make seed optional

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

Author: kylesayrs

src/compressed_tensors/transform/factory/base.py

@@ -13,6 +13,7 @@
 # limitations under the License.
 
 from abc import ABC, abstractmethod
+from typing import Optional
 
 import torch
 import torch.nn.utils.parametrize as P
@@ -46,11 +47,12 @@ class TransformFactory(RegistryMixin, ABC):
     :param seed: random seed used to transform weight randomization
     """
 
-    def __init__(self, name: str, scheme: TransformScheme, seed: int = 42):
+    def __init__(self, name: str, scheme: TransformScheme, seed: Optional[int] = None):
         self.name = name
         self.scheme = scheme
-        self.generator = torch.Generator().manual_seed(seed)
-        self.seed = seed
+        self.generator = torch.Generator()
+        if seed is not None:
+            self.generator.manual_seed(seed)
 
     @classmethod
     def from_scheme(cls: type[T], scheme: TransformScheme, **kwargs) -> T:

src/compressed_tensors/transform/factory/hadamard.py

@@ -38,7 +38,7 @@ class HadamardFactory(TransformFactory):
     :param seed: random seed used to transform weight randomization
     """
 
-    def __init__(self, name: str, scheme: TransformScheme, seed: int = 42):
+    def __init__(self, name: str, scheme: TransformScheme, seed: Optional[int] = None):
         super().__init__(name, scheme, seed)
         self.weights = ParameterizedDefaultDict(self._create_weight)
 

src/compressed_tensors/transform/factory/matrix_multiply.py

@@ -12,6 +12,8 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
+from typing import Optional
+
 import torch
 from compressed_tensors.transform import TransformArgs, TransformScheme
 from compressed_tensors.transform.factory.base import TransformBase, TransformFactory
@@ -35,7 +37,7 @@ class RandomMatrixFactory(TransformFactory):
     :param seed: random seed used to transform weight randomization
     """
 
-    def __init__(self, name: str, scheme: TransformScheme, seed: int = 42):
+    def __init__(self, name: str, scheme: TransformScheme, seed: Optional[int] = None):
         super().__init__(name, scheme, seed)
         self.weights = ParameterizedDefaultDict(self._create_weight)
         self.inverses = ParameterizedDefaultDict(self._create_inverse)