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@nlothian
nlothian / gist:3127581
Created July 17, 2012 06:25
OpenStack authentication return
View gist:3127581
{
"access": {
"token": {
"expires": "2012-04-23T23:54:00",
"id": "<id>",
"tenant": {
"id": "<tenantId>",
"name": "<username>"
}
},
@nlothian
nlothian / Trystack images JSON
Created July 17, 2012 06:43
JSON returned from Trystack
View Trystack images JSON
{
"images":[
{
"status":"ACTIVE",
"updated":"2012-02-02T19:11:00Z",
"name":"oneiric-server-cloudimg-amd64",
"links":[
{
"href":"https://nova-api.trystack.org:9774/v1.1/<tenantId>/images/15",
"rel":"self"
@nlothian
nlothian / Penn Treebank II Tags.md
Last active January 29, 2024 19:54
Penn Treebank II Tags
View Penn Treebank II Tags.md
View imagerecognizer.py
from flask import Flask
from flask import request
import simplejson as json
from decimal import Decimal
import numpy as np
import os
import sys
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],
@nlothian
nlothian / fasttext_to_tensorboard.py
Created November 23, 2017 23:28
Convert a FastText model to a form suitable for viewing in Tensorboard
View fasttext_to_tensorboard.py
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 fasttext_plus_continous_keras.py
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
nlothian / Untitled.ipynb
Created August 5, 2020 11:13
Weird PIL behaviour
View Untitled.ipynb
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@nlothian
nlothian / matplotlib2base64MD.py
Created February 18, 2021 02:33
Convert a matplotlib graph to base64, suitable for inclusing as a data: url in HTML.
View matplotlib2base64MD.py
def build_GRAPHS_MD(fig):
# encode as base64 for markdown display
buf = io.BytesIO()
fig.savefig(buf, format='png')
buf.seek(0)
b64str = base64.b64encode(buf.read()).decode('ascii')
plt.close()
markdown_txt = f"""
View clip_words.txt
!
""""
#
$
%
&
'
(
)
*