merge issues

Signed-off-by: Kyle Sayers <[email protected]>

Author: kylesayrs

src/compressed_tensors/transform/factory/hadamard.py

@@ -86,15 +86,13 @@ def __init__(
         perm: Optional[Parameter],
         scheme: TransformScheme,
         args: TransformArgs,
-        precision: torch.dtype,
         module_type: type[torch.nn.Module],
     ):
         super().__init__()
         self.weight = weight
         self.perm = perm
         self.scheme = scheme
         self.args = args
-        self.precision = precision
         self.module_type = module_type
         self._scale = torch.tensor(weight.size(0), dtype=self.scheme.precision).sqrt()
 

src/compressed_tensors/transform/factory/matrix_multiply.py

@@ -54,13 +54,12 @@ def create_transform(self, module: Module, args: TransformArgs):
         size = get_transform_size(module, args.location, self.scheme.head_dim)
         dtype = self.scheme.precision
         device = get_offloaded_device(module)
-        precision = self.scheme.precision
 
         weight = self.weights[size, dtype, device]
         if args.inverse:
             weight = self.inverses[weight]
 
-        return RandomMatrixTransform(weight, args, precision, type(module))
+        return RandomMatrixTransform(weight, self.scheme, args, type(module))
 
     def _create_weight(self, size: int, dtype: dtype, device: device) -> Parameter:
         # TODO: verify that weight is invertible (has non-zero determinant)
@@ -81,14 +80,12 @@ def __init__(
         weight: Tensor,
         scheme: TransformScheme,
         args: TransformArgs,
-        precision: torch.dtype,
         module_type: type[torch.nn.Module],
     ):
         super().__init__()
         self.weight = weight  # is an inverse if args.inverse
         self.scheme = scheme
         self.args = args
-        self.precision = precision
         self.module_type = module_type
 
     def forward(self, value: Tensor) -> Parameter: