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vocab not being written correctly #27

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ajtritt opened this issue Feb 22, 2021 · 0 comments
Open

vocab not being written correctly #27

ajtritt opened this issue Feb 22, 2021 · 0 comments
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ajtritt commented Feb 22, 2021

In a DeepIndexFile that is currently sitting on Cori at $CSCRATCH/exabiome/deep-index/input/gtdb/r95/ar122_r95.input.h5, the vocabulary attribute on seq_table/sequence was [A T C G N], when it should be [A C Y W S K D V N T G R W S M H B N].

This attribute should get set during conversion here:

vocab = np.array(list(vocab_it.characters()))

According to this line, the correct vocabulary should be returned:

chars = ('ACYWSKDVN'
'TGRWSMHBN')

@ajtritt ajtritt self-assigned this Feb 22, 2021
ajtritt added a commit that referenced this issue Mar 2, 2021
ajtritt added a commit that referenced this issue Mar 5, 2021
* add function to extract profile data

* add assert to catch bad vocab. See #27

* add command to give dataset info

* Clean up some things

- clean up argparse arguments
- use CSV logger
- always use DDP. Remove SLURM/LSF support (until PL stabilizes)

* clean up job sumission

* update base model to work with PL

* improve chunking efficiency

* add command to exec

* remove name from environment

* remove read of downsample
ajtritt added a commit that referenced this issue Mar 5, 2021
* add function to extract profile data

* add assert to catch bad vocab. See #27

* add command to give dataset info

* Clean up some things

- clean up argparse arguments
- use CSV logger
- always use DDP. Remove SLURM/LSF support (until PL stabilizes)

* clean up job sumission

* update base model to work with PL

* improve chunking efficiency

* add command to exec

* remove name from environment

* remove read of downsample

* add classifier for ResNet feature models

* add options for using classifier

* add sensible statement for recurring error

* work out kinks in ResNet classifier

* add options for job submission script

* set model subdirectory if starting classification from features

* Resume from checkpoint of ResNetClassifier

- Use LightningDataModule so we can determine number of model outputs before initializing model

* clean up to make checkpointing and adding classifer work

* Clean up for Cori (#28)

* add function to extract profile data

* add assert to catch bad vocab. See #27

* add command to give dataset info

* Clean up some things

- clean up argparse arguments
- use CSV logger
- always use DDP. Remove SLURM/LSF support (until PL stabilizes)

* clean up job sumission

* update base model to work with PL

* improve chunking efficiency

* add command to exec

* remove name from environment

* remove read of downsample

* add arguments to job runner

* add classifier for ResNet feature models

* add options for using classifier

* add sensible statement for recurring error

* work out kinks in ResNet classifier

* add options for job submission script

* set model subdirectory if starting classification from features

* Resume from checkpoint of ResNetClassifier

- Use LightningDataModule so we can determine number of model outputs before initializing model

* clean up to make checkpointing and adding classifer work

* add arguments to job runner

* add field that was missing after restarting from checkpoint
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