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Expected behavior
The program run in multi-node and print a result.
ds_report output
Please run ds_report to give us details about your setup.
DeprecationWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html import('pkg_resources').require('deepspeed==0.14.3+0fc19b6a')
[2024-05-16 21:46:15,312] [INFO] [real_accelerator.py:203:get_accelerator] Setting ds_accelerator to cuda (auto detect)
[2024-05-16 21:46:15,444] [INFO] [real_accelerator.py:203:get_accelerator] Setting ds_accelerator to cuda (auto detect)
[WARNING] async_io requires the dev libaio .so object and headers but these were not found.
[WARNING] async_io: please install the libaio-dev package with apt
[WARNING] If libaio is already installed (perhaps from source), try setting the CFLAGS and LDFLAGS environment variables to where it can be found.
[WARNING] Please specify the CUTLASS repo directory as environment variable $CUTLASS_PATH
[WARNING] NVIDIA Inference is only supported on Ampere and newer architectures
[WARNING] sparse_attn requires a torch version >= 1.5 and < 2.0 but detected 2.3
[WARNING] using untested triton version (2.3.0), only 1.0.0 is known to be compatible
DeepSpeed C++/CUDA extension op report
NOTE: Ops not installed will be just-in-time (JIT) compiled at
runtime if needed. Op compatibility means that your system
meet the required dependencies to JIT install the op.
[WARNING] async_io requires the dev libaio .so object and headers but these were not found.
[WARNING] async_io: please install the libaio-dev package with apt
[WARNING] If libaio is already installed (perhaps from source), try setting the CFLAGS and LDFLAGS environment variables to where it can be found.
async_io ............... [NO] ....... [NO]
fused_adam ............. [NO] ....... [OKAY]
cpu_adam ............... [NO] ....... [OKAY]
cpu_adagrad ............ [NO] ....... [OKAY]
cpu_lion ............... [NO] ....... [OKAY]
[WARNING] Please specify the CUTLASS repo directory as environment variable $CUTLASS_PATH
evoformer_attn ......... [NO] ....... [NO]
[WARNING] NVIDIA Inference is only supported on Ampere and newer architectures
fp_quantizer ........... [NO] ....... [NO]
fused_lamb ............. [NO] ....... [OKAY]
fused_lion ............. [NO] ....... [OKAY]
inference_core_ops ..... [NO] ....... [OKAY]
cutlass_ops ............ [NO] ....... [OKAY]
transformer_inference .. [NO] ....... [OKAY]
quantizer .............. [NO] ....... [OKAY]
ragged_device_ops ...... [NO] ....... [OKAY]
ragged_ops ............. [NO] ....... [OKAY]
random_ltd ............. [NO] ....... [OKAY]
[WARNING] sparse_attn requires a torch version >= 1.5 and < 2.0 but detected 2.3
[WARNING] using untested triton version (2.3.0), only 1.0.0 is known to be compatible
sparse_attn ............ [NO] ....... [NO]
spatial_inference ...... [NO] ....... [OKAY]
transformer ............ [NO] ....... [OKAY]
stochastic_transformer . [NO] ....... [OKAY]
DeepSpeed general environment info:
torch install path ............... ['/home/archlab/zyl/copy/jlq/anaconda3/lib/python3.11/site-packages/torch']
torch version .................... 2.3.0+cu121
deepspeed install path ........... ['/home/archlab/zyl/copy/jlq/project/DeepSpeed/deepspeed']
deepspeed info ................... 0.14.3+0fc19b6a, 0fc19b6, master
torch cuda version ............... 12.1
torch hip version ................ None
nvcc version ..................... 12.1
deepspeed wheel compiled w. ...... torch 2.3, cuda 12.1
shared memory (/dev/shm) size .... 125.89 GB
Screenshots
System info (please complete the following information):
OS: Ubuntu 18.04
GPU count and types: two machines with x2 V100s each
(if applicable) what DeepSpeed-MII version are you using
deepspeed==0.14.3+0fc19b6a
(if applicable) Hugging Face Transformers/Accelerate/etc. versions
transfomers ==4.40.2
accelerate==0.30.0
Python version:3.11
Any other relevant info about your setup
Docker context
Are you using a specific docker image that you can share?
Not use docker
Additional context
And there is error when I run the deepspeedExample in the same environment.
run the DeepSpeedExamples/inference/huggingface/text-generation/run-generation-script/test-gpt.sh
Error is
then I changed the parameter in deepspeed.init_inference
model = deepspeed.init_inference(model,
mp_size=1,
dtype=(torch.half if args.fp16 else torch.float),
replace_with_kernel_inject=True)
Then error is
What should I do if I want to use deepspeed in multi-node?
