Traceback (most recent call last):


 "/usr/local/bin/bcbio_nextgen.py", line 234, in <module>

main(**kwargs)


 "/usr/local/bin/bcbio_nextgen.py", line 43, in main

run_main(**kwargs)


 "/usr/local/share/bcbio/anaconda/lib/python2.7/site-packages/bcbio/pipeline/main.py", line 42, in run_main

fc_dir, run_info_yaml)


 "/usr/local/share/bcbio/anaconda/lib/python2.7/site-packages/bcbio/pipeline/main.py", line 86, in _run_toplevel

for xs in pipeline(config, run_info_yaml, parallel, dirs, samples):


 "/usr/local/share/bcbio/anaconda/lib/python2.7/site-packages/bcbio/pipeline/main.py", line 119, in variant2pipeline

[x[0]["description"] for x in samples]]])


 "/usr/local/share/bcbio/anaconda/lib/python2.7/site-packages/bcbio/distributed/multi.py", line 28, in run_parallel

return run_multicore(fn, items, config, parallel=parallel)


 "/usr/local/share/bcbio/anaconda/lib/python2.7/site-packages/bcbio/distributed/multi.py", line 86, in run_multicore

for data in joblib.Parallel(parallel["num_jobs"], batch_size=1)(joblib.delayed(fn)(x) for x in items):


 "/usr/local/share/bcbio/anaconda/lib/python2.7/site-packages/joblib/parallel.py", line 804, in __call__

while self.dispatch_one_batch(iterator):


 "/usr/local/share/bcbio/anaconda/lib/python2.7/site-packages/joblib/parallel.py", line 662, in dispatch_one_batch

self._dispatch(tasks)


 "/usr/local/share/bcbio/anaconda/lib/python2.7/site-packages/joblib/parallel.py", line 570, in _dispatch

job = ImmediateComputeBatch(batch)


 "/usr/local/share/bcbio/anaconda/lib/python2.7/site-packages/joblib/parallel.py", line 183, in __init__

self.results = batch()


 "/usr/local/share/bcbio/anaconda/lib/python2.7/site-packages/joblib/parallel.py", line 72, in __call__

return [func(*args, **kwargs) for func, args, kwargs in self.items]


 "/usr/local/share/bcbio/anaconda/lib/python2.7/site-packages/bcbio/utils.py", line 51, in wrapper

return apply(f, *args, **kwargs)


 "/usr/local/share/bcbio/anaconda/lib/python2.7/site-packages/bcbio/distributed/multitasks.py", line 350, in organize_samples

return run_info.organize(*args)


 "/usr/local/share/bcbio/anaconda/lib/python2.7/site-packages/bcbio/pipeline/run_info.py", line 50, in organize

integrations=integrations)


 "/usr/local/share/bcbio/anaconda/lib/python2.7/site-packages/bcbio/pipeline/run_info.py", line 749, in _run_info_from_yaml

item = _normalize_files(item, dirs.get("flowcell"))


 "/usr/local/share/bcbio/anaconda/lib/python2.7/site-packages/bcbio/pipeline/run_info.py", line 668, in _normalize_files

_sanity_check_files(item, files)


 "/usr/local/share/bcbio/anaconda/lib/python2.7/site-packages/bcbio/pipeline/run_info.py", line 689, in _sanity_check_files

raise ValueError("%s for %s: %s" % (msg, item.get("description", ""), files))
ValueError: Expect both fastq files to not be the same for 412-normal: ['/home/centos/Calling/411/RAW/412_CTTGTA_L001_R1_001.fastq.gz', '/home/centos/Calling/411/RAW/412_CTTGTA_L001_R1_001.fastq.gz']

Traceback (most recent call last):


 "capsulenet-multi-gpu.py", line 166, in <module>

multi_model.fit_generator(trainData, steps_per_epoch = 100, epochs = args.epochs, validation_data = validateData, validation_steps=100, callbacks = [log, tb, lr_decay])


 "/root/anaconda3/lib/python3.6/site-packages/keras/legacy/interfaces.py", line 91, in wrapper

return func(*args, **kwargs)


 "/root/anaconda3/lib/python3.6/site-packages/keras/engine/training.py", line 1415, in fit_generator

initial_epoch=initial_epoch)


 "/root/anaconda3/lib/python3.6/site-packages/keras/engine/training_generator.py", line 213, in fit_generator

class_weight=class_weight)


 "/root/anaconda3/lib/python3.6/site-packages/keras/engine/training.py", line 1209, in train_on_batch

class_weight=class_weight)


 "/root/anaconda3/lib/python3.6/site-packages/keras/engine/training.py", line 749, in _standardize_user_data

exception_prefix='input')


 "/root/anaconda3/lib/python3.6/site-packages/keras/engine/training_utils.py", line 101, in standardize_input_data

str(len(data)) + ' arrays: ' + str(data)[:200] + '...')
ValueError: Error when checking model input: the list of Numpy arrays that you are passing to your model is not the size the model expected. Expected to see 2 array(s), but instead got the following list of 1 arrays: [array([[[[0.41060576, 0.40476605, 0.47026658],
