def test_creation(device):
# Shape takes tuple, list or o3d.SizeVector
t = o3d.Tensor.empty((2, 3), o3d.Dtype.Float32, device=device)
assert t.shape == o3d.SizeVector([2, 3])
t = o3d.Tensor.empty([2, 3], o3d.Dtype.Float32, device=device)
assert t.shape == o3d.SizeVector([2, 3])
t = o3d.Tensor.empty(o3d.SizeVector([2, 3]),
o3d.Dtype.Float32,
device=device)
assert t.shape == o3d.SizeVector([2, 3])
# Test zeros and ones
t = o3d.Tensor.zeros((2, 3), o3d.Dtype.Float32, device=device)
np.testing.assert_equal(t.cpu().numpy(), np.zeros((2, 3),
dtype=np.float32))
t = o3d.Tensor.ones((2, 3), o3d.Dtype.Float32, device=device)
np.testing.assert_equal(t.cpu().numpy(), np.ones((2, 3), dtype=np.float32))
# Automatic casting of dtype.
t = o3d.Tensor.full((2, ), False, o3d.Dtype.Float32, device=device)
np.testing.assert_equal(t.cpu().numpy(),
np.full((2, ), False, dtype=np.float32))
t = o3d.Tensor.full((2, ), 3.5, o3d.Dtype.UInt8, device=device)
np.testing.assert_equal(t.cpu().numpy(), np.full((2, ),
3.5,
dtype=np.uint8))
def test_to():
a = o3d.Tensor(np.array([0.1, 1.2, 2.3, 3.4, 4.5, 5.6]).astype(np.float32))
b = a.to(o3d.Dtype.Int32)
np.testing.assert_equal(b.numpy(), np.array([0, 1, 2, 3, 4, 5]))
assert b.shape == o3d.SizeVector([6])
assert b.strides == o3d.SizeVector([1])
assert b.dtype == o3d.Dtype.Int32
assert b.device == a.device
def _reduction_dim_to_size_vector(self, dim):
if dim is None:
return o3d.SizeVector(list(range(self.ndim)))
elif isinstance(dim, int):
return o3d.SizeVector([dim])
elif isinstance(dim, list) or isinstance(dim, tuple):
return o3d.SizeVector(dim)
else:
raise TypeError(
f"dim must be int, list or tuple, but was {type(dim)}.")
def ones(shape, dtype, device=o3d.Device("CPU:0")):
"""
Create a tensor with fill with ones.
Args:
shape (list, tuple, o3d.SizeVector): Shape of the tensor.
dtype (o3d.Dtype): Data type of the tensor.
device (o3d.Device): Device where the tensor is created.
"""
if not isinstance(shape, o3d.SizeVector):
shape = o3d.SizeVector(shape)
return super(Tensor, Tensor).ones(shape, dtype, device)
def full(shape, fill_value, dtype, device=o3d.Device("CPU:0")):
"""
Create a tensor with fill with the specified value.
Args:
shape (list, tuple, o3d.SizeVector): Shape of the tensor.
fill_value (scalar): The value to be filled.
dtype (o3d.Dtype): Data type of the tensor.
device (o3d.Device): Device where the tensor is created.
"""
if not isinstance(shape, o3d.SizeVector):
shape = o3d.SizeVector(shape)
return super(Tensor, Tensor).full(shape, fill_value, dtype, device)
def __init__(self, shape, dtype=None, device=None, size=None):
if isinstance(shape, list) or isinstance(shape, tuple):
shape = o3d.SizeVector(shape)
elif isinstance(shape, o3d.SizeVector):
pass
else:
raise ValueError('shape must be a list, tuple, or o3d.SizeVector')
if dtype is None:
dtype = o3d.Dtype.Float32
if device is None:
device = o3d.Device("CPU:0")
if size is None:
size = 0
super(TensorList, self).__init__(shape, dtype, device, size)
def test_size_vector():
# List
sv = o3d.SizeVector([-1, 2, 3])
assert "{}".format(sv) == "{-1, 2, 3}"
# Tuple
sv = o3d.SizeVector((-1, 2, 3))
assert "{}".format(sv) == "{-1, 2, 3}"
# Numpy 1D array
sv = o3d.SizeVector(np.array([-1, 2, 3]))
assert "{}".format(sv) == "{-1, 2, 3}"
# Empty
sv = o3d.SizeVector()
assert "{}".format(sv) == "{}"
sv = o3d.SizeVector([])
assert "{}".format(sv) == "{}"
sv = o3d.SizeVector(())
assert "{}".format(sv) == "{}"
sv = o3d.SizeVector(np.array([]))
assert "{}".format(sv) == "{}"
# Automatic int casting (not rounding to nearest)
sv = o3d.SizeVector((1.9, 2, 3))
assert "{}".format(sv) == "{1, 2, 3}"
# Automatic casting negative
sv = o3d.SizeVector((-1.5, 2, 3))
assert "{}".format(sv) == "{-1, 2, 3}"
# 2D list exception
with pytest.raises(ValueError):
sv = o3d.SizeVector([[1, 2], [3, 4]])
# 2D Numpy array exception
with pytest.raises(ValueError):
sv = o3d.SizeVector(np.array([[1, 2], [3, 4]]))
# Garbage input
with pytest.raises(ValueError):
sv = o3d.SizeVector(["foo", "bar"])
