feat: wire up paged decode CUDA kernel to Python extension

- Add attn_paged_decode wrapper in ops.py with gather fallback
- Register kernel in loader.py and export from __init__.py
- Extract test_utils.cuh shared by all attention unit tests
- Rename attn_paged_vs_contiguous.cu to attn_paged_decode_test.cu
- Refactor decode/prefill tests to use common bf16 helpers and cpu ref
- Fix k_cache dim check in attn_paged_decode.cu

astrai/extension/__init__.py

@@ -3,16 +3,18 @@
 Public API:
     - ``attn_decode`` — single-query decode attention
     - ``attn_prefill`` — multi-query prefill attention
+    - ``attn_paged_decode`` — paged decode attention (direct page-table access)
 
 Each wrapper dispatches to its compiled CUDA kernel (``astrai.extension.attn_*``)
 when available, otherwise falls back to ``torch.nn.functional.scaled_dot_product_attention``.
 """
 
 from astrai.extension.loader import KERNEL_NAMES, is_available
-from astrai.extension.ops import attn_decode, attn_prefill
+from astrai.extension.ops import attn_decode, attn_paged_decode, attn_prefill
 
 __all__ = [
     "attn_decode",
+    "attn_paged_decode",
     "attn_prefill",
     "is_available",
     "KERNEL_NAMES",