fix(package): Add PyTorch-style __call__ methods to exported modules

Resolved transformer training issues by adding __call__ methods to:
- Embedding, PositionalEncoding, EmbeddingLayer (text.embeddings)
- LayerNorm, MLP, TransformerBlock, GPT (models.transformer)
- MultiHeadAttention (core.attention)

This enables PyTorch-style syntax: model(x) instead of model.forward(x)
All transformer diagnostic tests now pass (5/5 ✓)(https://claude.ai/code)

tinytorch/core/attention.py

@@ -280,6 +280,10 @@ class MultiHeadAttention:
         return output
         ### END SOLUTION
 
+    def __call__(self, x: Tensor, mask: Optional[Tensor] = None) -> Tensor:
+        """Allows the attention layer to be called like a function."""
+        return self.forward(x, mask)
+
     def parameters(self) -> List[Tensor]:
         """
         Return all trainable parameters.