DhruvilKarani

import numpy as np
import pandas as pd
from typing import List
from time import time
from multiprocessing import Pool
from multiprocessing import shared_memory
from multiprocessing.shared_memory import SharedMemory


print("--Shared Memory--")

DhruvilKarani

import numpy as np
from typing import List
from time import time
from multiprocessing import Pool

print("--No shared memory---")

M = 100000
d = 32
N = 1000

DhruvilKarani

from typing import List

import faiss
import numpy as np
from numba import jit
from numba.typed import List
from scipy.spatial.distance import cdist


def numpy_cosine_batch_nn(matrix: np.array, queries: List[np.array]):

DhruvilKarani

import numpy as np

class CustomKMeans:
    def __init__(self, k, centroids, X):
        '''
        k: number of clusters
        centroids:  initial value of centres. 
                    np.array of shape (k, n_features)
        X:  dataset of m points and n_features. 
            array of shape (m, n_features)