Not able to fietune on single node multiple gpu

[aaekay]

System Info

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 20.04.1 LTS (x86_64)
GCC version: (Ubuntu 9.3.0-17ubuntu1~20.04) 9.3.0
Clang version: Could not collect
CMake version: version 3.27.0
Libc version: glibc-2.31

Python version: 3.11.4 | packaged by conda-forge | (main, Jun 10 2023, 18:08:17) [GCC 12.2.0] (64-bit runtime)
Python platform: Linux-5.13.0-28-generic-x86_64-with-glibc2.31
Is CUDA available: True
CUDA runtime version: 11.0.194
CUDA_MODULE_LOADING set to: LAZY
GPU models and configuration:
GPU 0: NVIDIA A100-SXM4-40GB
GPU 1: NVIDIA A100-SXM4-40GB
GPU 2: NVIDIA A100-SXM4-40GB
GPU 3: NVIDIA A100-SXM4-40GB
GPU 4: NVIDIA A100-SXM4-40GB
GPU 5: NVIDIA A100-SXM4-40GB
GPU 6: NVIDIA A100-SXM4-40GB
GPU 7: NVIDIA A100-SXM4-40GB

Nvidia driver version: 470.103.01
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: 43 bits physical, 48 bits virtual
CPU(s): 64
On-line CPU(s) list: 0-63
Thread(s) per core: 2
Core(s) per socket: 16
Socket(s): 2
NUMA node(s): 2
Vendor ID: AuthenticAMD
CPU family: 23
Model: 49
Model name: AMD EPYC 7282 16-Core Processor
Stepping: 0
Frequency boost: enabled
CPU MHz: 3195.310
CPU max MHz: 2800.0000
CPU min MHz: 1500.0000
BogoMIPS: 5600.46
Virtualization: AMD-V
L1d cache: 1 MiB
L1i cache: 1 MiB
L2 cache: 16 MiB
L3 cache: 128 MiB
NUMA node0 CPU(s): 0-15,32-47
NUMA node1 CPU(s): 16-31,48-63
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; Full AMD retpoline, IBPB conditional, IBRS_FW, STIBP 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 mmx fxsr sse sse2 ht syscall nx mmxext fxsr_opt pdpe1gb rdtscp lm constant_tsc rep_good nopl nonstop_tsc cpuid extd_apicid aperfmperf 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 xsaves 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

Versions of relevant libraries:
[pip3] numpy==1.25.1
[pip3] torch==2.0.1
[pip3] torch-tb-profiler==0.4.1
[pip3] torchvision==0.15.2
[conda] numpy 1.25.1 pypi_0 pypi
[conda] torch 2.0.1 pypi_0 pypi
[conda] torch-tb-profiler 0.4.1 pypi_0 pypi
[conda] torchvision 0.15.2 pypi_0 pypi

Information

• The official example scripts
• My own modified scripts

🐛 Describe the bug

Tried running torchrun for single node and multigpu but the process exists

Error logs

--> Running with torch dist debug set to detail
WARNING:torch.distributed.elastic.multiprocessing.api:Sending process 611719 closing signal SIGTERM
WARNING:torch.distributed.elastic.multiprocessing.api:Sending process 611720 closing signal SIGTERM
ERROR:torch.distributed.elastic.multiprocessing.api:failed (exitcode: -9) local_rank: 2 (pid: 611721) of binary: /home/amit_g/scratch/env/llm/bin/python
Traceback (most recent call last):
File "/home/amit_g/scratch/env/llm/bin/torchrun", line 8, in
sys.exit(main())
^^^^^^
File "/home/amit_g/scratch/env/llm/lib/python3.11/site-packages/torch/distributed/elastic/multiprocessing/errors/init.py", line 346, in wrapper
return f(*args, **kwargs)
^^^^^^^^^^^^^^^^^^
File "/home/amit_g/scratch/env/llm/lib/python3.11/site-packages/torch/distributed/run.py", line 794, in main
run(args)
File "/home/amit_g/scratch/env/llm/lib/python3.11/site-packages/torch/distributed/run.py", line 785, in run
elastic_launch(
File "/home/amit_g/scratch/env/llm/lib/python3.11/site-packages/torch/distributed/launcher/api.py", line 134, in call
return launch_agent(self._config, self._entrypoint, list(args))
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/home/amit_g/scratch/env/llm/lib/python3.11/site-packages/torch/distributed/launcher/api.py", line 250, in launch_agent
raise ChildFailedError(
torch.distributed.elastic.multiprocessing.errors.ChildFailedError:

./llama_finetuning.py FAILED

Failures:
<NO_OTHER_FAILURES>

Root Cause (first observed failure):
[0]:
time : 2023-08-09_02:46:25
host : user
rank : 2 (local_rank: 2)
exitcode : -9 (pid: 611721)
error_file: <N/A>
traceback : Signal 9 (SIGKILL) received by PID 611721

Expected behavior

i expected it to train

[HamidShojanazeri]

@aaekay can you pls share the command/ setting (how many GPU/ what type) you are running. Also please note if you are using FSDP + PEFT you need to install PyTorch nightlies.

[aaekay]

@HamidShojanazeri and after using the nightly pytorch , showing similar error:

"""
File "/home/amit_g/scratch/env/llm/bin/torchrun", line 33, in
sys.exit(load_entry_point('torch==2.1.0.dev20230808', 'console_scripts', 'torchrun')())
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/home/amit_g/scratch/env/llm/lib/python3.11/site-packages/torch/distributed/elastic/multiprocessing/errors/init.py", line 346, in wrapper
return f(*args, **kwargs)
^^^^^^^^^^^^^^^^^^
File "/home/amit_g/scratch/env/llm/lib/python3.11/site-packages/torch/distributed/run.py", line 806, in main
run(args)
File "/home/amit_g/scratch/env/llm/lib/python3.11/site-packages/torch/distributed/run.py", line 797, in run
elastic_launch(
File "/home/amit_g/scratch/env/llm/lib/python3.11/site-packages/torch/distributed/launcher/api.py", line 134, in call
return launch_agent(self._config, self._entrypoint, list(args))
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/home/amit_g/scratch/env/llm/lib/python3.11/site-packages/torch/distributed/launcher/api.py", line 264, in launch_agent
raise ChildFailedError(
torch.distributed.elastic.multiprocessing.errors.ChildFailedError:
"""

I am using the below command
torchrun --nnodes 1
--nproc_per_node 3
--rdzv_endpoint=localhost:1800
./llama_finetuning.py
--enable_fsdp
--use_peft
--peft_method lora
--dataset inhouse_dataset
--batch_size_training 2
--num_epochs 10
--model_name ../llama/models_hf/70B
--pure_bf16
--output_dir ./tmp/70B

[HamidShojanazeri]

@aaekay I believe you would a bigger compute resources to run the 70B model. Given enough compute, please make use of this PR to bypass the CPU OOM that you would potentially ran into.

[HamidShojanazeri]

It seems be stale, closing this pls feel free to re-open if still seeing the issue.