std::vector to/from np.array

std::vector to/from np.array

When you would like to directly handle std::vector in the c++ class, you can convert std::vector to np.array by faiss.vector_to_array. Similarily, you can call faiss.copy_array_to_vector to convert np.array to std::vector. See python/faiss.py for more details.

import faiss
import numpy as np

D = 2
N = 3
X = np.random.random((N, D)).astype(np.float32)
print(X)
# [[0.8482132  0.17902061]
#  [0.07226888 0.15747449]
#  [0.41783017 0.9381101 ]]

# Setup
index = faiss.IndexFlatL2(D)
index.add(X)

# Let's see std::vector inside the c++ class (IndexFlatL2)
# We cannot directly read/update them by nparray.
print(type(index.xb))  # <class 'faiss.swigfaiss.FloatVector'>
print(index.xb)  # <faiss.swigfaiss.FloatVector; proxy of <Swig Object of type 'std::vector< float > *' at 0x7fd62822a690> >

# Convert std::vector to np.array
xb_np = faiss.vector_to_array(index.xb)  # std::vector -> np.array
print(type(xb_np))  # <class 'numpy.ndarray'>
print(xb_np)  # [0.8482132  0.17902061 0.07226888 0.15747449 0.41783017 0.9381101 ]

# We can also convert np.array to std::vector
X2 = np.random.random((N, D)).astype(np.float32)  # new np.array
X2_std_vector = faiss.FloatVector()  # Buffer.
print(type(X2_std_vector))  # <class 'faiss.swigfaiss.FloatVector'>
faiss.copy_array_to_vector(X2.reshape(-1), X2_std_vector)  # np.array -> std::vector. Don't forget to flatten the np.array

# The obtained std:vector can be used inside the c++ class
index.xb = X2_std_vector  # You can set this in IndexFlatL2 (Be careful. This is dangerous)

print(index.search(x=X2, k=3))  # Works correctly
# (array([[0.        , 0.09678471, 0.5692644 ],
#        [0.        , 0.09678471, 0.23682791],
#        [0.        , 0.23682791, 0.5692644 ]], dtype=float32), array([[0, 1, 2],
#        [1, 0, 2],
#        [2, 1, 0]]))