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[Bug] Nexfort isn't compatible with PyTorch 2.4.0 #1068

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mrrfr opened this issue Aug 6, 2024 · 10 comments
Open

[Bug] Nexfort isn't compatible with PyTorch 2.4.0 #1068

mrrfr opened this issue Aug 6, 2024 · 10 comments
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@mrrfr
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mrrfr commented Aug 6, 2024

Your current environment information

Unable to load nexfort.{extension} module. Is it compatible with your PyTorch installation?
Collecting environment information...
PyTorch version: 2.4.0+cu121
Is debug build: False
CUDA used to build PyTorch: 12.1
ROCM used to build PyTorch: N/A

OneFlow version: none
Nexfort version: none
OneDiff version: 1.2.1.dev12+g4bf583b5
OneDiffX version: 1.2.1.dev12+g4bf583b5

OS: Ubuntu 22.04.3 LTS (x86_64)
GCC version: (Ubuntu 11.4.0-1ubuntu1~22.04) 11.4.0
Clang version: Could not collect
CMake version: version 3.26.4
Libc version: glibc-2.35

Python version: 3.10.13 (main, Sep 11 2023, 13:44:35) [GCC 11.2.0] (64-bit runtime)
Python platform: Linux-5.15.0-94-generic-x86_64-with-glibc2.35
Is CUDA available: True
CUDA runtime version: 12.1.105
CUDA_MODULE_LOADING set to: LAZY
GPU models and configuration: GPU 0: NVIDIA A100-SXM4-40GB
Nvidia driver version: 535.154.05
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
Address sizes: 43 bits physical, 48 bits virtual
Byte Order: Little Endian
CPU(s): 64
On-line CPU(s) list: 0-63
Vendor ID: AuthenticAMD
Model name: AMD EPYC 7532 32-Core Processor
CPU family: 23
Model: 49
Thread(s) per core: 1
Core(s) per socket: 32
Socket(s): 2
Stepping: 0
Frequency boost: enabled
CPU max MHz: 2400.0000
CPU min MHz: 1500.0000
BogoMIPS: 4800.29
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 nopl nonstop_tsc cpuid extd_apicid aperfmperf rapl pni pclmulqdq monitor ssse3 fma cx16 sse4_1 sse4_2 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 ibrs ibpb stibp vmmcall fsgsbase bmi1 avx2 smep bmi2 cqm rdt_a rdseed adx smap clflushopt clwb sha_ni xsaveopt xsavec xgetbv1 cqm_llc cqm_occup_llc cqm_mbm_total cqm_mbm_local clzero irperf xsaveerptr rdpru wbnoinvd amd_ppin arat npt lbrv svm_lock nrip_save tsc_scale vmcb_clean flushbyasid decodeassists pausefilter pfthreshold avic v_vmsave_vmload vgif v_spec_ctrl umip rdpid overflow_recov succor smca sme sev sev_es
Virtualization: AMD-V
L1d cache: 2 MiB (64 instances)
L1i cache: 2 MiB (64 instances)
L2 cache: 32 MiB (64 instances)
L3 cache: 512 MiB (32 instances)
NUMA node(s): 2
NUMA node0 CPU(s): 0-31
NUMA node1 CPU(s): 32-63
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 Retbleed: Mitigation; untrained return thunk; SMT disabled
Vulnerability Spec rstack overflow: Mitigation; SMT disabled
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; Retpolines, IBPB conditional, STIBP disabled, RSB filling, PBRSB-eIBRS Not affected
Vulnerability Srbds: Not affected
Vulnerability Tsx async abort: Not affected

