def test_binary_ew_ops(benchmark, size, dtype, op):
np_a = np.array(np.random.uniform(1, 127, size),
dtype=to_numpy_dtype(dtype))
np_b = np.array(np.random.uniform(1, 127, size),
dtype=to_numpy_dtype(dtype))
a = o3c.Tensor(np_a, dtype=dtype, device=o3c.Device("CPU:0"))
b = o3c.Tensor(np_b, dtype=dtype, device=o3c.Device("CPU:0"))
benchmark(op, a, b)
def test_knn_index():
dtype = o3c.Dtype.Float64
device = o3c.Device("CPU:0")
t = o3c.Tensor.zeros((10, 3), dtype, device=device)
nns = o3c.nns.NearestNeighborSearch(t)
assert nns.knn_index()
assert nns.multi_radius_index()
assert nns.fixed_radius_index()
assert nns.hybrid_index()
def test_registration_result_constructor(device):
dtype = o3c.Dtype.Float64
# Constructor.
registration_result = o3d.t.pipelines.registration.RegistrationResult()
# Checking default values.
assert registration_result.inlier_rmse == 0.0
assert registration_result.fitness == 0.0
assert registration_result.transformation.allclose(
o3c.Tensor.eye(4, dtype, o3c.Device("CPU:0")))
def test_device():
device = o3c.Device()
assert device.get_type() == o3c.Device.DeviceType.CPU
assert device.get_id() == 0
device = o3c.Device("CUDA", 1)
assert device.get_type() == o3c.Device.DeviceType.CUDA
assert device.get_id() == 1
device = o3c.Device("CUDA:2")
assert device.get_type() == o3c.Device.DeviceType.CUDA
assert device.get_id() == 2
assert o3c.Device("CUDA", 1) == o3c.Device("CUDA:1")
assert o3c.Device("CUDA", 1) != o3c.Device("CUDA:0")
assert o3c.Device("CUDA", 1).__str__() == "CUDA:1"
def test_fixed_radius_search():
dtype = o3c.Dtype.Float64
device = o3c.Device("CPU:0")
dataset_points = o3c.Tensor(
[[0.0, 0.0, 0.0], [0.0, 0.0, 0.1], [0.0, 0.0, 0.2], [0.0, 0.1, 0.0],
[0.0, 0.1, 0.1], [0.0, 0.1, 0.2], [0.0, 0.2, 0.0], [0.0, 0.2, 0.1],
[0.0, 0.2, 0.2], [0.1, 0.0, 0.0]],
dtype=dtype,
device=device)
nns = o3c.nns.NearestNeighborSearch(dataset_points)
nns.fixed_radius_index()
# Single query point.
query_points = o3c.Tensor([[0.064705, 0.043921, 0.087843]],
dtype=dtype,
device=device)
indices, distances, num_neighbors = nns.fixed_radius_search(
query_points, 0.1)
np.testing.assert_equal(indices.cpu().numpy(),
np.array([1, 4], dtype=np.int64))
np.testing.assert_allclose(distances.cpu().numpy(),
np.array([0.00626358, 0.00747938],
dtype=np.float64),
rtol=1e-5,
atol=0)
np.testing.assert_equal(num_neighbors.cpu().numpy(),
np.array([2], dtype=np.int64))
# Multiple query points.
query_points = o3c.Tensor(
[[0.064705, 0.043921, 0.087843], [0.064705, 0.043921, 0.087843]],
dtype=dtype,
device=device)
indices, distances, num_neighbors = nns.fixed_radius_search(
query_points, 0.1)
np.testing.assert_equal(indices.cpu().numpy(),
np.array([1, 4, 1, 4], dtype=np.int64))
np.testing.assert_allclose(
distances.cpu().numpy(),
np.array([0.00626358, 0.00747938, 0.00626358, 0.00747938],
dtype=np.float64),
rtol=1e-5,
atol=0)
np.testing.assert_equal(num_neighbors.cpu().numpy(),
np.array([2, 2], dtype=np.int64))
def _on_start(self):
max_points = self.est_point_count_slider.int_value
pcd_placeholder = o3d.t.geometry.PointCloud(
o3c.Tensor(np.zeros((max_points, 3), dtype=np.float32)))
pcd_placeholder.point['colors'] = o3c.Tensor(
np.zeros((max_points, 3), dtype=np.float32))
mat = rendering.MaterialRecord()
mat.shader = 'defaultUnlit'
mat.sRGB_color = True
self.widget3d.scene.scene.add_geometry('points', pcd_placeholder, mat)
self.model = o3d.t.pipelines.slam.Model(
self.voxel_size_slider.double_value, 16,
self.est_block_count_slider.int_value, o3c.Tensor(np.eye(4)),
o3c.Device(self.config.device))
self.is_started = True
set_enabled(self.fixed_prop_grid, False)
set_enabled(self.adjustable_prop_grid, True)
def list_devices():
devices = [o3c.Device("CPU:0")]
if o3c.cuda.is_available():
devices.append(o3c.Device("CUDA:0"))
return devices
def test_float_unary_ew_ops(benchmark, size, dtype, op):
# Set upper bound to 88 to avoid overflow for exp() op.
np_a = np.array(np.random.uniform(1, 88, size),
dtype=to_numpy_dtype(dtype))
a = o3c.Tensor(np_a, dtype=dtype, device=o3c.Device("CPU:0"))
benchmark(op, a)