Initial K3 snapshot: 0.5B KDA/MLA/MoE train path

Standalone tree split from LLMRL/projects/kda. Includes Triton dt_bias
backward fix, train_k3 --preset 0.5b, SFT, Docker runtime, and tests.

kda/ops/triton/chunk_fwd.py

@@ -0,0 +1,37 @@
+"""Vendored FLA chunk KDA forward, returning ``(o, ht)`` like the public op."""
+
+from __future__ import annotations
+
+import torch
+
+from kda._fla.ops.kda.chunk import chunk_kda
+from kda._fla.ops.kda.chunk_fwd import chunk_kda_fwd as fla_chunk_kda_fwd
+
+__all__ = ["chunk_kda_fwd", "fla_chunk_kda_fwd"]
+
+
+def chunk_kda_fwd(
+    q: torch.Tensor,
+    k: torch.Tensor,
+    v: torch.Tensor,
+    g: torch.Tensor,
+    beta: torch.Tensor,
+    scale: float | None = None,
+    initial_state: torch.Tensor | None = None,
+    output_final_state: bool = False,
+    chunk_size: int = 64,
+    **kwargs,
+):
+    """Chunked KDA forward with FLA kernels. Returns ``(o, ht)``."""
+    return chunk_kda(
+        q,
+        k,
+        v,
+        g,
+        beta,
+        scale=scale,
+        initial_state=initial_state,
+        output_final_state=output_final_state,
+        chunk_size=chunk_size,
+        **kwargs,
+    )