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| import torch | |
| from memory_native import C_DEFAULT, decode_state, encode_state | |
| def test_roundtrip_all_states(): | |
| for C in (8, 11): | |
| ts, cs = [], [] | |
| for t in (-1, 0, 1): | |
| for c in range(-(C - 1), C): | |
| ts.append(t) | |
| cs.append(c) | |
| t = torch.tensor(ts, dtype=torch.int16) | |
| c = torch.tensor(cs, dtype=torch.int16) | |
| state = encode_state(t, c, C) | |
| assert state.dtype == torch.uint8 | |
| assert int(state.max()) < 3 * (2 * C - 1) | |
| t2, c2 = decode_state(state, C) | |
| assert torch.equal(t2.to(torch.int16), t) | |
| assert torch.equal(c2.to(torch.int16), c) | |
| def test_default_C_fits_byte(): | |
| assert 3 * (2 * C_DEFAULT - 1) <= 256 | |