Fixes in helion puzzles

docs/helion_puzzles.rst

@@ -433,7 +433,7 @@ A scalar version of FlashAttention.
                 scores = q_tile[:, None] * k_tile[None, :]
 
                 # Find max for numerical stability
-                batch_max = torch.max(scores, dim=1)[0]
+                batch_max = torch.amax(scores, dim=1)
                 new_max = torch.maximum(max_val, batch_max)
 
                 # Scale old accumulations
@@ -468,7 +468,7 @@ A batched 2D convolution.
 .. code-block:: python
 
     def conv2d_spec(x: Float32[Tensor, "4 8 8"], k: Float32[Tensor, "4 4"]) -> Float32[Tensor, "4 8 8"]:
-        z = torch.zeros(4, 8, 8)
+        z = torch.zeros(4, 8, 8, device=x.device)
         x = torch.nn.functional.pad(x, (0, 4, 0, 4, 0, 0), value=0.0)
         for i in range(8):
             for j in range(8):
@@ -495,7 +495,7 @@ A batched 2D convolution.
                     # Extract the patch
                     patch = x_padded[tile_batch, i:i+kh, j:j+kw]
                     # Apply the kernel
-                    out[tile_batch, i, j] = (k[tile_batch] * patch).sum([1, 2])
+                    out[tile_batch, i, j] = (k[tile_batch,:,:] * patch).sum([1, 2])
 
         return out