def test_packed_fail4(self, packed_tensor, total_numel, last_dim, dtype,
wrong_device):
with pytest.raises(TypeError,
match='tensor device is cpu, should be cuda'):
testing.check_packed_tensor(packed_tensor, total_numel, last_dim,
dtype, wrong_device)
assert not testing.check_packed_tensor(packed_tensor, total_numel,
last_dim,
dtype, wrong_device, throw=False)
def test_packed_fail3(self, packed_tensor, total_numel, last_dim,
wrong_dtype, device):
with pytest.raises(TypeError,
match='tensor dtype is torch.float32, should be torch.int64'):
testing.check_packed_tensor(packed_tensor, total_numel, last_dim,
wrong_dtype, device)
assert not testing.check_packed_tensor(packed_tensor, total_numel,
last_dim,
wrong_dtype, device, throw=False)
def test_packed_fail2(self, packed_tensor, total_numel, wrong_last_dim,
dtype, device):
with pytest.raises(ValueError,
match='tensor last_dim is 2, should be 3'):
testing.check_packed_tensor(packed_tensor, total_numel,
wrong_last_dim, dtype, device)
assert not testing.check_packed_tensor(packed_tensor, total_numel,
wrong_last_dim,
dtype, device, throw=False)
def test_packed_fail1(self, packed_tensor, wrong_total_numel, last_dim,
dtype, device):
with pytest.raises(ValueError,
match='tensor total number of elements is 5, should be 6'):
testing.check_packed_tensor(packed_tensor, wrong_total_numel,
last_dim, dtype, device)
assert not testing.check_packed_tensor(packed_tensor, wrong_total_numel,
last_dim,
dtype, device, throw=False)
def test_list_to_packed_to_list(self, tensor_list, shape_per_tensor,
first_idx,
last_dim, dtype, device):
packed_tensor, output_shape_per_tensor = batch.list_to_packed(
tensor_list)
assert torch.equal(output_shape_per_tensor, shape_per_tensor)
check_packed_tensor(packed_tensor, total_numel=first_idx[-1],
last_dim=last_dim,
dtype=dtype, device=device)
for i, tensor in enumerate(tensor_list):
assert torch.equal(packed_tensor[first_idx[i]:first_idx[i + 1]],
tensor.reshape(-1, last_dim))
output_tensor_list = batch.packed_to_list(packed_tensor,
shape_per_tensor, first_idx)
for output_tensor, expected_tensor in zip(output_tensor_list,
tensor_list):
assert torch.equal(output_tensor, expected_tensor)
def test_packed_default_success(self, packed_tensor):
assert testing.check_packed_tensor(packed_tensor)
def test_packed_success(self, packed_tensor, total_numel, last_dim, dtype,
device):
assert testing.check_packed_tensor(packed_tensor, total_numel,
last_dim, dtype, device)
