qwen3.5-122B-A10B on DGX Spark: vLLM + DFlash + dense-bandwidth stack, one-shot installer

tools/validate_int8_v3.py

@@ -0,0 +1,45 @@
+#!/usr/bin/env python3
+"""Validate patch_int8_lmhead_v3 landed + the helper runs on GPU. Run AFTER the
+patch in the same container."""
+import torch
+
+import vllm.model_executor.layers.logits_processor as lp
+
+print("import OK | helpers:",
+      hasattr(lp, "_spark_int8_gemm"),
+      hasattr(lp, "_spark_int8_lmhead_apply"),
+      hasattr(lp, "_spark_k_int8"))
+src = open(lp.__file__).read()
+print("sentinel in _get_logits:", "DGX_SPARK_INT8_LMHEAD_V3: int8 w8a16" in src)
+
+V, H = 4096, 512
+torch.manual_seed(0)
+W = torch.randn(V, H, device="cuda") * 0.02
+s = (W.abs().amax(1) / 127).clamp(min=1e-12)
+wi = (W / s.unsqueeze(1)).round().clamp(-127, 127).to(torch.int8).contiguous()
+sf = s.to(torch.float16)
+for B in (1, 5, 13):
+    x = torch.randn(B, H, device="cuda", dtype=torch.bfloat16) * 0.1
+    out = lp._spark_int8_gemm(x, wi, sf)
+    ref = x.float() @ (wi.float() * s.unsqueeze(1)).T
+    am = (out.argmax(-1) == ref.argmax(-1)).float().mean().item()
+    print(f"  B={B}: out{tuple(out.shape)} {out.dtype}  argmax={am*100:.0f}%  "
+          f"maxerr={(out - ref).abs().max().item():.4f}")
+
+# Exercise the FULL apply path (print + quantize-once + gemm) with a mock lm_head
+# (vocab > 100k to trigger the int8 path). self is unused -> None.
+print("--- full _spark_int8_lmhead_apply path (mock lm_head, V=131072) ---")
+Vbig = 131072
+
+class _MockLMHead:
+    pass
+
+mh = _MockLMHead()
+mh.weight = (torch.randn(Vbig, H, device="cuda", dtype=torch.float32) * 0.02).to(torch.bfloat16)
+hs = torch.randn(3, H, device="cuda", dtype=torch.bfloat16) * 0.1
+o1 = lp._spark_int8_lmhead_apply(None, mh, hs, None)  # first call: quantizes + prints
+o2 = lp._spark_int8_lmhead_apply(None, mh, hs, None)  # second call: reuses int8
+refb = hs.float() @ mh.weight.float().T
+am = (o2.argmax(-1) == refb.argmax(-1)).float().mean().item()
+print(f"  apply: out{tuple(o2.shape)} {o2.dtype}  argmax_vs_bf16={am*100:.0f}%  "
+      f"int8_ready={getattr(mh, '_spark_int8_ready', None)}  weight_kept={mh.weight.numel() > 0}")