Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Some tensorflow warning/error messages when running Helixer via Singularity #123

Open
spoonbender76 opened this issue Apr 11, 2024 · 3 comments

Comments

@spoonbender76
Copy link

Hi, I'm running Helixer v0.3.3 via Singularity v4.0.3
singularity pull docker://gglyptodon/helixer-docker:helixer_v0.3.3_cuda_11.8.0-cudnn8
singularity run --nv helixer-docker_helixer_v0.3.3_cuda_11.8.0-cudnn8.sif Helixer.py --fasta-path Nm.softmasked.fa --lineage invertebrate --gff-output-path Nm_helixer.gff3 --batch-size 8

Can I safely ignore these TensorFlow warnings/error messages, or might they affect performance/results?

setting self.n_seqs to 4932, bc that is len of data/X
2024-04-11 11:40:25.627235: I tensorflow/compiler/xla/stream_executor/cuda/cuda_dnn.cc:432] Loaded cuDNN version 8906
2024-04-11 11:40:28.342978: I tensorflow/tsl/platform/default/subprocess.cc:304] Start cannot spawn child process: Permission denied
2024-04-11 11:40:28.344534: I tensorflow/tsl/platform/default/subprocess.cc:304] Start cannot spawn child process: Permission denied
2024-04-11 11:40:28.344551: W tensorflow/compiler/xla/stream_executor/gpu/asm_compiler.cc:109] Couldn't get ptxas version : FAILED_PRECONDITION: Couldn't get ptxas/nvlink version string: INTERNAL: Couldn't invoke ptxas --version
2024-04-11 11:40:28.346127: I tensorflow/tsl/platform/default/subprocess.cc:304] Start cannot spawn child process: Permission denied
2024-04-11 11:40:28.346192: W tensorflow/compiler/xla/stream_executor/gpu/redzone_allocator.cc:318] INTERNAL: Failed to launch ptxas
Relying on driver to perform ptx compilation. 
Modify $PATH to customize ptxas location.
This message will be only logged once.
@haessar
Copy link

haessar commented Apr 19, 2024

I'm encountering similar when training a model with HybridModel.py using Apptainer v1.1.8 (rebranded Singularity) with the latest Docker container (helixer-docker:helixer_v0.3.3_cuda_11.8.0-cudnn8). Now worrying that my model training is running sub-optimally (i.e. slow), so would appreciate a response.

@Jiangjiangzhang6
Copy link

I met the same error,.

I'm encountering similar when training a model with HybridModel.py using Apptainer v1.1.8 (rebranded Singularity) with the latest Docker container (helixer-docker:helixer_v0.3.3_cuda_11.8.0-cudnn8). Now worrying that my model training is running sub-optimally (i.e. slow), so would appreciate a response.

i met the same error , but i didnot have the root ,just to use the singularity,

@alisandra
Copy link
Collaborator

Hi, thanks for raising, will check out these errors more closely for the next release. I strongly suspect you can ignore them.

Helixer should run on the order of magnitude of 100mbp of genome/30min (or faster, hardware, batch size and gene density dependent). If it's much slower than that, then please let us know, that would be unexpectedly slow and might be running on the CPU instead of GPU.

Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
Labels
None yet
Projects
None yet
Development

No branches or pull requests

4 participants