Versions of relevant libraries:
[pip3] diffusers==0.30.0.dev0
[pip3] numpy==1.26.3
[pip3] optree==0.10.0
[pip3] torch==2.4.0
[pip3] torchao==0.1
[pip3] torchaudio==2.4.0
[pip3] torchelastic==0.2.2
[pip3] torchvision==0.19.0
[pip3] transformers==4.43.4
[pip3] triton==3.0.0
[conda] blas 1.0 mkl
[conda] ffmpeg 4.3 hf484d3e_0 pytorch
[conda] libjpeg-turbo 2.0.0 h9bf148f_0 pytorch
[conda] mkl 2023.1.0 h213fc3f_46344
[conda] mkl-service 2.4.0 py310h5eee18b_1
[conda] mkl_fft 1.3.8 py310h5eee18b_0
[conda] mkl_random 1.2.4 py310hdb19cb5_0
[conda] numpy 1.26.3 py310h5f9d8c6_0
[conda] numpy-base 1.26.3 py310hb5e798b_0
[conda] optree 0.10.0 pypi_0 pypi
[conda] pytorch-cuda 12.1 ha16c6d3_5 pytorch
[conda] pytorch-mutex 1.0 cuda pytorch
[conda] torch 2.4.0 pypi_0 pypi
[conda] torchao 0.1 pypi_0 pypi
[conda] torchaudio 2.4.0 pypi_0 pypi
[conda] torchelastic 0.2.2 pypi_0 pypi
[conda] torchvision 0.19.0 pypi_0 pypi
[conda] triton 3.0.0 pypi_0 pypi

🐛 Describe the bug

I tried to execute Flux diffusers pipeline with Nexfort backend and Onediff and i have this error:

Unable to load nexfort.{extension} module. Is it compatible with your PyTorch installation?
Traceback (most recent call last):
  File "/workspace/main.py", line 164, in <module>
    main()
  File "/workspace/main.py", line 134, in main
    flux = FluxGenerator(args.model, compilerconfig, quantizeconfig)
  File "/workspace/main.py", line 87, in init
    self.pipe = self.compile_pipe(self.pipe, compiler_config)
  File "/workspace/main.py", line 120, in compile_pipe
    pipe.transformer = compile(pipe.transformer, backend="nexfort", options=options)
  File "/workspace/onediff/src/onediff/infer_compiler/backends/compiler.py", line 16, in compile
    model = backend(torch_module, options=options)
  File "/workspace/onediff/src/onediff/infer_compiler/backends/nexfort/nexfort.py", line 11, in compile
    from nexfort.compilers import nexfort_compile
  File "/opt/conda/lib/python3.10/site-packages/nexfort/__init.py", line 22, in <module>
    exec(f"import nexfort.{extension} as {extension}")
  File "<string>", line 1, in <module>
ImportError: /opt/conda/lib/python3.10/site-packages/nexfort/_C_inductor.cpython-310-x86_64-linux-gnu.so: undefined symbol: _ZN5torch3jit11parseSchemaERKSs

I have installed Nexfort with pip install -U nexfort

@mrrfr mrrfr added the Request-bug Something isn't working label Aug 6, 2024
@strint
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strint commented Aug 6, 2024

Nexfort version: none

This is not as expected.

https://pypi.org/project/nexfort/#history

it should be 0.1.dev261

@mrrfr
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mrrfr commented Aug 6, 2024 •
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Yes but when i retry (after upgrading torch & torchvision version) to pip install -U nexfort it seems to be good.

Here's the output, Did i miss something ?

