loretoparisi

With wildcard

{
  "query": {
    "bool": {
      "must": [
        {
          "wildcard": {
 "text": "*antonio*banderas*"

loretoparisi

def trace_mem(nframe=6,top=8):
    '''
        naive memory trace
    '''
    import tracemalloc
    is_tracing = tracemalloc.is_tracing()
    if not is_tracing:
        # start tracing
        tracemalloc.start(nframe)
        return {}

loretoparisi

async function getObjectAsync(bucket, key) {
  try {
    const data = await s3
      .getObject({ Bucket: bucket, Key: key })
      .promise();
    var contents = data.Body.toString('utf-8');
    return contents;
  } catch (err) {
    console.log(err);
  }

loretoparisi

function aggressive_tokenizer(text) {
    // most punctuation
    text = text.replace(/[^\w\.\-\/\+\<\>,&]/g, " $& ");
    // commas if followed by space
    text = text.replace(/(,\s)/g, " $1");
    // single quotes if followed by a space
    text = text.replace(/('\s)/g, " $1");
    // single quotes if last char
    text = text.replace(/('$)/, " $1");
    text = text.replace(/(\s+[`'"‘])(\w+)\b(?!\2)/g, " $2");

loretoparisi

#!/usr/bin/env python
# -*- coding: utf-8 -*-
#
# @author loretoparisi at gmail dot com
# Copyright (c) 2020 Loreto Parisi
#

### built-in
import argparse
import json

thomwolf

import os; import psutil; import timeit
from datasets import load_dataset

mem_before = psutil.Process(os.getpid()).memory_info().rss >> 20
wiki = load_dataset("wikipedia", "20200501.en", split='train')
mem_after = psutil.Process(os.getpid()).memory_info().rss >> 20
print(f"RAM memory used: {(mem_after - mem_before)} MB")

s = """batch_size = 1000
for i in range(0, len(wiki), batch_size):

malharb

prediction = model.predict_classes(X_test)
prediction = prediction.reshape(5370,)

data = {'True':y_test,'Predicted':prediction}
df2 = pd.DataFrame(data)

from sklearn.metrics import classification_report,confusion_matrix
print(classification_report(df2['True'],df2['Predicted']))

print(confusion_matrix(df2['True'],df2['Predicted']))

loretoparisi

Get started by creating a new file or uploading an existing file. We recommend every repository include a README, LICENSE, and .gitignore.

…or create a new repository on the command line

echo "# myrepo" >> README.md
git init
git add README.md
git commit -m "first commit"
git remote add origin https://github.com/loretoparisi/myrepo.git
git push -u origin master

julien-c

API Name	Memory	vCPUs	Physical Processor	Network Performance	Linux On Demand cost	Linux Reserved cost
a1.2xlarge	16.0 GiB	8 vCPUs	AWS Graviton Processor	Up to 10 Gigabit	$148.92 monthly	$93.80 monthly
a1.4xlarge	32.0 GiB	16 vCPUs	AWS Graviton Processor	Up to 10 Gigabit	$297.84 monthly	$187.61 monthly
a1.large	4.0 GiB	2 vCPUs	AWS Graviton Processor	Up to 10 Gigabit	$37.23 monthly	$23.43 monthly
a1.medium	2.0 GiB	1 vCPUs	AWS Graviton Processor	Up to 10 Gigabit	$18.61 monthly	$11.75 monthly
a1.metal	32.0 GiB	16 vCPUs	AWS Graviton Processor	Up to 10 Gigabit	$297.84 monthly	$187.61 monthly
a1.xlarge	8.0 GiB	4 vCPUs	AWS Graviton Processor	Up to 10 Gigabit	$74.46 monthly	$46.93 monthly
c1.medium	1.7 GiB	2 vCPUs	Intel Xeon Family	Moderate	$94.90 monthly	$66.43 monthly

loretoparisi

[
  {
    "title": "'Corine, Corine'",
    "artist": "The Abletones Big Band",
    "count": "19",
    "size": "393 MB",
    "link": "http://mtkdata.cambridgemusictechnology.co.uk/Telefunken/AbletonesBigBand_CorineCorine_Full.zip"
  },
  {
    "title": "'Song Of India'",