perf: replace paged KV cache with contiguous ContiguousCache, decode all groups

- Add KVCache/CacheView abstract base classes in cache.py
- Add ContiguousCache (contiguous per-slot buffer, default) alongside PageCache (paged, renamed from old KVCache)
- Merge make_table_tensor + bind into bind_tasks on KVCache interface
- Remove task_cached/task_record_hashes from base class (PageCache-only)
- Scheduler: decode all position groups instead of just the largest (eliminates 63% group skip rate)
- Scheduler: accept optional cache param for swapping implementations
- Model layer type hints use CacheView base class
- Batch 1-32: 1-7% speedup from eliminating Storage.gather overhead
- All 183 inference tests pass

astrai/model/transformer.py

@@ -5,7 +5,7 @@ import torch.nn as nn
 from torch import Tensor
 
 from astrai.config.model_config import AutoRegressiveLMConfig
-from astrai.inference.core.cache import KvcacheView
+from astrai.inference.core.cache import CacheView
 from astrai.model.automodel import AutoModel
 from astrai.model.components.decoder_block import DecoderBlock
 from astrai.model.components.embedding import Embedding
@@ -112,7 +112,7 @@ class AutoRegressiveLM(AutoModel):
         self,
         input_ids: Tensor,
         input_mask: Optional[Tensor] = None,
-        paged_cache: Optional[KvcacheView] = None,
+        paged_cache: Optional[CacheView] = None,
         position_ids: Optional[Tensor] = None,
     ) -> Dict[str, Tensor]:
         assert input_ids.ndim == 2