Requirement already satisfied: nexfort in /opt/conda/lib/python3.10/site-packages (0.1.dev261)
Requirement already satisfied: packaging in /opt/conda/lib/python3.10/site-packages (from nexfort) (23.1)
Requirement already satisfied: torch in /opt/conda/lib/python3.10/site-packages (from nexfort) (2.4.0)
Requirement already satisfied: filelock in /opt/conda/lib/python3.10/site-packages (from torch->nexfort) (3.13.1)
Requirement already satisfied: typing-extensions>=4.8.0 in /opt/conda/lib/python3.10/site-packages (from torch->nexfort) (4.9.0)
Requirement already satisfied: sympy in /opt/conda/lib/python3.10/site-packages (from torch->nexfort) (1.12)
Requirement already satisfied: networkx in /opt/conda/lib/python3.10/site-packages (from torch->nexfort) (3.1)
Requirement already satisfied: jinja2 in /opt/conda/lib/python3.10/site-packages (from torch->nexfort) (3.1.2)
Requirement already satisfied: fsspec in /opt/conda/lib/python3.10/site-packages (from torch->nexfort) (2023.12.2)
Requirement already satisfied: nvidia-cuda-nvrtc-cu12==12.1.105 in /opt/conda/lib/python3.10/site-packages (from torch->nexfort) (12.1.105)
Requirement already satisfied: nvidia-cuda-runtime-cu12==12.1.105 in /opt/conda/lib/python3.10/site-packages (from torch->nexfort) (12.1.105)
Requirement already satisfied: nvidia-cuda-cupti-cu12==12.1.105 in /opt/conda/lib/python3.10/site-packages (from torch->nexfort) (12.1.105)
Requirement already satisfied: nvidia-cudnn-cu12==9.1.0.70 in /opt/conda/lib/python3.10/site-packages (from torch->nexfort) (9.1.0.70)
Requirement already satisfied: nvidia-cublas-cu12==12.1.3.1 in /opt/conda/lib/python3.10/site-packages (from torch->nexfort) (12.1.3.1)
Requirement already satisfied: nvidia-cufft-cu12==11.0.2.54 in /opt/conda/lib/python3.10/site-packages (from torch->nexfort) (11.0.2.54)
Requirement already satisfied: nvidia-curand-cu12==10.3.2.106 in /opt/conda/lib/python3.10/site-packages (from torch->nexfort) (10.3.2.106)
Requirement already satisfied: nvidia-cusolver-cu12==11.4.5.107 in /opt/conda/lib/python3.10/site-packages (from torch->nexfort) (11.4.5.107)
Requirement already satisfied: nvidia-cusparse-cu12==12.1.0.106 in /opt/conda/lib/python3.10/site-packages (from torch->nexfort) (12.1.0.106)
Requirement already satisfied: nvidia-nccl-cu12==2.20.5 in /opt/conda/lib/python3.10/site-packages (from torch->nexfort) (2.20.5)
Requirement already satisfied: nvidia-nvtx-cu12==12.1.105 in /opt/conda/lib/python3.10/site-packages (from torch->nexfort) (12.1.105)
Requirement already satisfied: triton==3.0.0 in /opt/conda/lib/python3.10/site-packages (from torch->nexfort) (3.0.0)
Requirement already satisfied: nvidia-nvjitlink-cu12 in /opt/conda/lib/python3.10/site-packages (from nvidia-cusolver-cu12==11.4.5.107->torch->nexfort) (12.6.20)
Requirement already satisfied: MarkupSafe>=2.0 in /opt/conda/lib/python3.10/site-packages (from jinja2->torch->nexfort) (2.1.3)
Requirement already satisfied: mpmath>=0.19 in /opt/conda/lib/python3.10/site-packages (from sympy->torch->nexfort) (1.3.0)
WARNING: Running pip as the 'root' user can result in broken permissions and conflicting behaviour with the system package manager. It is recommended to use a virtual environment instead: https://pip.pypa.io/warnings/venv```

@strint
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strint commented Aug 6, 2024 •
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A friend had the same problem, and he fixed this with torch 2.3.0

We will see the torch 2.4.0 problem later(torch 2.4.0 works in my env).

@mrrfr
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mrrfr commented Aug 6, 2024

Ok thank you :)

@Swarzox
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Swarzox commented Aug 10, 2024

A friend had the same problem, and he fixed this with torch 2.3.0

We will see the torch 2.4.0 problem later(torch 2.4.0 works in my env).

Could you please share your env so we can use onediff with torch 2.4.0

@Azru44
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Azru44 commented Aug 12, 2024

Ok thank you :)

did you find anything ? We are facing the same issue

@mrrfr
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mrrfr commented Aug 12, 2024

Ok thank you :)

did you find anything ? We are facing the same issue

Unfortunately, no. I saw that a new version of nexfort was released but it seems like it didn't work with pytorch 2.4.

@Swarzox
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Swarzox commented Aug 17, 2024

any update?

@strint
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strint commented Aug 19, 2024

Since pytorch 2.4 is released, nexfort package has been update to pytorch 2.4.0 and cuda 12.1: https://pypi.org/project/nexfort/

@Swarzox @mrrfr @Azru44

@liho00
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liho00 commented Nov 7, 2024 •
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how about torch 2.4.1 and 2.5? @strint

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@strint @Swarzox @liho00 @Azru44 @mrrfr