Comments (5)
@bcantarel what type of machine are you running this on? I wonder if DeepVariant is resource-constrained.
What do you get when you type nproc
? Can you try to lower the value of --num_shards
to this value if it is lower?
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I tried on both an e2-highmem-16 and nd2-highmem-96, so that's 16 and 96 cpus, I saw this in both instances. when running deep-variant I set num_shards to $(nproc)
from deepvariant.
@bcantarel Thank you for flagging this. I was able to reproduce this issue as well. While we investigate further, you can revert back to DeepVariant 1.4. I tested v1.4 and had no issues running the RNA-seq model. Note that we have only released one RNA-seq model.
We'll continue to look into this and try to resolve it.
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Please use "1.5.0" for the RNA-seq model as it is trained with slim. Version 1.6.0 only works with Keras models.
from deepvariant.
Hi @bcantarel ,
I hope using the right version resolved your issue. Closing this now.
from deepvariant.
Related Issues (20)
- Issue calling make_examples.py HOT 2
- Maintain Barcode in Output HOT 6
- The step of postprocess_variants cannot find the VCF file HOT 2
- Running error with deepvariant_1.6.0-gpu.sif HOT 3
- ouput variants from tool HOT 6
- Not all shards generated HOT 5
- The model files model/model.ckpt* do not exist HOT 4
- Compatibility of GATK4 gVCF files with DeepVariant for joint calling HOT 2
- DeepTrio from 1.6.0 : how to isolate de novo calls from trio VCF ? HOT 3
- Errors running DeepVariant with Singularity
- RNA-seq model compatibility HOT 2
- Error running DeepVariant HOT 4
- Error running DeepVariant via singularity HOT 7
- Somatic and germline variants HOT 3
- model_type for ONT WGS data HOT 1
- Parallel execution of DeepVariant fails when using CRAM alignment files. HOT 3
- Question about retraining DeepVariant HOT 2
- Don't use nvidia-tensorrt. Instead specify version with tensorrt==8.5.3.1 HOT 4
- Question: How to train using custom tags in BAM as features? HOT 2
- RNA-seq pre-processing HOT 4
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