[reland] Refactor TorchAOBaseTensor for better BC (#2793)

[jerryzh168]

Summary:

After this PR, tensors inheriting from TorchAOBaseTensor will have better support BC, that is if they add some optional tensor data attribute or optional non-tensor attribute, we will still have BC without any additional changes.

More Details: The BC story we are looking at is that, after we land some tensor, e.g. Int4Tensor, Float8Tensor, future changes should only add optional Tensor data attributes and optional non-Tensor attributes to the Tensor (other bigger changes will require a version bump, we need to add that too). The current TorchAOBaseTensor doesn’t support this very well.

also see #2840 for a real test that adds both an optional tensor and optional non-tensor attribute to Float8Tensor, and the BC test in https://github.com/pytorch/ao/blob/main/test/integration/test_load_and_run_checkpoint.py that tests Float8Tensor does not fail.

Docs for current TorchAOBaseTensor:

ao/torchao/utils.py

Lines 726 to 731 in e6b38bb

	class variables to define to simplify implmentation of tensor subclasses:
	`tensor_data_names` (List[str]): list of names of all requires tensor_data, order should match
	the `__init__` list of tensor subclass
	`optional_tensor_data_names` (List[str]): it's optional to define this field to have the additional boilerplate functions been implemented for you, but this will be need if there are some optional Tensor attributes, when defined, this will be a list of names of Tensors that can be optional
	`tensor_attribute_names` (List[str]): list of names of non-Tensor attributes,
	order should match the `__init__` list of tensor subclass, following all the `tensor_data_names` arguments and `optional_tensor_data_names`

tensor_data_names (List[str]): list of names of all requires tensor_data, order should match the __init__ list of tensor subclass
optional_tensor_data_names (List[str]): it's optional to define this field to have the additional boilerplate functions been implemented for you, but this will be need if there are some optional Tensor attributes, when defined, this will be a list of names of Tensors that can be optional tensor_attribute_names (List[str]): list of names of non-Tensor attributes, order should match the __init__ list of tensor subclass, following all the tensor_data_names arguments and optional_tensor_data_names

Problems: current optional_tensor_data_names is not truly optional, since it is followed by tensor_attribute_names which contains both required and optional attributes. So if we add a tensor data attribute to Tensor, it will break BC.

Here are a few options:

class Int4Tensor(TorchAOBaseTensor):
    tensor_data_names = ["qdata", "scale", "zero_point"]
    optional_tensor_data_names = ["act_scale"]
    tensor_attribute_names = ["block_size", "shape", "_demo_only_optional_attr"]

    def __init__(self, qdata, scale, zero_point, act_scale=None, block_size=None, shape=None, _demo_only_optional_attr=None):
        ...

   # for BC
   def __setstate__(self, state):
      torch._utils._set_obj_state(self, state)
      if "act_scale" not in self.__dict__:
          self.act_scale = None

class Int4Tensor(TorchAOBaseTensor):
    tensor_data_names = ["qdata", "scale", "zero_point"]
    optional_tensor_data_names = ["act_scale"]
    required_tensor_attribute_names = ["block_size", "shape"]
    optional_tensor_attribute_names = ["_demo_only_optional_attr"]

    def __init__(self, qdata, scale, zero_point, block_size, shape, act_scale=None, _demo_only_optional_attr = None):
        ...

   # for BC
   def __setstate__(self, state):
      torch._utils._set_obj_state(self, state)
      if "act_scale" not in self.__dict__:
          self.act_scale = None

class Int4Tensor(TorchAOBaseTensor):
    tensor_data_names = ["qdata", "scale", "zero_point"]
    tensor_attribute_names = ["block_size", "shape", "_demo_only_optional_attr"]
    optional_tensor_data_names = ["act_scale"]

    def __init__(self, qdata, scale, zero_point, block_size, shape, _demo_only_optional_attr = None, act_scale = None):
        ...

   # for BC
   def __setstate__(self, state):
      torch._utils._set_obj_state(self, state)
      if "act_scale" not in self.__dict__:
          self.act_scale = None

Test Plan:
python test/integration/test_load_and_run_checkpoint.py

Reviewers:

Subscribers:

Tasks:

Tags:

[pytorch-bot]

🔗 Helpful Links

🧪 See artifacts and rendered test results at hud.pytorch.org/pr/pytorch/ao/2855

• 📄 Preview Python docs built from this PR

Note: Links to docs will display an error until the docs builds have been completed.

❌ 1 New Failure, 1 Cancelled Job

As of commit 3df4541 with merge base 27f4d75 ():

NEW FAILURE - The following job has failed:

• Run TorchAO Experimental Tests / test-cpu-ops (macos-14) (gh)
  Process completed with exit code 1.

CANCELLED JOB - The following job was cancelled. Please retry:

• Run TorchAO Experimental Tests / test-cpu-ops (linux.arm64.2xlarge) (gh)
  ##[error]The operation was canceled.

This comment was automatically generated by Dr. CI and updates every 15 minutes.