pytorch - 💡(How to fix) Fix `InductorError: AssertionError` in `simplify_and_reorder` during scheduler node fusion for model with `unfold → scaled_dot_product_attention → roll → LayerNorm` [1 participants]

🐛 Describe the bug

torch.compile(backend='inductor') raises an InductorError (wrapping an AssertionError) during the kernel fusion phase of the Inductor scheduler. The crash happens in SchedulerNode._compute_attrs → simplify_and_reorder, with the following assertion failing:

assert all(isinstance(f, Expr) for f in extra_indexing_expr)
torch._inductor.exc.InductorError: AssertionError:

The model pipeline is:

1. nn.Hardswish() on input [2, 6]
2. .unfold(1, 2, 1) → shape [2, 5, 2]
3. F.scaled_dot_product_attention(x, x, x) (self-attention)
4. torch.roll(..., 1, 2)
5. nn.LayerNorm([2])
6. torch.nan_to_num(...)

Eager mode runs correctly and produces finite output. The crash is deterministic and occurs at compile time (not at runtime execution), inside the C++ CPU backend's node fusion logic (codegen/cpp.py → fuse → recompute_size_and_body).

Minimal Reproducer

import os, tempfile
os.environ.setdefault('TORCHINDUCTOR_CACHE_DIR', tempfile.mkdtemp(prefix='inductor_'))

import torch
import torch.nn as nn
import torch.nn.functional as F

m_hardswish = nn.Hardswish()
m_layernorm = nn.LayerNorm([2])

torch.manual_seed(0)
x = torch.randn([2, 6])

def model():
    out = m_hardswish(x)                                    # [2, 6]
    out = out.unfold(1, 2, 1)                               # [2, 5, 2]
    out = F.scaled_dot_product_attention(out, out, out)     # [2, 5, 2]
    out = torch.roll(out, 1, 2)                             # [2, 5, 2]
    out = m_layernorm(out)                                  # [2, 5, 2]
    out = torch.nan_to_num(out)                             # [2, 5, 2]
    return out

# Eager: works fine
print("Eager:", model().shape)

# Compiled: crashes in Inductor scheduler during node fusion
compiled_model = torch.compile(model, backend='inductor')
compiled_model()  # ← InductorError: AssertionError in simplify_and_reorder

