decagon-pytorch/tests/triacontagon/test_loop.py

from triacontagon.loop import _merge_pos_neg_batches
from triacontagon.model import TrainingBatch
import torch
import pytest


def test_merge_pos_neg_batches_01():
    b_1 = TrainingBatch(0, 0, 0, torch.tensor([
        [0, 1],
        [2, 3],
        [4, 5],
        [5, 6]
    ]), torch.ones(4))
    b_2 = TrainingBatch(0, 0, 0, torch.tensor([
        [1, 6],
        [3, 5],
        [5, 2],
        [4, 1]
    ]), torch.zeros(4))
    b = _merge_pos_neg_batches(b_1, b_2)

    assert b.vertex_type_row == 0
    assert b.vertex_type_column == 0
    assert b.relation_type_index == 0
    assert torch.all(b.edges == torch.tensor([
        [0, 1],
        [2, 3],
        [4, 5],
        [5, 6],
        [1, 6],
        [3, 5],
        [5, 2],
        [4, 1]
    ]))
    assert torch.all(b.target_values == \
        torch.cat([ torch.ones(4), torch.zeros(4) ]))


def test_merge_pos_neg_batches_02():
    b_1 = TrainingBatch(0, 1, 0, torch.tensor([
        [0, 1],
        [2, 3],
        [4, 5],
        [5, 6]
    ]), torch.ones(4))
    b_2 = TrainingBatch(0, 0, 0, torch.tensor([
        [1, 6],
        [3, 5],
        [5, 2],
        [4, 1]
    ]), torch.zeros(4))
    print(b_1)
    with pytest.raises(AssertionError):
        _ = _merge_pos_neg_batches(b_1, b_2)

    b_1.vertex_type_row, b_1.vertex_type_column = \
        b_1.vertex_type_column, b_1.vertex_type_row
    print(b_1)
    with pytest.raises(AssertionError):
        _ = _merge_pos_neg_batches(b_1, b_2)

    b_1.vertex_type_row, b_1.relation_type_index = \
        b_1.relation_type_index, b_1.vertex_type_row
    print(b_1)
    with pytest.raises(AssertionError):
        _ = _merge_pos_neg_batches(b_1, b_2)