(create_func, shape, dense_dim, select_dim, rang)
| 488 | @pytest.mark.parametrize("select_dim", [0, 1]) |
| 489 | @pytest.mark.parametrize("rang", [slice(0, 2), slice(1, 3)]) |
| 490 | def test_range_select(create_func, shape, dense_dim, select_dim, rang): |
| 491 | ctx = F.ctx() |
| 492 | A = create_func(shape, 20, ctx, dense_dim) |
| 493 | A_select = A.range_select(select_dim, rang) |
| 494 | |
| 495 | dense = sparse_matrix_to_dense(A) |
| 496 | if select_dim == 0: |
| 497 | dense_select = dense[rang, :] |
| 498 | else: |
| 499 | dense_select = dense[:, rang] |
| 500 | |
| 501 | A_select_to_dense = sparse_matrix_to_dense(A_select) |
| 502 | |
| 503 | assert A_select_to_dense.shape == dense_select.shape |
| 504 | assert torch.allclose(A_select_to_dense, dense_select) |
| 505 | |
| 506 | |
| 507 | @pytest.mark.parametrize( |
nothing calls this directly
no test coverage detected