Error logs

Traceback (most recent call last): File "/home/bugs/crash_c3315dea.py", line 33, in <module> _compiled_out = _compiled() File "/home/.venv/lib/python3.10/site-packages/torch/_dynamo/eval_frame.py", line 1038, in compile_wrapper raise e.remove_dynamo_frames() from None # see TORCHDYNAMO_VERBOSE=1 File "/home/.venv/lib/python3.10/site-packages/torch/_dynamo/eval_frame.py", line 1024, in compile_wrapper return fn(*args, **kwargs) File "/home/.venv/lib/python3.10/site-packages/torch/_dynamo/convert_frame.py", line 2316, in call result = self._torchdynamo_orig_backend( File "/home/.venv/lib/python3.10/site-packages/torch/_dynamo/convert_frame.py", line 2052, in call result = self._inner_convert( File "/home/.venv/lib/python3.10/site-packages/torch/_dynamo/convert_frame.py", line 729, in call result = _compile( File "/home/.venv/lib/python3.10/site-packages/torch/_dynamo/convert_frame.py", line 1827, in _compile guarded_code, tracer_output = compile_inner(code, one_graph, hooks) File "/home/.venv/lib/python3.10/site-packages/torch/_utils_internal.py", line 96, in wrapper_function return function(*args, **kwargs) File "/home/.venv/lib/python3.10/site-packages/torch/_dynamo/convert_frame.py", line 1500, in compile_inner return _compile_inner(code, one_graph, hooks) File "/home/.venv/lib/python3.10/site-packages/torch/_dynamo/convert_frame.py", line 1534, in _compile_inner dynamo_output = compile_frame( File "/home/.venv/lib/python3.10/site-packages/torch/_dynamo/convert_frame.py", line 1408, in compile_frame bytecode, tracer_output = transform_code_object(code, transform) File "/home/.venv/lib/python3.10/site-packages/torch/_dynamo/bytecode_transformation.py", line 1608, in transform_code_object tracer_output = transformations(instructions, code_options) File "/home/.venv/lib/python3.10/site-packages/torch/_dynamo/convert_frame.py", line 1380, in transform tracer_output = trace_frame( File "/home/.venv/lib/python3.10/site-packages/torch/_dynamo/convert_frame.py", line 341, in _fn return fn(*args, **kwargs) File "/home/.venv/lib/python3.10/site-packages/torch/_dynamo/convert_frame.py", line 863, in trace_frame run_tracer() File "/home/.venv/lib/python3.10/site-packages/torch/_dynamo/convert_frame.py", line 844, in run_tracer tracer.run() File "/home/.venv/lib/python3.10/site-packages/torch/_dynamo/symbolic_convert.py", line 1794, in run while self.step(): File "/home/.venv/lib/python3.10/site-packages/torch/_dynamo/symbolic_convert.py", line 1459, in step self.dispatch_table[inst.opcode](self, inst) File "/home/.venv/lib/python3.10/site-packages/torch/_dynamo/symbolic_convert.py", line 5570, in RETURN_VALUE self._return(inst) File "/home/.venv/lib/python3.10/site-packages/torch/_dynamo/symbolic_convert.py", line 5552, in _return all_stack_locals_metadata = self.output.compile_subgraph( File "/home/.venv/lib/python3.10/site-packages/torch/_dynamo/output_graph.py", line 1889, in compile_subgraph self.compile_and_call_fx_graph(tx, pass2.graph_output_vars(), root) File "/home/.venv/lib/python3.10/site-packages/torch/_dynamo/output_graph.py", line 2460, in compile_and_call_fx_graph compiled_fn = self.call_user_compiler(gm, self.example_inputs()) File "/home/.venv/lib/python3.10/site-packages/torch/_dynamo/output_graph.py", line 2613, in call_user_compiler return self._call_user_compiler(gm, example_inputs) File "/home/.venv/lib/python3.10/site-packages/torch/_dynamo/output_graph.py", line 2664, in call_user_compiler compiled_fn = compiler_fn(gm, example_inputs) File "/home/.venv/lib/python3.10/site-packages/torch/dynamo/repro/after_dynamo.py", line 156, in call compiled_gm = compiler_fn(gm, example_inputs) File "/home/.venv/lib/python3.10/site-packages/torch/init.py", line 2461, in call return compile_fx(model, inputs, config_patches=self.config) File "/home/.venv/lib/python3.10/site-packages/torch/_inductor/compile_fx.py", line 2578, in compile_fx return _maybe_wrap_and_compile_fx_main( File "/home/.venv/lib/python3.10/site-packages/torch/_inductor/compile_fx.py", line 2655, in _maybe_wrap_and_compile_fx_main return _compile_fx_main( File "/home/.venv/lib/python3.10/site-packages/torch/_inductor/compile_fx.py", line 2864, in _compile_fx_main raise e.remove_dynamo_frames() from None # see TORCHDYNAMO_VERBOSE=1 File "/home/.venv/lib/python3.10/site-packages/torch/_inductor/compile_fx.py", line 2850, in _compile_fx_main return aot_autograd( File "/home/.venv/lib/python3.10/site-packages/torch/_dynamo/backends/common.py", line 124, in call cg = aot_module_simplified(gm, example_inputs, **self.kwargs) File "/home/.venv/lib/python3.10/site-packages/torch/_functorch/aot_autograd.py", line 1161, in aot_module_simplified compiled_fn, _ = aot_stage2_compile( File "/home/.venv/lib/python3.10/site-packages/torch/_functorch/_aot_autograd/graph_compile.py", line 366, in aot_stage2_compile return aot_stage2_autograd(aot_state, aot_graph_capture) File "/home/.venv/lib/python3.10/site-packages/torch/_functorch/_aot_autograd/graph_compile.py", line 2197, in aot_stage2_autograd fwd_output_strides, compiled_fw_func = _aot_stage2b_fw_compile( File "/home/.venv/lib/python3.10/site-packages/torch/_functorch/_aot_autograd/graph_compile.py", line 1986, in _aot_stage2b_fw_compile return _aot_stage2b_compile_forward_or_inference( File "/home/.venv/lib/python3.10/site-packages/torch/_functorch/_aot_autograd/graph_compile.py", line 2513, in _aot_stage2b_compile_forward_or_inference compiled_fw_func = compiler(fw_module, adjusted_flat_args) File "/home/.venv/lib/python3.10/site-packages/torch/_functorch/_aot_autograd/schemas.py", line 1394, in call output_code = self.compiler_fn(gm, example_inputs) File "/home/.venv/lib/python3.10/site-packages/torch/_inductor/compile_fx.py", line 2719, in fw_compiler_base return compile_fx_forward( File "/home/.venv/lib/python3.10/site-packages/torch/_inductor/compile_fx.py", line 2390, in compile_fx_forward return inner_compile( File "/home/.venv/lib/python3.10/site-packages/torch/_inductor/compile_fx.py", line 826, in compile_fx_inner return wrap_compiler_debug(_compile_fx_inner, compiler_name="inductor")( File "/home/.venv/lib/python3.10/site-packages/torch/_dynamo/repro/after_aot.py", line 273, in debug_wrapper inner_compiled_fn = compiler_fn(gm, example_inputs) File "/home/.venv/lib/python3.10/site-packages/torch/_inductor/compile_fx.py", line 1053, in _compile_fx_inner raise InductorError(e, currentframe()).with_traceback( File "/home/.venv/lib/python3.10/site-packages/torch/_inductor/compile_fx.py", line 1037, in _compile_fx_inner mb_compiled_graph = fx_codegen_and_compile( File "/home/.venv/lib/python3.10/site-packages/torch/_inductor/compile_fx.py", line 1798, in fx_codegen_and_compile return scheme.codegen_and_compile(gm, example_inputs, inputs_to_check, graph_kwargs) File "/home/.venv/lib/python3.10/site-packages/torch/_inductor/compile_fx.py", line 1570, in codegen_and_compile compiled_module = graph.compile_to_module() File "/home/.venv/lib/python3.10/site-packages/torch/_inductor/graph.py", line 2499, in compile_to_module return self._compile_to_module() File "/home/.venv/lib/python3.10/site-packages/torch/_inductor/graph.py", line 2505, in _compile_to_module self.codegen_with_cpp_wrapper() if self.cpp_wrapper else self.codegen() File "/home/.venv/lib/python3.10/site-packages/torch/_inductor/graph.py", line 2437, in codegen self._update_scheduler() File "/home/.venv/lib/python3.10/site-packages/torch/_inductor/graph.py", line 2431, in _update_scheduler self.scheduler = Scheduler(self.operations) File "/home/.venv/lib/python3.10/site-packages/torch/_inductor/scheduler.py", line 2882, in init self._init(nodes) File "/home/.venv/lib/python3.10/site-packages/torch/_inductor/scheduler.py", line 2975, in _init self.nodes = self.fuse_nodes(self.nodes) File "/home/.venv/lib/python3.10/site-packages/torch/_inductor/scheduler.py", line 3711, in fuse_nodes nodes = self.fuse_nodes_once(nodes, is_reorder_round=False) File "/home/.venv/lib/python3.10/site-packages/torch/_inductor/scheduler.py", line 4637, in fuse_nodes_once self._try_fusion_pairs( File "/home/.venv/lib/python3.10/site-packages/torch/_inductor/scheduler.py", line 4546, in _try_fusion_pairs self.fuse_two_nodes(node1, node2, fused_nodes) File "/home/.venv/lib/python3.10/site-packages/torch/_inductor/scheduler.py", line 4373, in fuse_two_nodes node3 = self.get_backend(device).fuse(node1, node2) File "/home/.venv/lib/python3.10/site-packages/torch/_inductor/codegen/cpp.py", line 4744, in fuse node_to_recomp.recompute_size_and_body( File "/home/.venv/lib/python3.10/site-packages/torch/_inductor/scheduler.py", line 1547, in recompute_size_and_body self._compute_attrs( File "/home/.venv/lib/python3.10/site-packages/torch/_inductor/scheduler.py", line 1515, in _compute_attrs self._sizes, body = self.node.simplify_and_reorder( File "/home/.venv/lib/python3.10/site-packages/torch/_inductor/ir.py", line 4963, in simplify_and_reorder assert all(isinstance(f, Expr) for f in extra_indexing_expr) torch._inductor.exc.InductorError: AssertionError:

