RuntimeError: oneCCL: coll_param.cpp:455 validate: EXCEPTION: average operation is not supported for the scheduler path #2361
Description
🐛 Describe the bug
When I run the sft_gemma3 example in trl with FSDP2, I meet this error. Here is the steps to reproduce:
git clone https://github.com/huggingface/trl.git
cd trl
pip install -e .
export ZE_AFFINITY_MASK=0,1,2,3
accelerate launch --config_file config.yaml examples/scripts/sft_gemma3.py
And related config.yaml file is here:
compute_environment: LOCAL_MACHINE
debug: false
distributed_type: FSDP
downcast_bf16: 'no'
enable_cpu_affinity: false
fsdp_config:
fsdp_activation_checkpointing: false
fsdp_auto_wrap_policy: TRANSFORMER_BASED_WRAP
fsdp_cpu_ram_efficient_loading: true
fsdp_offload_params: false
fsdp_reshard_after_forward: true
fsdp_state_dict_type: SHARDED_STATE_DICT
fsdp_transformer_layer_cls_to_wrap: Gemma3DecoderLayer
fsdp_version: 2
ipex_config:
ipex: false
machine_rank: 0
main_training_function: main
mixed_precision: 'no'
num_machines: 1
num_processes: 4
rdzv_backend: static
same_network: true
tpu_env: []
tpu_use_cluster: false
tpu_use_sudo: false
use_cpu: false
And here is the error log:
[rank2]: Traceback (most recent call last):
[rank2]: File "/root/trl/examples/scripts/sft_gemma3.py", line 77, in <module>
[rank2]: main()
[rank2]: File "/root/trl/examples/scripts/sft_gemma3.py", line 70, in main
[rank2]: trainer.train()
[rank2]: File "/opt/venv/lib/python3.12/site-packages/transformers/trainer.py", line 2325, in train
[rank2]: return inner_training_loop(
[rank2]: ^^^^^^^^^^^^^^^^^^^^
[rank2]: File "/opt/venv/lib/python3.12/site-packages/transformers/trainer.py", line 2674, in _inner_training_loop
[rank2]: tr_loss_step = self.training_step(model, inputs, num_items_in_batch)
[rank2]: ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[rank2]: File "/root/trl/trl/trainer/sft_trainer.py", line 1190, in training_step
[rank2]: return super().training_step(*args, **kwargs)
[rank2]: ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[rank2]: File "/opt/venv/lib/python3.12/site-packages/transformers/trainer.py", line 4071, in training_step
[rank2]: self.accelerator.backward(loss, **kwargs)
[rank2]: File "/opt/venv/lib/python3.12/site-packages/accelerate/accelerator.py", line 2740, in backward
[rank2]: loss.backward(**kwargs)
[rank2]: File "/opt/venv/lib/python3.12/site-packages/torch/_tensor.py", line 629, in backward
[rank2]: torch.autograd.backward(
[rank2]: File "/opt/venv/lib/python3.12/site-packages/torch/autograd/__init__.py", line 364, in backward
[rank2]: _engine_run_backward(
[rank2]: File "/opt/venv/lib/python3.12/site-packages/torch/autograd/graph.py", line 865, in _engine_run_backward
[rank2]: return Variable._execution_engine.run_backward( # Calls into the C++ engine to run the backward pass
[rank2]: ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[rank2]: File "/opt/venv/lib/python3.12/site-packages/torch/autograd/function.py", line 317, in apply
[rank2]: return user_fn(self, *args)
[rank2]: ^^^^^^^^^^^^^^^^^^^^
[rank2]: File "/opt/venv/lib/python3.12/site-packages/torch/distributed/fsdp/_fully_shard/_fsdp_param_group.py", line 900, in backward
[rank2]: ctx.param_group.post_backward()
[rank2]: File "/opt/venv/lib/python3.12/site-packages/torch/distributed/fsdp/_fully_shard/_fsdp_param_group.py", line 566, in post_backward
[rank2]: ) = foreach_reduce(
[rank2]: ^^^^^^^^^^^^^^^
[rank2]: File "/opt/venv/lib/python3.12/site-packages/torch/utils/_contextlib.py", line 124, in decorate_context
