Module improvements: Core modules (01-08)

- Update tensor module notebook
- Enhance activations module
- Expand layers module functionality
- Improve autograd implementation
- Add optimizers enhancements
- Update training module
- Refine dataloader notebook

modules/06_optimizers/optimizers.py

@@ -445,6 +445,75 @@ class SGD(Optimizer):
         self.momentum_buffers = [None for _ in self.params]
         ### END SOLUTION
 
+    def has_momentum(self) -> bool:
+        """
+        Check if this optimizer uses momentum.
+
+        This explicit API method replaces the need for hasattr() checks
+        in checkpointing code (Module 07).
+
+        Returns:
+            bool: True if momentum is enabled (momentum > 0), False otherwise
+
+        Example:
+            >>> optimizer = SGD(params, lr=0.01, momentum=0.9)
+            >>> optimizer.has_momentum()
+            True
+        """
+        return self.momentum > 0
+
+    def get_momentum_state(self) -> Optional[List]:
+        """
+        Get momentum buffers for checkpointing.
+
+        This explicit API method provides safe access to momentum buffers
+        without using hasattr(), making the API contract clear.
+
+        Returns:
+            Optional[List]: List of momentum buffers if momentum is enabled,
+                          None otherwise
+
+        Example:
+            >>> optimizer = SGD(params, lr=0.01, momentum=0.9)
+            >>> optimizer.step()  # Initialize buffers
+            >>> state = optimizer.get_momentum_state()
+            >>> # Later: optimizer.set_momentum_state(state)
+        """
+        if not self.has_momentum():
+            return None
+        return [buf.copy() if buf is not None else None
+                for buf in self.momentum_buffers]
+
+    def set_momentum_state(self, state: Optional[List]) -> None:
+        """
+        Restore momentum buffers from checkpointing.
+
+        This explicit API method provides safe restoration of momentum state
+        without using hasattr().
+
+        Args:
+            state: List of momentum buffers or None
+
+        Example:
+            >>> optimizer = SGD(params, lr=0.01, momentum=0.9)
+            >>> state = optimizer.get_momentum_state()
+            >>> # Training interruption...
+            >>> new_optimizer = SGD(params, lr=0.01, momentum=0.9)
+            >>> new_optimizer.set_momentum_state(state)
+        """
+        if state is None or not self.has_momentum():
+            return
+
+        if len(state) != len(self.momentum_buffers):
+            raise ValueError(
+                f"State length {len(state)} doesn't match "
+                f"optimizer parameters {len(self.momentum_buffers)}"
+            )
+
+        for i, buf in enumerate(state):
+            if buf is not None:
+                self.momentum_buffers[i] = buf.copy()
+
     def step(self):
         """
         Perform SGD update step with momentum.