| |
| |
| """Unit tests for Cohere embed protocol: build_typed_embeddings and its |
| underlying packing helpers, plus Cohere-specific serving helpers.""" |
|
|
| import struct |
|
|
| import numpy as np |
| import pybase64 as base64 |
| import pytest |
|
|
| from vllm.entrypoints.pooling.embed.protocol import ( |
| build_typed_embeddings, |
| ) |
|
|
|
|
| @pytest.fixture |
| def sample_embeddings() -> list[list[float]]: |
| return [ |
| [0.1, -0.2, 0.3, -0.4, 0.5, -0.6, 0.7, -0.8], |
| [-0.05, 0.15, -0.25, 0.35, -0.45, 0.55, -0.65, 0.75], |
| ] |
|
|
|
|
| class TestBuildTypedEmbeddingsFloat: |
| def test_float_passthrough(self, sample_embeddings: list[list[float]]): |
| result = build_typed_embeddings(sample_embeddings, ["float"]) |
| assert result.float == sample_embeddings |
| assert result.binary is None |
|
|
| def test_empty_input(self): |
| result = build_typed_embeddings([], ["float"]) |
| assert result.float == [] |
|
|
|
|
| class TestBuildTypedEmbeddingsBinary: |
| def test_binary_packing(self): |
| |
| |
| embs = [[1.0, -1.0, 1.0, -1.0, 1.0, -1.0, 1.0, -1.0]] |
| result = build_typed_embeddings(embs, ["binary"]) |
| assert result.binary is not None |
| assert result.binary[0] == [42] |
|
|
| def test_ubinary_packing(self): |
| embs = [[1.0, -1.0, 1.0, -1.0, 1.0, -1.0, 1.0, -1.0]] |
| result = build_typed_embeddings(embs, ["ubinary"]) |
| assert result.ubinary is not None |
| assert result.ubinary[0] == [170] |
|
|
| def test_binary_all_positive(self): |
| embs = [[0.1] * 8] |
| result = build_typed_embeddings(embs, ["binary"]) |
| assert result.binary is not None |
| |
| assert result.binary[0] == [127] |
|
|
| def test_binary_all_negative(self): |
| embs = [[-0.1] * 8] |
| result = build_typed_embeddings(embs, ["binary"]) |
| assert result.binary is not None |
| |
| assert result.binary[0] == [-128] |
|
|
| def test_binary_dimension_is_eighth(self, sample_embeddings: list[list[float]]): |
| result = build_typed_embeddings(sample_embeddings, ["binary"]) |
| assert result.binary is not None |
| for orig, packed in zip(sample_embeddings, result.binary): |
| assert len(packed) == len(orig) // 8 |
|
|
| def test_zero_treated_as_positive(self): |
| embs = [[0.0] * 8] |
| result = build_typed_embeddings(embs, ["binary"]) |
| assert result.binary is not None |
| |
| assert result.binary[0] == [127] |
|
|
| def test_non_multiple_of_8_raises(self): |
| embs = [[0.1] * 7] |
| with pytest.raises(ValueError, match="multiple of 8"): |
| build_typed_embeddings(embs, ["binary"]) |
|
|
| def test_ubinary_non_multiple_of_8_raises(self): |
| embs = [[0.1] * 10] |
| with pytest.raises(ValueError, match="multiple of 8"): |
| build_typed_embeddings(embs, ["ubinary"]) |
|
|
|
|
| class TestBuildTypedEmbeddingsBase64: |
| def test_base64_roundtrip(self, sample_embeddings: list[list[float]]): |
| result = build_typed_embeddings(sample_embeddings, ["base64"]) |
| assert result.base64 is not None |
| assert len(result.base64) == 2 |
|
|
| for orig, b64_str in zip(sample_embeddings, result.base64): |
| decoded = base64.b64decode(b64_str) |
| n = len(orig) |
| values = struct.unpack(f"<{n}f", decoded) |
| np.testing.assert_allclose(orig, values, rtol=1e-5) |
|
|
| def test_base64_byte_length(self): |
| embs = [[0.1, 0.2, 0.3]] |
| result = build_typed_embeddings(embs, ["base64"]) |
| assert result.base64 is not None |
| raw = base64.b64decode(result.base64[0]) |
| assert len(raw) == 3 * 4 |
|
|
|
|
| class TestBuildTypedEmbeddingsMultiple: |
| def test_all_types_at_once(self, sample_embeddings: list[list[float]]): |
| result = build_typed_embeddings( |
| sample_embeddings, |
| ["float", "binary", "ubinary", "base64"], |
| ) |
| assert result.float is not None |
| assert result.binary is not None |
| assert result.ubinary is not None |
| assert result.base64 is not None |
|
|
| def test_subset_types(self, sample_embeddings: list[list[float]]): |
| result = build_typed_embeddings(sample_embeddings, ["float", "binary"]) |
| assert result.float is not None |
| assert result.binary is not None |
| assert result.ubinary is None |
| assert result.base64 is None |
|
|
| def test_unknown_type_ignored(self, sample_embeddings: list[list[float]]): |
| result = build_typed_embeddings(sample_embeddings, ["float", "unknown_type"]) |
| assert result.float is not None |
|
|