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[test only] testing adding optioanl tensor arg to float8 tensor #2840

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[test only] testing adding optioanl tensor arg to float8 tensor #2840

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8 changes: 8 additions & 0 deletions torchao/quantization/quantize_/workflows/float8/float8_tensor.py
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Original file line number Diff line number Diff line change
Expand Up @@ -95,6 +95,7 @@ class Float8Tensor(TorchAOBaseTensor):

tensor_data_names = ["qdata", "scale"]
tensor_attribute_names = []
optional_tensor_data_names = ["test_only_data"]
optional_tensor_attribute_names = [
"block_size",
"mm_config",
Expand All @@ -103,19 +104,22 @@ class Float8Tensor(TorchAOBaseTensor):
"act_quant_kwargs",
"kernel_preference",
"dtype",
"new_optional_attr",
]

def __new__(
cls,
qdata: torch.Tensor,
scale: torch.Tensor,
test_only_data: Optional[torch.Tensor] = None,
block_size: Optional[List[int]] = None,
mm_config: Optional[Float8MMConfig] = None,
hp_value_lb: Optional[float] = None,
hp_value_ub: Optional[float] = None,
act_quant_kwargs: Optional[QuantizeTensorToFloat8Kwargs] = None,
kernel_preference: KernelPreference = KernelPreference.AUTO,
dtype: Optional[torch.dtype] = None,
new_optional_attr: Optional[int] = None,
):
shape = qdata.shape
kwargs = {}
Expand All @@ -128,22 +132,26 @@ def __init__(
self,
qdata: torch.Tensor,
scale: torch.Tensor,
test_only_data: Optional[torch.Tensor] = None,
block_size: Optional[List[int]] = None,
mm_config: Optional[Float8MMConfig] = None,
hp_value_lb: Optional[float] = None,
hp_value_ub: Optional[float] = None,
act_quant_kwargs: Optional[QuantizeTensorToFloat8Kwargs] = None,
kernel_preference: KernelPreference = KernelPreference.AUTO,
dtype: Optional[torch.dtype] = None,
new_optional_attr: Optional[int] = None,
):
self.qdata = qdata
self.scale = scale
self.test_only_data = test_only_data
self.block_size = block_size
self.mm_config = mm_config
self.hp_value_lb = hp_value_lb
self.hp_value_ub = hp_value_ub
self.act_quant_kwargs = act_quant_kwargs
self.kernel_preference = kernel_preference
self.new_optional_attr = new_optional_attr

def __repr__(self):
return (
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