feat: add load progress heartbeats to prevent k8s health check kills

The 5-minute gap after safetensors load is GPU weight upload — no
output, k8s marks the pod unhealthy. Now prints a heartbeat every
256 weight loads during the expert loading phase.

Also adds checkpoint-ready and model-ready prints around finalize:
  Checkpoint loaded. Transferring weights to GPU & preparing NVFP4...
  (JIT compile)NVFP4 MoE layers: 50%|██████████░░░░░░░░░░| 31/61
  NVFP4 model ready ✓

vllm/patches/deepseek_v4.py

@@ -222,6 +222,7 @@ class DeepseekV4MegaMoEExperts(nn.Module):
     This replaces the broken C++ CUTLASS kernel (see README.md for the full story).
     """
     _cutedsl_runner: 'CuTeDSLMoERunner | None' = None
+    _weight_load_count: int = 0
 
     # NVFP4 E2M1 lookup table (positive values, sign from bit 3)
     E2M1_LUT = [0.0, 0.5, 1.0, 1.5, 2.0, 3.0, 4.0, 6.0]
@@ -351,6 +352,12 @@ class DeepseekV4MegaMoEExperts(nn.Module):
         shard_id: str,
         expert_id: int,
     ) -> bool:
+        # Heartbeat: print every 256 weight loads so k8s/docker
+        # don't think the pod is dead during GPU upload
+        DeepseekV4MegaMoEExperts._weight_load_count += 1
+        if DeepseekV4MegaMoEExperts._weight_load_count % 256 == 1:
+            print(f"  Loading expert weights... ({DeepseekV4MegaMoEExperts._weight_load_count})", flush=True)
+
         local_expert_id = self._map_global_expert_id(expert_id)
         if local_expert_id == -1:
             return False
@@ -2200,8 +2207,10 @@ class DeepseekV4ForCausalLM(nn.Module):
         # AutoWeightsLoader bypasses this logic and would break NVFP4 loading.
         loaded_params = self.model.load_weights(rest)
         loaded_params.add("lm_head.weight")
+        print("  Checkpoint loaded. Transferring weights to GPU & preparing NVFP4...", flush=True)
         self.model.finalize_mega_moe_weights()
         self.model._convert_nvfp4_post_load()
+        print("  NVFP4 model ready ✓", flush=True)
 
         return loaded_params