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siliconflow / onediff

OneDiff: An out-of-the-box acceleration library for diffusion models.
https://github.com/siliconflow/onediff/wiki
Apache License 2.0
1.71k stars 105 forks source link

[Bug] switch lora error #1130

Open xiecon opened 3 weeks ago

xiecon commented 3 weeks ago

Your current environment information

ENV

PyTorch version: 2.4.1+cu121 Is debug build: False CUDA used to build PyTorch: 12.1 ROCM used to build PyTorch: N/A

OneFlow version: path: ['/opt/conda/envs/comfyui/lib/python3.10/site-packages/oneflow'], version: 0.9.1.dev20240802+cu118, git_commit: d23c061, cmake_build_type: Release, rdma: True, mlir: True, enterprise: False Nexfort version: none OneDiff version: 1.2.1.dev24+g9231f556 OneDiffX version: none

OS: Ubuntu 20.04.6 LTS (x86_64) GCC version: (Ubuntu 9.4.0-1ubuntu1~20.04.1) 9.4.0 Clang version: Could not collect CMake version: version 3.26.4 Libc version: glibc-2.31

Python version: 3.10.15 (main, Oct 3 2024, 07:27:34) [GCC 11.2.0] (64-bit runtime) Python platform: Linux-5.10.0-1.0.0.28-x86_64-with-glibc2.31 Is CUDA available: True CUDA runtime version: 11.8.89 CUDA_MODULE_LOADING set to: LAZY GPU models and configuration: GPU 0: NVIDIA A100-SXM4-80GB GPU 1: NVIDIA A100-SXM4-80GB GPU 2: NVIDIA A100-SXM4-80GB GPU 3: NVIDIA A100-SXM4-80GB GPU 4: NVIDIA A100-SXM4-80GB GPU 5: NVIDIA A100-SXM4-80GB GPU 6: NVIDIA A100-SXM4-80GB GPU 7: NVIDIA A100-SXM4-80GB

Nvidia driver version: 525.125.06 cuDNN version: Probably one of the following: /usr/lib/x86_64-linux-gnu/libcudnn.so.8.9.0 /usr/lib/x86_64-linux-gnu/libcudnn_adv_infer.so.8.9.0 /usr/lib/x86_64-linux-gnu/libcudnn_adv_train.so.8.9.0 /usr/lib/x86_64-linux-gnu/libcudnn_cnn_infer.so.8.9.0 /usr/lib/x86_64-linux-gnu/libcudnn_cnn_train.so.8.9.0 /usr/lib/x86_64-linux-gnu/libcudnn_ops_infer.so.8.9.0 /usr/lib/x86_64-linux-gnu/libcudnn_ops_train.so.8.9.0 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, 57 bits virtual CPU(s): 128 On-line CPU(s) list: 0-127 Thread(s) per core: 2 Core(s) per socket: 32 Socket(s): 2 NUMA node(s): 2 Vendor ID: GenuineIntel CPU family: 6 Model: 106 Model name: Intel(R) Xeon(R) Platinum 8350C CPU @ 2.60GHz Stepping: 6 Frequency boost: enabled CPU MHz: 3044.888 CPU max MHz: 3500.0000 CPU min MHz: 800.0000 BogoMIPS: 5200.00 Virtualization: VT-x L1d cache: 3 MiB L1i cache: 2 MiB L2 cache: 80 MiB L3 cache: 96 MiB NUMA node0 CPU(s): 0-31,64-95 NUMA node1 CPU(s): 32-63,96-127 Vulnerability Itlb multihit: Not affected Vulnerability L1tf: Not affected Vulnerability Mds: Not affected Vulnerability Meltdown: Not affected 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 Vulnerability Srbds: Not affected Vulnerability Tsx async abort: Not affected 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 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 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 wbnoinvd dtherm ida arat pln pts avx512vbmi umip pku avx512_vbmi2 gfni vaes vpclmulqdq avx512_vnni avx512_bitalg tme avx512_vpopcntdq rdpid fsrm md_clear pconfig flush_l1d arch_capabilities

Versions of relevant libraries: [pip3] diffusers==0.30.3 [pip3] numpy==1.26.4 [pip3] onnx==1.17.0 [pip3] onnxruntime==1.19.2 [pip3] onnxruntime-gpu==1.19.2 [pip3] open_clip_torch==2.27.1 [pip3] torch==2.4.1 [pip3] torchaudio==2.4.1 [pip3] torchsde==0.2.6 [pip3] torchvision==0.19.1 [pip3] transformers==4.45.2 [pip3] triton==3.0.0 [conda] numpy 1.26.4 pypi_0 pypi [conda] open-clip-torch 2.27.1 pypi_0 pypi [conda] torch 2.4.1 pypi_0 pypi [conda] torchaudio 2.4.1 pypi_0 pypi [conda] torchsde 0.2.6 pypi_0 pypi [conda] torchvision 0.19.1 pypi_0 pypi [conda] triton 3.0.0 pypi_0 pypi

IPA version: 78ac59c61c8caf33e3419d2c8f70838b2da0fb04 ComfyUI version: 2759191a0d

🐛 Describe the bug

ERROR

This error message will appear when switching lora behavior during batch testing.

[ERROR](GRAPH:OneflowGraph_12:OneflowGraph) run got error: <class 'oneflow._oneflow_internal.exception.RuntimeError'> Error: Reshape infered output element count is different with input in op_name: model.output_blocks.5.1.transformer_blocks.0-reshape-743 input shape is : (1,257,1280) , output shape is : (1,4,1280) , output logical shape is (1,4,1280) , and reshape shape conf is : (1,4,1280) op_loc: 

ERROR [2024-10-31 03:14:40] ../comfyui/onediff/src/onediff/infer_compiler/backends/oneflow/deployable_module.py:44 - Exception in forward: e=RuntimeError('\x1b[1m\x1b[38;2;255;000;000mError\x1b[0m: Reshape infered output element count is different with input in op_name: model.output_blocks.5.1.transformer_blocks.0-reshape-743 input shape is : (1,257,1280) , output shape is : (1,4,1280) , output logical shape is (1,4,1280) , and reshape shape conf is : (1,4,1280) op_loc: \n')