WEIGHT in Distributed Training Test with Deprecated torch.distributed.reduce_op

AnantGulati commented 3 weeks ago

🐛 Describe the bug

When attempting to run the distributed training test test_schedule_multiproc.py using the command:

Test file for pipeline parallelism having missing attribute. File: pytorch/test/distributed/pipelining/test_schedule_multiproc.py

ran with python3 test_schedule_multiproc.py

I encountered the following error message:

Traceback (most recent call last):
  File "/software/users/agulati/clean/pytorch/test/distributed/pipelining/test_schedule_multiproc.py", line 10, in <module>
    from schedule_registry import ScheduleUnbalanced, ScheduleVShaped, ScheduleWithW
  File "/software/users/agulati/clean/pytorch/test/distributed/pipelining/schedule_registry.py", line 17, in <module>
    W = _ComputationType.WEIGHT
        ^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/conda/lib/python3.11/enum.py", line 786, in __getattr__
    raise AttributeError(name) from None
AttributeError: WEIGHT

This indicates that the WEIGHT attribute is not found in the _ComputationType enum,

please advise cc @XilunWu @H-Huang @awgu @kwen2501 @wanchaol @fegin @fduwjj @wz337 @wconstab @d4l3k @c-p-i-o

Versions

Collecting environment information... PyTorch version: 2.4.0 Is debug build: False CUDA used to build PyTorch: 11.8 ROCM used to build PyTorch: N/A

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: 3.11.9 (main, Apr 19 2024, 16:48:06) [GCC 11.2.0] (64-bit runtime) Python platform: Linux-5.15.0-117-generic-x86_64-with-glibc2.35 Is CUDA available: True CUDA runtime version: 11.8.89 CUDA_MODULE_LOADING set to: LAZY GPU models and configuration: GPU 0: NVIDIA TITAN Xp GPU 1: NVIDIA TITAN Xp GPU 2: NVIDIA TITAN Xp GPU 3: NVIDIA TITAN Xp GPU 4: NVIDIA TITAN Xp GPU 5: NVIDIA TITAN Xp GPU 6: NVIDIA TITAN Xp GPU 7: NVIDIA TITAN Xp

Nvidia driver version: 550.90.07 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 Address sizes: 46 bits physical, 48 bits virtual Byte Order: Little Endian CPU(s): 112 On-line CPU(s) list: 0-111 Vendor ID: GenuineIntel Model name: Intel(R) Xeon(R) Gold 6258R CPU @ 2.70GHz CPU family: 6 Model: 85 Thread(s) per core: 2 Core(s) per socket: 28 Socket(s): 2 Stepping: 7 CPU max MHz: 4000.0000 CPU min MHz: 1000.0000 BogoMIPS: 5400.00 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 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 Virtualization: VT-x L1d cache: 1.8 MiB (56 instances) L1i cache: 1.8 MiB (56 instances) L2 cache: 56 MiB (56 instances) L3 cache: 77 MiB (2 instances) NUMA node(s): 2 NUMA node0 CPU(s): 0-27,56-83 NUMA node1 CPU(s): 28-55,84-111 Vulnerability Gather data sampling: Mitigation; Microcode Vulnerability Itlb multihit: KVM: Mitigation: VMX disabled Vulnerability L1tf: Not affected Vulnerability Mds: Not affected Vulnerability Meltdown: Not affected Vulnerability Mmio stale data: Mitigation; Clear CPU buffers; SMT vulnerable Vulnerability Reg file data sampling: Not affected Vulnerability Retbleed: Mitigation; Enhanced IBRS Vulnerability Spec rstack overflow: 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 / Automatic IBRS; IBPB conditional; RSB filling; PBRSB-eIBRS SW sequence; BHI SW loop, KVM SW loop Vulnerability Srbds: Not affected Vulnerability Tsx async abort: Mitigation; TSX disabled

Versions of relevant libraries: [pip3] numpy==1.26.4 [pip3] optree==0.12.1 [pip3] torch==2.4.0 [pip3] torchaudio==2.4.0 [pip3] torchelastic==0.2.2 [pip3] torchvision==0.19.0 [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 py311h5eee18b_1
[conda] mkl_fft 1.3.8 py311h5eee18b_0
[conda] mkl_random 1.2.4 py311hdb19cb5_0
[conda] numpy 1.26.4 py311h08b1b3b_0
[conda] numpy-base 1.26.4 py311hf175353_0
[conda] optree 0.12.1 pypi_0 pypi [conda] pytorch 2.4.0 py3.11_cuda11.8_cudnn9.1.0_0 pytorch [conda] pytorch-cuda 11.8 h7e8668a_5 pytorch [conda] pytorch-mutex 1.0 cuda pytorch [conda] torchaudio 2.4.0 py311_cu118 pytorch [conda] torchelastic 0.2.2 pypi_0 pypi [conda] torchtriton 3.0.0 py311 pytorch [conda] torchvision 0.19.0 py311_cu118 pytorch

awgu commented 3 weeks ago

cc: @H-Huang @kwen2501 @wconstab

H-Huang commented 2 weeks ago

I think this is similar reason as the comment in https://github.com/pytorch/pytorch/issues/134450#issuecomment-2313484634. I think you are running tests from the main/current developed branch, when you should be running tests from whatever your pytorch version is.

If you would like to run the current main branch test please look into these instructions to develop pytorch locally: https://github.com/pytorch/pytorch?tab=readme-ov-file#install-pytorch

pytorch / pytorch

WEIGHT in Distributed Training Test with Deprecated torch.distributed.reduce_op #134218

🐛 Describe the bug

Versions