Comments (2)
i met the same problem using the docker image, with Python 2.7.6.
But seems to be solved by editing the file Basset/src/seq_hdf5.py, line 81-89,
adding int() to test_count, train_count and valid_count
train_count = seqs.shape[0] - test_count - valid_count
train_count = int(batch_round(train_count, options.batch_size))
print >> sys.stderr, '%d training sequences ' % train_count
test_count = int(batch_round(test_count, options.batch_size))
print >> sys.stderr, '%d test sequences ' % test_count
valid_count = int(batch_round(valid_count, options.batch_size))
print >> sys.stderr, '%d validation sequences ' % valid_count
from basset.
I guess the error in line 92 of current seq_hdf5.py while running python 2.7.5 is related. Onceupon, could your request a pull?
[ca445@cbsugpu01 bassetfiles]$ python /usr/local/Basset-0.1.0/src/seq_hdf5.py -r -c -v 3000 -t 3000 learn_cd4.fa lt.txt learn_cd4.h5
85261 training sequences
3000 test sequences
3000 validation sequences
Traceback (most recent call last):
File "/usr/local/Basset-0.1.0/src/seq_hdf5.py", line 130, in <module>
main()
File "/usr/local/Basset-0.1.0/src/seq_hdf5.py", line 92, in main
train_seqs, train_targets = seqs[i:i+train_count,:], targets[i:i+train_count,:]
TypeError: slice indices must be integers or None or have an __index__ method
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Related Issues (20)
- Training aways converges after 2 or 3 epochs HOT 4
- Training takes too long HOT 3
- Pre-trained Weights? HOT 1
- Torch-HDF5 Failure during Writing Output by basset_motifs_predict.lua HOT 3
- First Epoch Loss is Bigger than Expected HOT 2
- Nucleotide Order in Motif Heatmap Reversed HOT 1
- how are filters combined HOT 2
- Error in running basset_sat_vcf.py HOT 1
- Convolutional layers - padding and bias HOT 1
- input and target size mismatch when running test.lua HOT 3
- Citation on README HOT 1
- Prediction tasks specification HOT 1
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- how to install 'convnet' module HOT 1
- ENUM error when running basset_train.lua HOT 7
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from basset.