Comments (1)
This changed a bit between the tf1 and tf2 versions, and I know you're moving to tf2 from the other thread, so I'll hold off to give specific advice. Generally, num_targets in the parameters file is meant to help guide the model construction during training. I wrote the --ti option in basenji_test.py to allow me to write bigwigs for just a few of the many targets. So you can ignore it if you want to write all targets.
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Related Issues (20)
- No checkpoints found. HOT 3
- "When the bin size needs to be adjusted (e.g. from 128 to 100), how should I design the optimal pooling kernel size?" HOT 2
- Can I apply Basenji's series of functions to the Enformer model? HOT 2
- fasta file of saluki_predict_fasta.py HOT 1
- train/test/valid sequences for predetermined regions HOT 2
- failed running "basenji_sat_bed.py" in tutorials HOT 4
- Basenji Features used for Whole Blood Fine-Mapping HOT 3
- Issue running basenji_data.py HOT 2
- Blacklist file & unmappable regions HOT 2
- question about clip threshold in basenji/enformer. HOT 2
- Training with multiple directories HOT 1
- Problem with multigenome training with > 2 genomes HOT 1
- Tensorflow records generated with basenji_data.py differ from original HOT 1
- akita can't train HOT 1
- Question about Gene Expression Training Preprocessing HOT 3
- pygene installation HOT 2
- Question about Basenji2 receptive field HOT 2
- How to prepare TFRecords files for saluki training HOT 1
- error with akita_data. py HOT 3
- Output regions from Akita HOT 1
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