[rank2]: return func(*args, **kwargs)
[rank2]: ^^^^^^^^^^^^^^^^^^^^^
[rank2]: File "/opt/venv/lib/python3.12/site-packages/torch/distributed/fsdp/_fully_shard/_fsdp_collectives.py", line 543, in foreach_reduce
[rank2]: reduce_scatter_comm(
[rank2]: File "/opt/venv/lib/python3.12/site-packages/torch/distributed/fsdp/_fully_shard/_fsdp_collectives.py", line 125, in __call__
[rank2]: return dist.reduce_scatter_tensor(
[rank2]: ^^^^^^^^^^^^^^^^^^^^^^^^^^^
[rank2]: File "/opt/venv/lib/python3.12/site-packages/torch/distributed/c10d_logger.py", line 83, in wrapper
[rank2]: return func(*args, **kwargs)
[rank2]: ^^^^^^^^^^^^^^^^^^^^^
[rank2]: File "/opt/venv/lib/python3.12/site-packages/torch/distributed/distributed_c10d.py", line 4586, in reduce_scatter_tensor
[rank2]: work = group._reduce_scatter_base(output, input, opts)
[rank2]: ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[rank2]: RuntimeError: oneCCL: coll_param.cpp:455 validate: EXCEPTION: average operation is not supported for the scheduler path
Versions
env info:
PyTorch version: 2.10.0.dev20251112+xpu
Is debug build: False
CUDA used to build PyTorch: None
ROCM used to build PyTorch: N/A
OS: Ubuntu 24.04.2 LTS (x86_64)
GCC version: (Ubuntu 13.3.0-6ubuntu2~24.04) 13.3.0
Clang version: Could not collect
CMake version: version 3.28.3
Libc version: glibc-2.39
Python version: 3.12.3 (main, Aug 14 2025, 17:47:21) [GCC 13.3.0] (64-bit runtime)
Python platform: Linux-6.8.0-86-generic-x86_64-with-glibc2.39
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: True
XPU used to build PyTorch: 20250201
Intel GPU driver version:
* intel-opencl-icd: 25.18.33578.15-1146~24.04
* libze1: 1.21.9.0-1136~24.04
Intel GPU models onboard:
* Intel(R) Data Center GPU Max 1550
* Intel(R) Data Center GPU Max 1550
* Intel(R) Data Center GPU Max 1550
* Intel(R) Data Center GPU Max 1550
Intel GPU models detected:
* [0] _XpuDeviceProperties(name='Intel(R) Data Center GPU Max 1550', platform_name='Intel(R) oneAPI Unified Runtime over Level-Zero', type='gpu', device_id=0xBD5, uuid=4651a87a-c1fc-7e89-0000-000000000001, driver_version='1.6.33578+15', total_memory=65520MB, max_compute_units=512, gpu_eu_count=512, gpu_subslice_count=64, max_work_group_size=1024, max_num_sub_groups=64, sub_group_sizes=[16 32], has_fp16=1, has_fp64=1, has_atomic64=1)
* [1] _XpuDeviceProperties(name='Intel(R) Data Center GPU Max 1550', platform_name='Intel(R) oneAPI Unified Runtime over Level-Zero', type='gpu', device_id=0xBD5, uuid=4651a87a-c1fc-7e89-0000-000000000002, driver_version='1.6.33578+15', total_memory=65520MB, max_compute_units=512, gpu_eu_count=512, gpu_subslice_count=64, max_work_group_size=1024, max_num_sub_groups=64, sub_group_sizes=[16 32], has_fp16=1, has_fp64=1, has_atomic64=1)
* [2] _XpuDeviceProperties(name='Intel(R) Data Center GPU Max 1550', platform_name='Intel(R) oneAPI Unified Runtime over Level-Zero', type='gpu', device_id=0xBD5, uuid=107dce6d-c943-d902-0000-000000000001, driver_version='1.6.33578+15', total_memory=65520MB, max_compute_units=512, gpu_eu_count=512, gpu_subslice_count=64, max_work_group_size=1024, max_num_sub_groups=64, sub_group_sizes=[16 32], has_fp16=1, has_fp64=1, has_atomic64=1)
* [3] _XpuDeviceProperties(name='Intel(R) Data Center GPU Max 1550', platform_name='Intel(R) oneAPI Unified Runtime over Level-Zero', type='gpu', device_id=0xBD5, uuid=107dce6d-c943-d902-0000-000000000002, driver_version='1.6.33578+15', total_memory=65520MB, max_compute_units=512, gpu_eu_count=512, gpu_subslice_count=64, max_work_group_size=1024, max_num_sub_groups=64, sub_group_sizes=[16 32], has_fp16=1, has_fp64=1, has_atomic64=1)
