[baseline5] volatile fix trans to shfl_down
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verify_xllm_moe_load.py
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verify_xllm_moe_load.py
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#!/usr/bin/env python3
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"""
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verify_xllm_moe_load.py — 在 BI-V100 真机验证 xllm_moe.so 能否加载
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用法: python3 verify_xllm_moe_load.py
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或 Docker 内: python3 /workspace/qwen3_6_scripts/verify_xllm_moe_load.py
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验证内容:
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1. 所有 prebuilt .so 的 dlopen 可行性
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2. xllm_moe.so 的 moe_fused_topk 是否可调用
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3. corex_moe_topk_softmax.so 的 moe_topk_softmax 是否可调用
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4. ix_startup_patch.apply() 完整执行结果
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5. _custom_ops.topk_softmax 实际走哪条路径
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"""
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import os
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import sys
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import importlib
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import importlib.util
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import traceback
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def section(title):
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print(f"\n{'='*65}")
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print(f" {title}")
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print(f"{'='*65}")
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def try_load_so(name, path):
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"""Try to load a .so file, return (module, error_string)."""
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if not os.path.isfile(path):
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return None, f"FILE NOT FOUND: {path}"
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try:
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spec = importlib.util.spec_from_file_location(name, path)
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if spec is None:
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return None, "spec_from_file_location returned None"
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mod = importlib.util.module_from_spec(spec)
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spec.loader.exec_module(mod)
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funcs = [x for x in dir(mod) if not x.startswith('_')]
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return mod, f"OK ({len(funcs)} functions: {', '.join(funcs[:10])})"
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except Exception as e:
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return None, f"{type(e).__name__}: {e}"
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# =========================================================================
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section("1. Locate all .so files")
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# =========================================================================
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# Search paths (same as xllm_ops.py)
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search_dirs = []
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try:
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import vllm
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vllm_root = os.path.dirname(vllm.__file__)
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search_dirs.append(vllm_root)
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print(f" vllm root: {vllm_root}")
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except ImportError:
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print(" vllm not installed")
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vllm_root = None
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for d in [
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"/workspace/qwen3_6_scripts/prebuilt/corex-3.2.3-ivcore10",
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"/workspace/qwen3_6_scripts/ex_engine/prebuilt",
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os.path.join(os.path.dirname(__file__), "prebuilt", "corex-3.2.3-ivcore10"),
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os.path.join(os.path.dirname(__file__), "qwen3_6_scripts", "prebuilt", "corex-3.2.3-ivcore10"),
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]:
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if os.path.isdir(d):
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search_dirs.append(os.path.normpath(d))
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search_dirs = list(dict.fromkeys(search_dirs)) # dedupe preserving order
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print(f" search dirs: {search_dirs}")
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# =========================================================================
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section("2. Load test: all xllm_*.so and key bridge .so")
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# =========================================================================
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test_modules = [
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"xllm_moe",
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"xllm_norm",
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"xllm_activation",
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"xllm_cache",
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"xllm_rope",
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"ix_moe_bridge",
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"ix_full_bridge",
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"corex_moe_topk_softmax",
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"corex_moe_index_combine",
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"corex_moe_direct_routed",
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"corex_moe_weight_gather",
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"corex_moe_exact_reduce",
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"gemm_grouped",
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"corex_batched_gemm",
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]
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loaded_modules = {}
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for name in test_modules:
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found = False
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for d in search_dirs:
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path = os.path.join(d, f"{name}.so")
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if os.path.isfile(path):
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mod, status = try_load_so(name, path)
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tag = "✓" if mod else "✗"
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print(f" {tag} {name:35s} {status}")
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if mod:
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loaded_modules[name] = mod
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found = True
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break
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if not found:
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print(f" - {name:35s} NOT FOUND in any search dir")
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# =========================================================================
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section("3. Functional test: xllm_moe.moe_fused_topk")
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# =========================================================================
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if "xllm_moe" in loaded_modules:
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mod = loaded_modules["xllm_moe"]
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print(f" Exported functions: {[x for x in dir(mod) if not x.startswith('_')]}")
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if hasattr(mod, "moe_fused_topk"):
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try:
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import torch
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if torch.cuda.is_available():
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# moe_fused_topk(gating_output, topk, renormalize, correction_bias, scoring_func)
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gating = torch.randn(4, 8, device="cuda", dtype=torch.float32)
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w, ids = mod.moe_fused_topk(gating, 2)
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print(f" ✓ moe_fused_topk: weights shape={w.shape}, ids shape={ids.shape}")
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print(f" weights={w[0].tolist()}, ids={ids[0].tolist()}")
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else:
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print(f" - no CUDA device, skipping functional test")
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except Exception as e:
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print(f" ✗ moe_fused_topk call FAILED: {e}")
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traceback.print_exc()
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else:
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print(f" ✗ moe_fused_topk NOT in module attrs")
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print(f" available: {[x for x in dir(mod) if not x.startswith('_')]}")
