ValueError: Query/Key/Value should either all have the same dtype,

[khayamgondal]

xformers fails with the following error when run with accelerate

ValueError: Query/Key/Value should either all have the same dtype, or (in the quantized case) Key/Value should have dtype torch.int32
  query.dtype: torch.float32
  key.dtype  : torch.float16
  value.dtype: torch.float16

I am running accelerate as following

accelerate launch diffusers/examples/dreambooth/train_dreambooth_lora_sdxl.py \
      --pretrained_model_name_or_path="stabilityai/stable-diffusion-xl-base-1.0" \
      --instance_data_dir={input_dir} \
      --output_dir={output_dir} \
      --instance_prompt=instance_prompt \
      --mixed_precision="fp16" \
      --resolution=1024 \
      --train_batch_size=1 \
      --gradient_accumulation_steps=4 \
      --learning_rate=1e-4 \
      --lr_scheduler="constant" \
      --lr_warmup_steps=0 \
      --checkpointing_steps=500 \
      --max_train_steps=1000 \
      --seed="0" \
      --checkpoints_total_limit=5 \
      --enable_xformers_memory_efficient_attention

Accelerate config
{
  "compute_environment": "LOCAL_MACHINE",
  "debug": false,
  "distributed_type": "MULTI_GPU",
  "downcast_bf16": false,
  "machine_rank": 0,
  "main_training_function": "main",
  "mixed_precision": "no",
  "num_machines": 1,
  "num_processes": 2,
  "rdzv_backend": "static",
  "same_network": false,
  "tpu_use_cluster": false,
  "tpu_use_sudo": false,
  "use_cpu": false
}

Versions:

xformers==0.0.23.dev687
accelerate==0.24.1
torch==2.1.0
torchvision==0.16.1

@blefaudeux @danthe3rd @fmassa

[matthiasreisser]

Same problem for me. Code runs fine without xformers.

Collecting environment information... PyTorch version: 2.0.1+cu117 Is debug build: False CUDA used to build PyTorch: 11.7 ROCM used to build PyTorch: N/A

OS: Ubuntu 20.04.6 LTS (x86_64) GCC version: (Ubuntu 9.4.0-1ubuntu1~20.04.2) 9.4.0 Clang version: Could not collect CMake version: version 3.25.0 Libc version: glibc-2.31

Python version: 3.10.13 (main, Aug 25 2023, 13:20:03) [GCC 9.4.0] (64-bit runtime) Python platform: Linux-5.4.0-152-generic-x86_64-with-glibc2.31 Is CUDA available: True CUDA runtime version: 11.7.99 CUDA_MODULE_LOADING set to: LAZY GPU models and configuration: GPU 0: Tesla V100-SXM2-32GB Nvidia driver version: 515.65.01 cuDNN version: Could not collect 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 Byte Order: Little Endian Address sizes: 46 bits physical, 48 bits virtual CPU(s): 80 On-line CPU(s) list: 0-79 Thread(s) per core: 2 Core(s) per socket: 20 Socket(s): 2 NUMA node(s): 2 Vendor ID: GenuineIntel CPU family: 6 Model: 85 Model name: Intel(R) Xeon(R) Gold 6230 CPU @ 2.10GHz Stepping: 7 CPU MHz: 1997.367 CPU max MHz: 3900.0000 CPU min MHz: 800.0000 BogoMIPS: 4200.00 Virtualization: VT-x L1d cache: 1.3 MiB L1i cache: 1.3 MiB L2 cache: 40 MiB L3 cache: 55 MiB NUMA node0 CPU(s): 0-19,40-59 NUMA node1 CPU(s): 20-39,60-79 Vulnerability Itlb multihit: KVM: Mitigation: Split huge pages Vulnerability L1tf: Not affected Vulnerability Mds: Not affected Vulnerability Meltdown: Not affected Vulnerability Mmio stale data: Mitigation; Clear CPU buffers; SMT vulnerable Vulnerability Retbleed: Mitigation; Enhanced IBRS Vulnerability Spec store bypass: Mitigation; Speculative Store Bypass disabled via prctl and seccomp Vulnerability Spectre v1: Mitigation; usercopy/swapgs barriers and __user pointer sanitization Vulnerability Spectre v2: Mitigation; Enhanced IBRS, IBPB conditional, RSB filling, PBRSB-eIBRS SW sequence Vulnerability Srbds: Not affected Vulnerability Tsx async abort: Mitigation; TSX disabled 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 pni pclmulqdq dtes64 monitor 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 cdp_l3 invpcid_single intel_ppin ssbd mba ibrs ibpb stibp ibrs_enhanced tpr_shadow vnmi flexpriority ept vpid ept_ad fsgsbase tsc_adjust bmi1 avx2 smep bmi2 erms invpcid cqm mpx rdt_a avx512f avx512dq rdseed adx smap clflushopt clwb intel_pt avx512cd avx512bw avx512vl xsaveopt xsavec xgetbv1 xsaves cqm_llc cqm_occup_llc cqm_mbm_total cqm_mbm_local dtherm ida arat pln pts pku ospke avx512_vnni md_clear flush_l1d arch_capabilities

Versions of relevant libraries: [pip3] mypy==0.931 [pip3] mypy-extensions==1.0.0 [pip3] numpy==1.24.1 [pip3] torch==2.0.1+cu117 [pip3] torchaudio==2.0.2+cu117 [pip3] torchvision==0.15.2+cu117 [conda] Could not collect xformers==0.0.21 accelerate==0.24.1

N.b. this happens only during evaluation:

with torch.cuda.amp.autocast():
    images = [
        pipeline(**pipeline_args, generator=generator).images[0]
        for _ in range(args.num_validation_images)
    ]

Thanks

[faceslog]

Any workaround ? I tried building locally xformers but still the same problem

[JakobLS]

This and this are likely related issues.