def hasher(): hashobj = Hashing() return hashobj
import sys import pytest import numpy as np from sklearn.metrics.pairwise import cosine_similarity from imagededup.handlers.search.retrieval import ( HashEval, cosine_similarity_chunk, get_cosine_similarity, ) from imagededup.methods.hashing import Hashing HAMMING_DISTANCE_FUNCTION = Hashing().hamming_distance def test_cosine_similarity_chunk(): X = np.random.rand(333, 100) start_idx = 10 end_idx = 100 input_tuple = (X, (start_idx, end_idx)) result = cosine_similarity_chunk(input_tuple) np.testing.assert_array_almost_equal( result, cosine_similarity(X[start_idx:end_idx, :], X).astype('float16') ) def test_get_cosine_similarity(): X = np.random.rand(333, 10)