sailfish009

import base64
import os
import json
import pickle
import uuid
import re

import streamlit as st
import pandas as pd

sailfish009

function perc2color(perc) {
	var r, g, b = 0;
	if(perc < 50) {
		r = 255;
		g = Math.round(5.1 * perc);
	}
	else {
		g = 255;
		r = Math.round(510 - 5.10 * perc);
	}

sailfish009

Installing the NVIDIA driver, CUDA and cuDNN on Linux (Ubuntu 20.04)

This is a companion piece to my instructions on building TensorFlow from source. In particular, the aim is to install the following pieces of software

• NVIDIA graphics card driver (v450.57)
• CUDA (v11.0.2)
• cuDNN (v8.0.2.39)

on an Ubuntu Linux system, in particular Ubuntu 20.04.

sailfish009

def make_weights_for_balanced_classes(images, nclasses):                        
    count = [0] * nclasses                                                      
    for item in images:                                                         
        count[item[1]] += 1                                                     
    weight_per_class = [0.] * nclasses                                      
    N = float(sum(count))                                                   
    for i in range(nclasses):                                                   
        weight_per_class[i] = N/float(count[i])                                 
    weight = [0] * len(images)                                              
    for idx, val in enumerate(images):                                          

sailfish009

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class Ralamb(Optimizer):

    def __init__(self, params, lr=1e-3, betas=(0.9, 0.999), eps=1e-8, weight_decay=0):
        defaults = dict(lr=lr, betas=betas, eps=eps, weight_decay=weight_decay)
        self.buffer = [[None, None, None] for ind in range(10)]
        super(Ralamb, self).__init__(params, defaults)

    def __setstate__(self, state):
        super(Ralamb, self).__setstate__(state)

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from typing import Union

import torch
import numpy as np


def percentile(t: torch.tensor, q: float) -> Union[int, float]:
    """
    Return the ``q``-th percentile of the flattened input tensor's data.
    

sailfish009

import xmltodict
import pandas as pd

with open("full_database.xml") as db:
    doc = xmltodict.parse(db.read())

values = []
for item in doc['drugbank']['drug']:
    logp = None
    try:

sailfish009

import os, time, sys, subprocess

if len(sys.argv) == 2:
    time.sleep(5)
    print 'track end'
    if sys.platform == 'darwin':
	    subprocess.Popen(['say', 'hello'])
else:
    print 'main begin'
    subprocess.Popen(['python', os.path.realpath(__file__), '0'], close_fds=True)

sailfish009

import os
import sys
import traceback
from functools import wraps
from multiprocessing import Process, Queue


def processify(func):
    '''Decorator to run a function as a process.
    Be sure that every argument and the return value