aputs

export MACOSX_DEPLOYMENT_TARGET=11.0
brew install pyenv bzip2 zlib xz [email protected]

## 3.6.8
CFLAGS="-I$(brew --prefix openssl)/include -I$(brew --prefix bzip2)/include -I$(brew --prefix readline)/include -I$(xcrun --show-sdk-path)/usr/include" LDFLAGS="-L$(brew --prefix openssl)/lib -L$(brew --prefix readline)/lib -L$(brew --prefix zlib)/lib -L$(brew --prefix bzip2)/lib" pyenv install --patch 3.6.8 < <(curl -sSL https://github.com/python/cpython/commit/8ea6353.patch\?full_index\=1)

## 3.6.12
CFLAGS="-I$(brew --prefix openssl)/include -I$(brew --prefix bzip2)/include -I$(brew --prefix readline)/include -I$(xcrun --show-sdk-path)/usr/include" LDFLAGS="-L$(brew --prefix openssl)/lib -L$(brew --prefix readline)/lib -L$(brew --prefix zlib)/lib -L$(brew --prefix bzip2)/lib" pyenv install --patch 3.6.12 < <(curl -sSL https://github.com/python/cpython/commit/8ea6353.patch\?full_index\=1)

## 3.7.9

ines

"""
Example of a Streamlit app for an interactive Prodigy dataset viewer that also lets you
run simple training experiments for NER and text classification.

Requires the Prodigy annotation tool to be installed: https://prodi.gy
See here for details on Streamlit: https://streamlit.io.
"""
import streamlit as st
from prodigy.components.db import connect
from prodigy.models.ner import EntityRecognizer, merge_spans, guess_batch_size

tokestermw

import click

import torch
import torch.autograd
import torch.nn.functional as F
from torch.autograd import Variable

import os
import random
import math

groteck

port module Spelling exposing (..)

import Html exposing (..)
import Html.Events exposing (..)
import String


main =
    program
        { init = init

danneu

module Current where

import Native.Current

import Time exposing (Time)
import Date exposing (Date)

-- milliseconds since epoch
time : () -> Time
time _ =

evanscottgray

docker ps | awk {' print $1 '} | tail -n+2 > tmp.txt; for line in $(cat tmp.txt); do docker kill $line; done; rm tmp.txt

jboner

Latency Comparison Numbers (~2012)
----------------------------------
L1 cache reference                           0.5 ns
Branch mispredict                            5   ns
L2 cache reference                           7   ns                      14x L1 cache
Mutex lock/unlock                           25   ns
Main memory reference                      100   ns                      20x L2 cache, 200x L1 cache
Compress 1K bytes with Zippy             3,000   ns        3 us
Send 1K bytes over 1 Gbps network       10,000   ns       10 us
Read 4K randomly from SSD*             150,000   ns      150 us          ~1GB/sec SSD