use random seeds, rename matrix multiply

Signed-off-by: Kyle Sayers <kylesayrs@gmail.com>

Author: kylesayrs

src/compressed_tensors/transform/factory/base.py

@@ -82,8 +82,8 @@ def apply_to_model(self, model: Module):
         :param model: module to apply transforms to
         """
         for arg in self.scheme.apply:
-            for path, module in list(model.named_modules()):
-                if is_target(path, module, arg.targets, arg.ignore):
+            for name, module in list(model.named_modules()):
+                if is_target(name, module, arg.targets, arg.ignore):
                     self._apply_to_module(module, arg)
 
     def _apply_to_module(self, module: Module, args: TransformArgs):

src/compressed_tensors/transform/factory/hadamard.py

@@ -40,6 +40,7 @@ class HadamardFactory(TransformFactory):
 
     def __init__(self, name: str, scheme: TransformScheme, seed: int = 42):
         super().__init__(name, scheme, seed)
+        self.generator = torch.Generator(device="cpu").manual_seed(seed)
         self.weights = ParameterizedDefaultDict(self._create_weight)
 
     def create_transform(self, module: Module, args: TransformArgs):
@@ -59,7 +60,7 @@ def create_transform(self, module: Module, args: TransformArgs):
         return HadamardTransform(weight, args)
 
     def _create_weight(self, size: int, dtype: dtype, device: device) -> Parameter:
-        data = deterministic_hadamard_matrix(size)  # TODO: seed=self.seed
+        data = deterministic_hadamard_matrix(size)
         data = data.to(dtype=dtype, device=device)
         return Parameter(data, requires_grad=self.scheme.requires_grad)
 

src/compressed_tensors/transform/factory/matrix_multiply.py

@@ -25,7 +25,7 @@
 from torch.nn import Linear, Module, Parameter
 
 
-@TransformFactory.register("matrix-mul")
+@TransformFactory.register("random-matrix")
 class RandomMatrixFactory(TransformFactory):
     """
     Factory used to apply random matrix transforms to a model

src/compressed_tensors/transform/factory/random_hadamard.py

@@ -29,6 +29,6 @@ class RandomHadamardFactory(HadamardFactory):
     """
 
     def _create_weight(self, size: int, dtype: dtype, device: device) -> Parameter:
-        data = random_hadamard_matrix(size)  # seed
+        data = random_hadamard_matrix(size, self.generator)
         data = data.to(dtype=dtype, device=device)
         return Parameter(data, requires_grad=self.scheme.requires_grad)