[FEATURE] Add transforms

prototorch/core/__init__.py

@@ -7,3 +7,4 @@ from .initializers import *
 from .losses import *
 from .pooling import *
 from .similarities import *
+from .transforms import *

prototorch/core/initializers.py

@@ -313,7 +313,7 @@ class AbstractReasoningsInitializer(ABC):
     @abstractmethod
     def generate(self, distribution: Union[dict, list, tuple]):
         ...
-        return generate_end_hook(...)
+        return self.generate_end_hook(...)
 
 
 class LiteralReasoningsInitializer(AbstractReasoningsInitializer):
@@ -380,6 +380,51 @@ class PurePositiveReasoningsInitializer(AbstractReasoningsInitializer):
         return reasonings
 
 
+# Transforms
+class AbstractTransformInitializer(ABC):
+    """Abstract class for all transform initializers."""
+    ...
+
+
+class AbstractLinearTransformInitializer(AbstractTransformInitializer):
+    """Abstract class for all linear transform initializers."""
+    def __init__(self, out_dim_first: bool = False):
+        self.out_dim_first = out_dim_first
+
+    def generate_end_hook(self, weights):
+        if self.out_dim_first:
+            weights = weights.permute(1, 0)
+        return weights
+
+    @abstractmethod
+    def generate(self, in_dim: int, out_dim: int):
+        ...
+        return self.generate_end_hook(...)
+
+
+class ZerosLinearTransformInitializer(AbstractLinearTransformInitializer):
+    """Initialize a matrix with zeros."""
+    def generate(self, in_dim: int, out_dim: int):
+        weights = torch.zeros(in_dim, out_dim)
+        return self.generate_end_hook(weights)
+
+
+class OnesLinearTransformInitializer(AbstractLinearTransformInitializer):
+    """Initialize a matrix with ones."""
+    def generate(self, in_dim: int, out_dim: int):
+        weights = torch.ones(in_dim, out_dim)
+        return self.generate_end_hook(weights)
+
+
+class EyeTransformInitializer(AbstractLinearTransformInitializer):
+    """Initialize a matrix with the largest possible identity matrix."""
+    def generate(self, in_dim: int, out_dim: int):
+        weights = torch.zeros(in_dim, out_dim)
+        I = torch.eye(min(in_dim, out_dim))
+        weights[:I.shape[0], :I.shape[1]] = I
+        return self.generate_end_hook(weights)
+
+
 # Aliases - Components
 CACI = ClassAwareCompInitializer
 DACI = DataAwareCompInitializer
@@ -406,3 +451,8 @@ ORI = OnesReasoningsInitializer
 PPRI = PurePositiveReasoningsInitializer
 RRI = RandomReasoningsInitializer
 ZRI = ZerosReasoningsInitializer
+
+# Aliases - Transforms
+Eye = EyeTransformInitializer
+OLTI = OnesLinearTransformInitializer
+ZLTI = ZerosLinearTransformInitializer