Versions

Collecting environment information... PyTorch version: 2.11.0+cu130 Is debug build: False CUDA used to build PyTorch: 13.0 ROCM used to build PyTorch: N/A

OS: Ubuntu 22.04.5 LTS (x86_64) GCC version: (Ubuntu 11.4.0-1ubuntu1~22.04.3) 11.4.0 Clang version: 15.0.0 ([email protected]:llvm/llvm-project.git 4ba6a9c9f65bbc8bd06e3652cb20fd4dfc846137) CMake version: version 3.22.1 Libc version: glibc-2.35

Python version: 3.10.12 (main, Mar 3 2026, 11:56:32) [GCC 11.4.0] (64-bit runtime) Python platform: Linux-6.8.0-94-generic-x86_64-with-glibc2.35 Is CUDA available: False CUDA runtime version: No CUDA CUDA_MODULE_LOADING set to: N/A GPU models and configuration: No CUDA Nvidia driver version: No CUDA cuDNN version: No CUDA Is XPU available: False HIP runtime version: N/A MIOpen runtime version: N/A Is XNNPACK available: True Caching allocator config: N/A

CPU: Architecture: x86_64 CPU op-mode(s): 32-bit, 64-bit Address sizes: 52 bits physical, 57 bits virtual Byte Order: Little Endian CPU(s): 384 On-line CPU(s) list: 0-383 Vendor ID: AuthenticAMD Model name: AMD EPYC 9684X 96-Core Processor CPU family: 25 Model: 17 Thread(s) per core: 2 Core(s) per socket: 96 Socket(s): 2 Stepping: 2 BogoMIPS: 5099.98 Flags: fpu vme de pse tsc msr pae mce cx8 apic sep mtrr pge mca cmov pat pse36 clflush mmx fxsr sse sse2 ht syscall nx mmxext fxsr_opt pdpe1gb rdtscp lm constant_tsc rep_good amd_lbr_v2 nopl nonstop_tsc cpuid extd_apicid aperfmperf rapl pni pclmulqdq monitor ssse3 fma cx16 pcid sse4_1 sse4_2 x2apic movbe popcnt aes xsave avx f16c rdrand lahf_lm cmp_legacy svm extapic cr8_legacy abm sse4a misalignsse 3dnowprefetch osvw ibs skinit wdt tce topoext perfctr_core perfctr_nb bpext perfctr_llc mwaitx cpb cat_l3 cdp_l3 hw_pstate ssbd mba perfmon_v2 ibrs ibpb stibp ibrs_enhanced vmmcall fsgsbase bmi1 avx2 smep bmi2 erms invpcid cqm rdt_a avx512f avx512dq rdseed adx smap avx512ifma clflushopt clwb avx512cd sha_ni avx512bw avx512vl xsaveopt xsavec xgetbv1 xsaves cqm_llc cqm_occup_llc cqm_mbm_total cqm_mbm_local user_shstk avx512_bf16 clzero irperf xsaveerptr rdpru wbnoinvd amd_ppin cppc amd_ibpb_ret arat npt lbrv svm_lock nrip_save tsc_scale vmcb_clean flushbyasid decodeassists pausefilter pfthreshold avic v_vmsave_vmload vgif x2avic v_spec_ctrl vnmi avx512vbmi umip pku ospke avx512_vbmi2 gfni vaes vpclmulqdq avx512_vnni avx512_bitalg avx512_vpopcntdq la57 rdpid overflow_recov succor smca fsrm flush_l1d debug_swap ibpb_exit_to_user Virtualization: AMD-V L1d cache: 6 MiB (192 instances) L1i cache: 6 MiB (192 instances) L2 cache: 192 MiB (192 instances) L3 cache: 2.3 GiB (24 instances) NUMA node(s): 2 NUMA node0 CPU(s): 0-95,192-287 NUMA node1 CPU(s): 96-191,288-383 Vulnerability Gather data sampling: Not affected Vulnerability Itlb multihit: Not affected Vulnerability L1tf: Not affected Vulnerability Mds: Not affected Vulnerability Meltdown: Not affected Vulnerability Mmio stale data: Not affected Vulnerability Reg file data sampling: Not affected Vulnerability Retbleed: Not affected Vulnerability Spec rstack overflow: Mitigation; Safe RET Vulnerability Spec store bypass: Mitigation; Speculative Store Bypass disabled via prctl Vulnerability Spectre v1: Mitigation; usercopy/swapgs barriers and __user pointer sanitization Vulnerability Spectre v2: Mitigation; Enhanced / Automatic IBRS; IBPB conditional; STIBP always-on; RSB filling; PBRSB-eIBRS Not affected; BHI Not affected Vulnerability Srbds: Not affected Vulnerability Tsx async abort: Not affected Vulnerability Vmscape: Mitigation; IBPB before exit to userspace

Versions of relevant libraries: [pip3] numpy==2.2.6 [pip3] nvidia-cublas==13.1.0.3 [pip3] nvidia-cuda-cupti==13.0.85 [pip3] nvidia-cuda-nvrtc==13.0.88 [pip3] nvidia-cuda-runtime==13.0.96 [pip3] nvidia-cudnn-cu13==9.19.0.56 [pip3] nvidia-cufft==12.0.0.61 [pip3] nvidia-curand==10.4.0.35 [pip3] nvidia-cusolver==12.0.4.66 [pip3] nvidia-cusparse==12.6.3.3 [pip3] nvidia-cusparselt-cu13==0.8.0 [pip3] nvidia-nccl-cu13==2.28.9 [pip3] nvidia-nvjitlink==13.0.88 [pip3] nvidia-nvtx==13.0.85 [pip3] torch==2.11.0 [pip3] triton==3.6.0 [conda] Could not collect

cc @chauhang @penguinwu