e-mon

import os
from sqlalchemy import create_engine
from sqlalchemy.types import VARCHAR
from pandas.io.sql import SQLTable, pandasSQL_builder
import tempfile
import numpy as np
import boto3
import json
import pandas as pd
from sqlalchemy import text

e-mon

def re_ranking(model, probFea,galFea,k1,k2,lambda_value):
    query_num = probFea.shape[0]
    all_num = query_num + galFea.shape[0]    
    feat = np.append(probFea,galFea,axis = 0)
    feat = feat.astype(np.float16)
    feat = torch.from_numpy(feat).half().cuda()
    print('computing original distance')

    sz = feat.shape[0]
    d = []

e-mon

def qwk(a1, a2):
    """
    Source: https://www.kaggle.com/c/data-science-bowl-2019/discussion/114133#latest-660168

    :param a1:
    :param a2:
    :param max_rat:
    :return:
    """
    max_rat = 3