Comments (6)
@gevro thank you for reporting. Can you share the command you are running?
from deepconsensus.
singularity run -W /data -B /scratch/projects/bin/deepconsensus/model:/model -B `pwd` /scratch/projects/bin/deepconsensus/deepconsensus_1.0.0.sif deepconsensus run --batch_size=1024 --batch_zmws=100 --cpus 4 --max_passes 20 --subreads_to_ccs=subreads_to_ccs.bam --ccs_bam=ccs.bam --checkpoint=/model/checkpoint --output=output.deepconsensus.fastq
from deepconsensus.
@gevro please try running singularity with a clean environment. I think passing --cleanenv
should work.
singularity run \
-W /data \
-B /scratch/projects/bin/deepconsensus/model:/model \
-B `pwd` \
--cleanenv \
/scratch/projects/bin/deepconsensus/deepconsensus_1.0.0.sif \
deepconsensus run \
--batch_size=1024 \
--batch_zmws=100 \
--cpus 4 \
--max_passes 20 \
--subreads_to_ccs=subreads_to_ccs.bam \
--ccs_bam=ccs.bam \
--checkpoint=/model/checkpoint \
--output=output.deepconsensus.fastq
For whatever reason, it appears you are using a shared version of the python library from your machine/HPC:
/share/apps/python/3.8.6/intel/lib/python3.8/site-packages/pandas/__init__.py
And this appears to be breaking things.
from deepconsensus.
Now I'm getting this error:
2022-10-11 17:08:33.096036: I tensorflow/core/platform/cpu_feature_guard.cc:193] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN) to use the following CPU instructions in performance-critical operations: AVX2 AVX512F AVX512_VNNI FMA
To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.
FATAL Flags parsing error: Unknown command line flag 'max_passes'
Pass --helpshort or --helpfull to see help on flags.
from deepconsensus.
We removed the --max_passes
flag in this release because we have not provided any models with alternative numbers of passes. Please try removing this flag:
singularity run \
-W /data \
-B /scratch/projects/bin/deepconsensus/model:/model \
-B `pwd` \
--cleanenv \
/scratch/projects/bin/deepconsensus/deepconsensus_1.0.0.sif \
deepconsensus run \
--batch_size=1024 \
--batch_zmws=100 \
--cpus 4 \
--subreads_to_ccs=subreads_to_ccs.bam \
--ccs_bam=ccs.bam \
--checkpoint=/model/checkpoint \
--output=output.deepconsensus.fastq
Also - the --max_passes
, and --example_width
flags are now dictated by the model params.json - so there is no need to set these flags.
from deepconsensus.
Ok working now. Thanks.
from deepconsensus.
Related Issues (20)
- Lower number of >Q30 average quality reads for v1.1 compared to v0.3 HOT 10
- Error detecting params.json using docker in debian (10) HPC HOT 2
- Installation from source file problem HOT 2
- lower quality and less reads in deepconsensus 1.0 output compared to ccs HOT 2
- python 3.9 HOT 2
- [Repeat] Running deepconsensus results in "free(): invalid pointer" error HOT 17
- QV for each ccs reads HOT 2
- Public raw train dataset availability HOT 2
- Cannot open/create ccs.bam file? HOT 6
- vRAM limit HOT 1
- the label without alignment HOT 5
- bam or fastq issue HOT 2
- Separate subreads for mixed samples? HOT 3
- GPU installation failure with pip HOT 3
- GPU installation using quick start guide fails HOT 5
- OSError: error -3 while reading file HOT 8
- normal pass / fail rate? HOT 2
- KeyError HOT 5
- About making ground truth. HOT 2
- Optimizing runtime on HPC HOT 2
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from deepconsensus.