🐛 [Bug] shape tensor is a list instead of integer

[zewenli98]

Bug Description

TensorRT/py/torch_tensorrt/dynamo/utils.py

Lines 135 to 148 in ee0ce96

	def get_torch_tensor(
	input: Input,
	device: torch.device,
	mode: str = "",
	) -> Union[int, torch.Tensor]:
	if input.is_shape_tensor:
	# TODO: All the shape tensors we've encountered so far are plain integers.
	# Validate this assumption on more models.
	return input.shape["opt_shape"][0]
	if len(mode) > 0:
	return input.example_tensor(mode).to(device)
	else:
	return input.torch_tensor.to(device)

Line 141 mentioned all the shape tensors encountered so far are plain integers, but aten::full() requires a list:

TensorRT/tests/py/dynamo/conversion/test_full_aten.py

Lines 29 to 54 in ee0ce96

	@parameterized.expand(
	[
	((1,), (3,), (4,), [3], 11),
	((3, 5), (3, 7), (3, 10), [3, 7], False),
	((1, 5), (3, 7), (4, 10), [3, 7], True),
	((1, 5, 3), (3, 7, 3), (4, 10, 4), [3, 7, 3], 0.11),
	]
	)
	def test_full_dynamic(self, min_shape, opt_shape, max_shape, data, fill_value):
	class full(nn.Module):
	def forward(self, shape):
	return torch.ops.aten.full.default(shape, fill_value)
	inputs = [
	torch_tensorrt.Input(
	min_shape=min_shape,
	opt_shape=opt_shape,
	max_shape=max_shape,
	dtype=torch.int64,
	torch_tensor=torch.tensor(data, dtype=torch.int64).cuda(),
	is_shape_tensor=True,
	)
	]
	self.run_test_with_dynamic_shape(
	full(), inputs, use_example_tensors=False, check_dtype=False
	)

The current implementation caused the error:

RuntimeError: aten::full() Expected a value of type 'List[int]' for argument 'size' but instead found type 'int'.
Position: 0
Value: 3
Declaration: aten::full(SymInt[] size, Scalar fill_value, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor
 Python error details: TypeError: 'int' object is not iterable