def test_multivalue(device):
capacity = 10
hashmap = o3c.HashMap(capacity, o3c.int64, (3), (o3c.int64, o3c.float64),
((1), (1)), device)
keys = o3c.Tensor([[1, 2, 3], [2, 3, 4], [3, 4, 5]],
dtype=o3c.int64,
device=device)
values_i64 = o3c.Tensor([1, 2, 3], dtype=o3c.int64, device=device)
values_f64 = o3c.Tensor([400.0, 500.0, 600.0],
dtype=o3c.float64,
device=device)
buf_indices, masks = hashmap.insert(keys, [values_i64, values_f64])
assert masks.to(o3c.int64).sum() == 3
valid_indices = buf_indices[masks].to(o3c.int64)
valid_keys = hashmap.key_tensor()[valid_indices, :]
valid_values_i64 = hashmap.value_tensor(0)[valid_indices]
valid_values_f64 = hashmap.value_tensor(1)[valid_indices]
np.testing.assert_equal(
valid_keys.cpu().numpy().flatten(),
np.array([[1, 2, 3], [2, 3, 4], [3, 4, 5]]).flatten())
np.testing.assert_equal(valid_values_i64.cpu().numpy().flatten(),
np.array([1, 2, 3]))
np.testing.assert_allclose(valid_values_f64.cpu().numpy().flatten(),
np.array([400.0, 500.0, 600.0]))
keys = o3c.Tensor([[1, 2, 3], [4, 5, 6]], dtype=o3c.int64, device=device)
masks = hashmap.erase(keys)
np.testing.assert_equal(masks.cpu().numpy().flatten(),
np.array([True, False]))
def test_complex_shape(device):
capacity = 10
hashmap = o3c.HashMap(capacity, o3c.int64, [3], o3c.int64, [1], device)
keys = o3c.Tensor([[1, 2, 3], [2, 3, 4], [3, 4, 5]],
dtype=o3c.int64,
device=device)
values = o3c.Tensor([1, 2, 3], dtype=o3c.int64, device=device)
buf_indices, masks = hashmap.insert(keys, values)
assert masks.to(o3c.int64).sum() == 3
valid_indices = buf_indices[masks].to(o3c.int64)
valid_keys = hashmap.key_tensor()[valid_indices, :]
valid_values = hashmap.value_tensor()[valid_indices]
np.testing.assert_equal(
valid_keys.cpu().numpy().flatten(),
np.array([[1, 2, 3], [2, 3, 4], [3, 4, 5]]).flatten())
np.testing.assert_equal(valid_values.cpu().numpy().flatten(),
np.array([1, 2, 3]))
keys = o3c.Tensor([[1, 2, 3], [4, 5, 6]], dtype=o3c.int64, device=device)
masks = hashmap.erase(keys)
np.testing.assert_equal(masks.cpu().numpy().flatten(),
np.array([True, False]))
def test_erase(device):
capacity = 10
hashmap = o3c.HashMap(capacity, o3c.int64, [1], o3c.int64, [1], device)
keys = o3c.Tensor([100, 300, 500, 700, 900],
dtype=o3c.int64,
device=device)
values = o3c.Tensor([1, 3, 5, 7, 9], dtype=o3c.int64, device=device)
hashmap.insert(keys, values)
keys = o3c.Tensor([100, 200, 500], dtype=o3c.int64, device=device)
masks = hashmap.erase(keys)
np.testing.assert_equal(masks.cpu().numpy(), np.array([True, False, True]))
assert hashmap.size() == 3
active_buf_indices = hashmap.active_buf_indices()
active_indices = active_buf_indices.to(o3c.int64)
active_keys = hashmap.key_tensor()[active_indices]
active_values = hashmap.value_tensor()[active_indices]
active_keys_np = active_keys.cpu().numpy().flatten()
active_values_np = active_values.cpu().numpy().flatten()
sorted_i = np.argsort(active_keys_np)
np.testing.assert_equal(active_keys_np[sorted_i], np.array([300, 700,
900]))
np.testing.assert_equal(active_values_np[sorted_i], np.array([3, 7, 9]))
def test_activate(device):
capacity = 10
hashmap = o3c.HashMap(capacity, o3c.int64, [1], o3c.int64, [1], device)
keys = o3c.Tensor([100, 300, 500, 700, 900, 900],
dtype=o3c.int64,
device=device)
buf_indices, masks = hashmap.activate(keys)
assert masks.to(o3c.int64).sum() == 5
valid_indices = buf_indices[masks].to(o3c.int64)
valid_keys = hashmap.key_tensor()[valid_indices]
np.testing.assert_equal(np.sort(valid_keys.cpu().numpy().flatten()),
np.array([100, 300, 500, 700, 900]))
def test_insertion(device):
capacity = 10
hashmap = o3c.HashMap(capacity, o3c.int64, [1], o3c.int64, [1], device)
keys = o3c.Tensor([100, 300, 500, 700, 900, 900],
dtype=o3c.int64,
device=device)
values = o3c.Tensor([1, 3, 5, 7, 9, 9], dtype=o3c.int64, device=device)
buf_indices, masks = hashmap.insert(keys, values)
assert masks.to(o3c.int64).sum() == 5
valid_indices = buf_indices[masks].to(o3c.int64)
valid_keys = hashmap.key_tensor()[valid_indices]
valid_values = hashmap.value_tensor()[valid_indices]
np.testing.assert_equal(valid_keys.cpu().numpy(),
valid_values.cpu().numpy() * 100)
def test_find(device):
capacity = 10
hashmap = o3c.HashMap(capacity, o3c.int64, [1], o3c.int64, [1], device)
keys = o3c.Tensor([100, 300, 500, 700, 900],
dtype=o3c.int64,
device=device)
values = o3c.Tensor([1, 3, 5, 7, 9], dtype=o3c.int64, device=device)
hashmap.insert(keys, values)
keys = o3c.Tensor([100, 200, 500], dtype=o3c.int64, device=device)
buf_indices, masks = hashmap.find(keys)
np.testing.assert_equal(masks.cpu().numpy(), np.array([True, False, True]))
valid_indices = buf_indices[masks].to(o3c.int64)
valid_keys = hashmap.key_tensor()[valid_indices]
valid_values = hashmap.value_tensor()[valid_indices]
assert valid_keys.shape[0] == 2
np.testing.assert_equal(valid_keys.cpu().numpy().flatten(),
np.array([100, 500]))
np.testing.assert_equal(valid_values.cpu().numpy().flatten(),
np.array([1, 5]))
def test_creation(device):
hashmap = o3c.HashMap(10, o3c.int64, [1], o3c.int64, [1], device)
assert hashmap.size() == 0