feat: add DeepGEMM build warning (#5176)

Co-authored-by: grimoire <streetyao@live.com>

python/sglang/srt/layers/quantization/fp8_kernel.py

@@ -16,6 +16,7 @@ import functools
 import json
 import logging
 import os
+from contextlib import contextmanager
 from typing import Any, Dict, List, Optional, Tuple
 
 import torch
@@ -59,7 +60,10 @@ if supports_custom_op():
         Bs: torch.Tensor,
         C: torch.Tensor,
     ) -> None:
-        deep_gemm.gemm_fp8_fp8_bf16_nt((A, As), (B, Bs), C)
+        M, K = A.shape
+        N, _ = B.shape
+        with _log_jit_build(M, N, K):
+            deep_gemm.gemm_fp8_fp8_bf16_nt((A, As), (B, Bs), C)
 
     def deep_gemm_fp8_fp8_bf16_nt_fake(
         A: torch.Tensor,
@@ -708,6 +712,25 @@ def get_w8a8_block_fp8_configs(
     return None
 
 
+@contextmanager
+def _log_jit_build(M: int, N: int, K: int):
+    from deep_gemm.jit.runtime import RuntimeCache
+
+    origin_func = RuntimeCache.__getitem__
+
+    def __patched_func(self, *args, **kwargs):
+        ret = origin_func(self, *args, **kwargs)
+        if ret is None:
+            logger.warning(
+                f"DeepGEMM JIT code generation <gemm_fp8_fp8_bf16_nt>: M={M}, N={N}, K={K}. Please wait."
+            )
+        return ret
+
+    RuntimeCache.__getitem__ = __patched_func
+    yield
+    RuntimeCache.__getitem__ = origin_func
+
+
 def w8a8_block_fp8_matmul(
     A: torch.Tensor,
     B: torch.Tensor,
@@ -782,7 +805,8 @@ def w8a8_block_fp8_matmul(
         if supports_custom_op():
             torch.ops.sglang.deep_gemm_fp8_fp8_bf16_nt(A, As, B, Bs, C)
         else:
-            deep_gemm.gemm_fp8_fp8_bf16_nt((A, As), (B, Bs), C)
+            with _log_jit_build(M, N, K):
+                deep_gemm.gemm_fp8_fp8_bf16_nt((A, As), (B, Bs), C)
     else:
         kernel = (
             _w8a8_block_fp8_matmul_unrolledx4