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else:
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print(f" ✗ xllm_moe.so not loaded, cannot test")
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# =========================================================================
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section("4. Functional test: corex_moe_topk_softmax.moe_topk_softmax")
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# =========================================================================
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if "corex_moe_topk_softmax" in loaded_modules:
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mod = loaded_modules["corex_moe_topk_softmax"]
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print(f" Exported functions: {[x for x in dir(mod) if not x.startswith('_')]}")
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if hasattr(mod, "moe_topk_softmax"):
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try:
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import torch
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if torch.cuda.is_available():
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gating = torch.randn(4, 8, device="cuda", dtype=torch.float32)
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w, ids = mod.moe_topk_softmax(gating, 2, True)
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print(f" ✓ moe_topk_softmax: weights shape={w.shape}, ids shape={ids.shape}")
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print(f" weights={w[0].tolist()}, ids={ids[0].tolist()}")
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else:
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print(f" - no CUDA device")
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except Exception as e:
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print(f" ✗ moe_topk_softmax call FAILED: {e}")
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traceback.print_exc()
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else:
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print(f" ✗ moe_topk_softmax NOT in module attrs")
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else:
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print(f" ✗ corex_moe_topk_softmax.so not loaded, cannot test")
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# =========================================================================
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section("5. ixformer.functions.vllm_moe_topk_softmax existence")
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# =========================================================================
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try:
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import ixformer.functions as ixf_F
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has_it = hasattr(ixf_F, "vllm_moe_topk_softmax")
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print(f" ixformer.functions.vllm_moe_topk_softmax: {'✓ EXISTS' if has_it else '✗ MISSING (expected on BI-V100)'}")
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if not has_it:
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# Check what MoE-related functions DO exist
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moe_funcs = [n for n in dir(ixf_F) if 'moe' in n.lower() or 'topk' in n.lower()]
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print(f" MoE-related functions that DO exist: {moe_funcs if moe_funcs else 'NONE'}")
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except ImportError as e:
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print(f" ixformer not available: {e}")
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# =========================================================================
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section("6. ix_startup_patch.apply() test")
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# =========================================================================
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try:
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from vllm import ix_startup_patch
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print(f" ix_startup_patch imported from: {ix_startup_patch.__file__}")
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n = ix_startup_patch.apply()
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print(f" ✓ apply() returned: {n} patches applied")
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except ImportError as e:
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print(f" ✗ import failed: {e}")
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except Exception as e:
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print(f" ✗ apply() failed: {type(e).__name__}: {e}")
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traceback.print_exc()
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# =========================================================================
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section("7. _custom_ops.topk_softmax dispatch test")
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# =========================================================================
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try:
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import vllm._custom_ops as ops
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print(f" _custom_ops from: {ops.__file__}")
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import torch
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if torch.cuda.is_available():
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gating = torch.randn(4, 8, device="cuda", dtype=torch.float32)
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tw = torch.empty(4, 2, device="cuda", dtype=torch.float32)
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ti = torch.empty(4, 2, device="cuda", dtype=torch.int32)
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tei = torch.empty(4, 2, device="cuda", dtype=torch.int32)
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try:
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ops.topk_softmax(tw, ti, tei, gating)
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print(f" ✓ topk_softmax succeeded")
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print(f" weights={tw[0].tolist()}, ids={ti[0].tolist()}")
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except Exception as e:
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print(f" ✗ topk_softmax FAILED: {e}")
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# Check which path was taken by inspecting the function
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import inspect
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src = inspect.getsource(ops.topk_softmax)
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if "hasattr(ixf_F" in src:
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print(f" → using PATCHED _custom_ops.py (has fallback chain)")
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elif "ixf_F.vllm_moe_topk_softmax" in src and "hasattr" not in src:
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print(f" → using ORIGINAL _custom_ops.py (NO fallback, will crash)")
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else:
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print(f" → using UNKNOWN version of topk_softmax")
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else:
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print(f" - no CUDA device")
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except Exception as e:
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print(f" ✗ {e}")
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traceback.print_exc()
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# =========================================================================
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section("8. Library compatibility check")
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# =========================================================================
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try:
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import torch
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print(f" PyTorch: {torch.__version__}")
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print(f" CUDA available: {torch.cuda.is_available()}")
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if torch.cuda.is_available():
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print(f" CUDA version: {torch.version.cuda}")
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print(f" Device: {torch.cuda.get_device_name(0)}")
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# Check if libcudart.so.10.2 exists (required by all xllm .so)
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import ctypes
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for lib in ["libcudart.so.10.2", "libcuinfer.so.7", "libc10.so",
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"libtorch_python.so", "libtorch_cuda.so"]:
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try:
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ctypes.CDLL(lib)
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print(f" ✓ {lib}")
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except OSError as e:
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print(f" ✗ {lib}: {e}")
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except Exception as e:
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print(f" error: {e}")
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print(f"\n{'='*65}")
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print(" DONE — paste this entire output back")
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print(f"{'='*65}")
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