cdfox

import re
import sys
import numpy as np
import numba

file_name = sys.argv[1]  # one document per line
num_topics = int(sys.argv[2])
num_iterations = int(sys.argv[3])
alpha = float(sys.argv[4])
alpha0 = float(sys.argv[5])

cdfox

package main

import (
    "fmt"
    "log"
    "net/http"
)

func main() {
    http.HandleFunc("/", func(w http.ResponseWriter, r *http.Request) {

cdfox

class foo:
     def __eq__(self, o):
         return False

t = (foo(),)
t2 = (t[0],)

t == t2  # True
t[0] == t2[0]  # False
t[0] is t2[0]  # True

cdfox

# Reproducing Roblox DistilBERT Medium Post
# https://blog.roblox.com/2020/05/scaled-bert-serve-1-billion-daily-requests-cpus/
#
# 1. Launch C5 12xlarge with Deep Learning AMI (Ubuntu 18.04) Version 32.0 (ami-0dc2264cd927ca9eb)
# 2. pip install transformers[torch]
# 3. python reproduce_roblox_distilbert.py

import timeit
from transformers import DistilBertTokenizerFast, \
    DistilBertForSequenceClassification