Thanks
The text was updated successfully, but these errors were encountered:
Describe the bug
The program is killed by timeout of watchdog when I run deepspeed on mutli-node.
To Reproduce
Steps to reproduce the behavior:
my code
Expected behavior
The program run in multi-node and print a result.
ds_report output
Please run
ds_report
to give us details about your setup.DeprecationWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html
import('pkg_resources').require('deepspeed==0.14.3+0fc19b6a')
[2024-05-16 21:46:15,312] [INFO] [real_accelerator.py:203:get_accelerator] Setting ds_accelerator to cuda (auto detect)
[2024-05-16 21:46:15,444] [INFO] [real_accelerator.py:203:get_accelerator] Setting ds_accelerator to cuda (auto detect)
[WARNING] async_io requires the dev libaio .so object and headers but these were not found.
[WARNING] async_io: please install the libaio-dev package with apt
[WARNING] If libaio is already installed (perhaps from source), try setting the CFLAGS and LDFLAGS environment variables to where it can be found.
[WARNING] Please specify the CUTLASS repo directory as environment variable $CUTLASS_PATH
[WARNING] NVIDIA Inference is only supported on Ampere and newer architectures
[WARNING] sparse_attn requires a torch version >= 1.5 and < 2.0 but detected 2.3
[WARNING] using untested triton version (2.3.0), only 1.0.0 is known to be compatible
DeepSpeed C++/CUDA extension op report
NOTE: Ops not installed will be just-in-time (JIT) compiled at
runtime if needed. Op compatibility means that your system
meet the required dependencies to JIT install the op.
JIT compiled ops requires ninja
ninja .................. [OKAY]
op name ................ installed .. compatible
[WARNING] async_io requires the dev libaio .so object and headers but these were not found.
[WARNING] async_io: please install the libaio-dev package with apt
[WARNING] If libaio is already installed (perhaps from source), try setting the CFLAGS and LDFLAGS environment variables to where it can be found.
async_io ............... [NO] ....... [NO]
fused_adam ............. [NO] ....... [OKAY]
cpu_adam ............... [NO] ....... [OKAY]
cpu_adagrad ............ [NO] ....... [OKAY]
cpu_lion ............... [NO] ....... [OKAY]
[WARNING] Please specify the CUTLASS repo directory as environment variable $CUTLASS_PATH
evoformer_attn ......... [NO] ....... [NO]
[WARNING] NVIDIA Inference is only supported on Ampere and newer architectures
fp_quantizer ........... [NO] ....... [NO]
fused_lamb ............. [NO] ....... [OKAY]
fused_lion ............. [NO] ....... [OKAY]
inference_core_ops ..... [NO] ....... [OKAY]
cutlass_ops ............ [NO] ....... [OKAY]
transformer_inference .. [NO] ....... [OKAY]
quantizer .............. [NO] ....... [OKAY]
ragged_device_ops ...... [NO] ....... [OKAY]
ragged_ops ............. [NO] ....... [OKAY]
random_ltd ............. [NO] ....... [OKAY]
[WARNING] sparse_attn requires a torch version >= 1.5 and < 2.0 but detected 2.3
[WARNING] using untested triton version (2.3.0), only 1.0.0 is known to be compatible
sparse_attn ............ [NO] ....... [NO]
spatial_inference ...... [NO] ....... [OKAY]
transformer ............ [NO] ....... [OKAY]
stochastic_transformer . [NO] ....... [OKAY]
DeepSpeed general environment info:
torch install path ............... ['/home/archlab/zyl/copy/jlq/anaconda3/lib/python3.11/site-packages/torch']
torch version .................... 2.3.0+cu121
deepspeed install path ........... ['/home/archlab/zyl/copy/jlq/project/DeepSpeed/deepspeed']
deepspeed info ................... 0.14.3+0fc19b6a, 0fc19b6, master
torch cuda version ............... 12.1
torch hip version ................ None
nvcc version ..................... 12.1
deepspeed wheel compiled w. ...... torch 2.3, cuda 12.1
shared memory (/dev/shm) size .... 125.89 GB
Screenshots
System info (please complete the following information):
deepspeed==0.14.3+0fc19b6a
transfomers ==4.40.2
accelerate==0.30.0
Docker context
Are you using a specific docker image that you can share?
Not use docker
Additional context
And there is error when I run the deepspeedExample in the same environment.
run the DeepSpeedExamples/inference/huggingface/text-generation/run-generation-script/test-gpt.sh
Error is
then I changed the parameter in deepspeed.init_inference
Then error is
What should I do if I want to use deepspeed in multi-node?
Thanks
The text was updated successfully, but these errors were encountered: