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Sentence-Transformers ve E5-Large model aktarımı.
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from __future__ import annotations
import numpy as np
import torch
from sentence_transformers.util.tensor import normalize_embeddings
def test_normalize_embeddings() -> None:
"""Tests the correct computation of util.normalize_embeddings"""
embedding_size = 100
a = torch.tensor(np.random.randn(50, embedding_size))
a_norm = normalize_embeddings(a)
for embedding in a_norm:
assert len(embedding) == embedding_size
emb_norm = torch.norm(embedding)
assert abs(emb_norm.item() - 1) < 0.0001