HIP runtime version: N/A
MIOpen runtime version: N/A
Is XNNPACK available: True
CPU:
Architecture: x86_64
CPU op-mode(s): 32-bit, 64-bit
Address sizes: 47 bits physical, 57 bits virtual
Byte Order: Little Endian
CPU(s): 224
On-line CPU(s) list: 0-223
Vendor ID: GenuineIntel
BIOS Vendor ID: Intel(R) Corporation
Model name: Intel(R) Xeon(R) Platinum 8480+
BIOS Model name: Intel(R) Xeon(R) Platinum 8480+ CPU @ 2.0GHz
BIOS CPU family: 179
CPU family: 6
Model: 143
Thread(s) per core: 2
Core(s) per socket: 56
Socket(s): 2
Stepping: 6
CPU(s) scaling MHz: 21%
CPU max MHz: 3800.0000
CPU min MHz: 800.0000
BogoMIPS: 4000.00
Flags: fpu vme de pse tsc msr pae mce cx8 apic sep mtrr pge mca cmov pat pse36 clflush dts acpi mmx fxsr sse sse2 ss ht tm pbe syscall nx pdpe1gb rdtscp lm constant_tsc art arch_perfmon pebs bts rep_good nopl xtopology nonstop_tsc cpuid aperfmperf tsc_known_freq pni pclmulqdq dtes64 ds_cpl vmx smx est tm2 ssse3 sdbg fma cx16 xtpr pdcm pcid dca sse4_1 sse4_2 x2apic movbe popcnt tsc_deadline_timer aes xsave avx f16c rdrand lahf_lm abm 3dnowprefetch cpuid_fault epb cat_l3 cat_l2 cdp_l3 intel_ppin cdp_l2 ssbd mba ibrs ibpb stibp ibrs_enhanced tpr_shadow flexpriority ept vpid ept_ad fsgsbase tsc_adjust sgx bmi1 avx2 smep bmi2 erms invpcid cqm rdt_a avx512f avx512dq rdseed adx smap avx512ifma clflushopt clwb intel_pt avx512cd sha_ni avx512bw avx512vl xsaveopt xsavec xgetbv1 xsaves cqm_llc cqm_occup_llc cqm_mbm_total cqm_mbm_local split_lock_detect user_shstk avx_vnni avx512_bf16 wbnoinvd dtherm ida arat pln pts hwp hwp_act_window hwp_epp hwp_pkg_req vnmi avx512vbmi umip pku ospke waitpkg avx512_vbmi2 gfni vaes vpclmulqdq avx512_vnni avx512_bitalg tme avx512_vpopcntdq la57 rdpid bus_lock_detect cldemote movdiri movdir64b enqcmd sgx_lc fsrm md_clear serialize tsxldtrk pconfig arch_lbr ibt amx_bf16 avx512_fp16 amx_tile amx_int8 flush_l1d arch_capabilities
Virtualization: VT-x
L1d cache: 5.3 MiB (112 instances)
L1i cache: 3.5 MiB (112 instances)
L2 cache: 224 MiB (112 instances)
L3 cache: 210 MiB (2 instances)
NUMA node(s): 2
NUMA node0 CPU(s): 0-55,112-167
NUMA node1 CPU(s): 56-111,168-223
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: Not affected
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; RSB filling; PBRSB-eIBRS SW sequence; BHI BHI_DIS_S
Vulnerability Srbds: Not affected
Vulnerability Tsx async abort: Not affected
Versions of relevant libraries:
[pip3] dpcpp-cpp-rt==2025.2.1
[pip3] galore-torch==1.0
[pip3] impi-rt==2021.16.1
[pip3] intel-cmplr-lib-rt==2025.2.1
[pip3] intel-cmplr-lib-ur==2025.2.1
[pip3] intel-cmplr-lic-rt==2025.2.1
[pip3] intel-opencl-rt==2025.2.1
[pip3] intel-openmp==2025.2.1
[pip3] intel-pti==0.13.1
[pip3] intel-sycl-rt==2025.2.1
[pip3] mkl==2025.2.0
[pip3] mypy_extensions==1.1.0
[pip3] numpy==1.26.4
[pip3] oneccl==2021.16.1
[pip3] oneccl-devel==2021.16.1
[pip3] onemkl-sycl-blas==2025.2.0
[pip3] onemkl-sycl-dft==2025.2.0
[pip3] onemkl-sycl-lapack==2025.2.0
[pip3] onemkl-sycl-rng==2025.2.0
[pip3] onemkl-sycl-sparse==2025.2.0
[pip3] onnx==1.19.0
[pip3] pytorch-msssim==1.0.0
[pip3] pytorch-triton-xpu==3.5.0+git1b0418a9
[pip3] tbb==2022.2.0
[pip3] tcmlib==1.4.0
[pip3] torch==2.10.0.dev20251112+xpu
[pip3] torchao==0.14.0.dev20250922+xpu
[pip3] torchaudio==2.10.0.dev20251113+xpu
[pip3] torchcodec==0.7.0.dev20250922
[pip3] torchdata==0.11.0
[pip3] torchvision==0.25.0.dev20251113+xpu
[pip3] triton==3.5.0
[pip3] umf==0.11.0