import Flask
from flask import request
import simplejson as json
from decimal import Decimal
import numpy as np
import os
import sys
nlothian / Penn Treebank II
Last active Dec 11, 2019
Penn Treebank II Tags
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nlothian / Trystack images JSON
Created Jul 17, 2012
JSON returned from Trystack
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nlothian / gist:3127581
Created Jul 17, 2012
OpenStack authentication return
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"access": {
"token": {
"expires": "2012-04-23T23:54:00",
"id": "<id>",
"tenant": {
"id": "<tenantId>",
"name": "<username>"
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