bitsandbytes 'invalid configuration argument' (ops.cu) with DeepSpeed Offload
Combining a bitsandbytes 8-bit optimizer with DeepSpeed ZeRO offload crashes with 'Error invalid configuration argument at line 216 in file .../bitsandbytes/csrc/ops.cu'. The two optimizer-state managers conflict over offloaded/partitioned parameters; disabling ZeRO offload (zero_stage 0) or dropping the 8-bit optimizer resolves it.
Combining a bitsandbytes 8-bit optimizer with DeepSpeed ZeRO offload crashes with 'Error invalid configuration argument at line 216 in file.
What this failure is
bitsandbytes 'invalid configuration argument' (ops.cu) with DeepSpeed Offload is a Distributed Training failure seen during ML training runs. Combining a bitsandbytes 8-bit optimizer with DeepSpeed ZeRO offload crashes with 'Error invalid configuration argument at line 216 in file .../bitsandbytes/csrc/ops.cu'. The two optimizer-state managers conflict over offloaded/partitioned parameters; disabling ZeRO offload (zero_stage 0) or dropping the 8-bit optimizer resolves it. Common tags: Bitsandbytes, Deepspeed, Zero Offload, 8bit Optimizer.
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Why it happens (the mechanism)
Bitsandbytes 8-bit optimizer CUDA kernels are launched per parameter; under DeepSpeed ZeRO offload the parameters are partitioned or moved to CPU, producing zero-size or mis-shaped launch configurations. DeepSpeed and bitsandbytes both try to manage optimizer state, and the combination yields an invalid CUDA launch configuration. Taken together, these mechanisms explain why the failure is reproducible, why it tends to surface on specific workloads or scales, and why generic mitigation attempts often fall short without addressing the underlying cause.
What you'll observe
- Training crashes early with a bitsandbytes CUDA configuration error
- torch.distributed.elastic reports the worker failed with exit code 1
- Happens only when 8-bit optimizers meet DeepSpeed ZeRO offload
Common symptoms and what they mean
| Symptom | Why it happens |
|---|---|
| Error invalid configuration argument at line 216 in file .../bitsandbytes/csrc/ops.cu | bitsandbytes 8-bit optimizer CUDA kernels are launched per parameter; under DeepSpeed ZeRO offload the parameters are partitioned or moved to CPU, producing zero-size or mis-shaped launch configurations |
| torch.distributed.elastic.multiprocessing.api: failed (exitcode: 1) | DeepSpeed and bitsandbytes both try to manage optimizer state, and the combination yields an invalid CUDA launch configuration |
| Occurs with adamw_8bit/paged optimizers under ZeRO-3 offload | bitsandbytes 8-bit optimizer CUDA kernels are launched per parameter; under DeepSpeed ZeRO offload the parameters are partitioned or moved to CPU, producing zero-size or mis-shaped launch configurations |
Which systems are affected
- Axolotl/HF + DeepSpeed ZeRO-2/3 with offload_optimizer or offload_param
- bitsandbytes 8-bit / paged optimizers
- QLoRA stacks that also enable ZeRO offload
How to confirm this is the problem
Use this checklist to test the hypothesis against a small reproduction. No single line proves the root cause, so preserve the preceding events and compare one variable at a time.
- ✓Reproduce the failure from a clean checkpoint/seed: the symptom must appear without warm-up state from a previous run.
- ✓Verified signal present: Error invalid configuration argument at line 216 in file .../bitsandbytes/csrc/ops.cu
- ✓Verified signal present: torch.distributed.elastic.multiprocessing.api: failed (exitcode: 1)
- ✓Verified signal present: Occurs with adamw_8bit/paged optimizers under ZeRO-3 offload
- ✓A targeted fix from the "How to fix it" section eliminates or substantially reduces the symptom within one validation pass.
The fix and the prevention pattern
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Diagnose this failure in VS Code
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Install the free VS Code extensionDeepSpeed errors in context
DeepSpeed changes when parameters, gradients and optimizer state are created, partitioned, gathered and offloaded. The hub separates ZeRO, memory, checkpoint and pipeline failures by lifecycle phase.
Compare every deepspeed error side by sideRelated failures to investigate next
Root cause
- bitsandbytes 8-bit optimizer CUDA kernels are launched per parameter; under DeepSpeed ZeRO offload the parameters are partitioned or moved to CPU, producing zero-size or mis-shaped launch configurations
- DeepSpeed and bitsandbytes both try to manage optimizer state, and the combination yields an invalid CUDA launch configuration
The fix and how to prevent it
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