cburgdorf

import numpy as np
from keras.models import Sequential
from keras.layers.core import Activation, Dense

training_data = np.array([[0,0],[0,1],[1,0],[1,1]], "float32")
target_data = np.array([[0],[1],[1],[0]], "float32")

model = Sequential()
model.add(Dense(32, input_dim=2, activation='relu'))
model.add(Dense(1, activation='sigmoid'))

mdouze

import numpy as np
import faiss



def search_knn(xq, xb, k, distance_type=faiss.METRIC_L2): 
    """ wrapper around the faiss knn functions without index """
    nq, d = xq.shape
    nb, d2 = xb.shape
    assert d == d2

VibhuJawa