apply autotuner fix

中文：应用 AutoTuner non-Tensor 输入保护修复。

Author: jiahanc

benchmarks/single_node/fixed_seq_len/minimaxm3_fp4_b300.sh

@@ -7,7 +7,8 @@
 #
 # At runtime the recipe swaps the image's FlashInfer for the first pinned
 # nightly containing the upstream SM100 low-M MXFP8 split-K kernel
-# (flashinfer-ai/flashinfer#3847).
+# (flashinfer-ai/flashinfer#3847), then backports the AutoTuner non-Tensor guard
+# fix from flashinfer-ai/flashinfer#3918.
 
 source "$(dirname "$0")/../../benchmark_lib.sh"
 
@@ -23,7 +24,7 @@ check_env_vars \
     RANDOM_RANGE_RATIO \
     RESULT_FILENAME
 
-# --- FlashInfer nightly ------------------------------------------------------
+# --- FlashInfer nightly + AutoTuner non-Tensor guard patch ------------------
 FLASHINFER_VERSION=0.6.15.dev20260710
 FLASHINFER_NIGHTLY_TAG=nightly-v0.6.15-20260710
 FLASHINFER_RELEASE_URL="https://github.com/flashinfer-ai/flashinfer/releases/download/${FLASHINFER_NIGHTLY_TAG}"
@@ -36,6 +37,20 @@ python3 -m pip install \
     "${FLASHINFER_RELEASE_URL}/flashinfer_jit_cache-${FLASHINFER_VERSION}+cu130-cp39-abi3-manylinux_2_28_$(uname -m).whl" \
     || { echo "FlashInfer nightly install failed" >&2; exit 1; }
 
+# The pinned nightly predates flashinfer-ai/flashinfer#3918. Apply only its
+# runtime fix; the upstream test change is intentionally not backported.
+FLASHINFER_PATCH="$(dirname "$0")/patches/flashinfer-autotuner-non-tensor-guard.patch"
+if ! command -v patch >/dev/null 2>&1; then
+    apt-get update -y && apt-get install -y --no-install-recommends patch \
+        || { echo "Failed to install patch(1)" >&2; exit 1; }
+fi
+SITE_PACKAGES=$(dirname "$(python3 -c "import importlib.util; print(importlib.util.find_spec('flashinfer').submodule_search_locations[0])")") \
+    || { echo "Could not locate the installed flashinfer package" >&2; exit 1; }
+patch --dry-run -p1 -d "${SITE_PACKAGES}" < "${FLASHINFER_PATCH}" >/dev/null \
+    || { echo "FlashInfer AutoTuner non-Tensor guard patch does not apply" >&2; exit 1; }
+patch -p1 -d "${SITE_PACKAGES}" < "${FLASHINFER_PATCH}" \
+    || { echo "FlashInfer AutoTuner non-Tensor guard patch failed" >&2; exit 1; }
+
 # -----------------------------------------------------------------------------
 
 if [[ -n "${MODEL_PATH:-}" ]]; then

benchmarks/single_node/fixed_seq_len/patches/flashinfer-autotuner-non-tensor-guard.patch

@@ -0,0 +1,38 @@
+diff --git a/flashinfer/autotuner/autotuner.py b/flashinfer/autotuner/autotuner.py
+index 54b90a0..76443ca 100644
+--- a/flashinfer/autotuner/autotuner.py
++++ b/flashinfer/autotuner/autotuner.py
+@@ -2074,14 +2074,19 @@ class AutoTuner:
+     def _prepare_input_tensors_with_batches(
+         self,
+-        inputs: list[torch.Tensor],
++        inputs: list[Any],
+         tuning_config: TuningConfig,
+-    ) -> list[list[torch.Tensor]]:
++    ) -> list[list[Any]]:
+         """Create multiple input copies to flush the L2 cache between profiling iterations."""
+         if not tuning_config.use_cold_l2_cache:
+             return [inputs]
+ 
+-        one_buffer_bytes = sum(input.numel() * input.element_size() for input in inputs)
++        one_buffer_bytes = sum(
++            input.numel() * input.element_size()
++            if isinstance(input, torch.Tensor)
++            else 0
++            for input in inputs
++        )
+         if one_buffer_bytes <= 0:
+             logger.debug(
+                 "[Autotuner] No tensor inputs or zero-sized tensors; falling back to single-batch profiling."
+             )
+@@ -2093,7 +2098,9 @@ class AutoTuner:
+ 
+         inputs_list = [inputs]
+         for _ in range(num_buffers - 1):
+-            inputs_list.append(list(t.clone() for t in inputs))
++            inputs_list.append(
++                [t.clone() if isinstance(t, torch.Tensor) else t for t in inputs]
++            )
+ 
+         logger.debug(
+             f"[Autotuner] use_cold_l2_cache={tuning_config.use_cold_l2_cache}, use {num_buffers} different tensors for profiling"