Closed QingboKang closed 5 years ago
Hi, I guess this has something to do with the how the data gets downloaded, could you check that your data is found correctly? For instance, in my local directory if I use this command line: ''' ls datafolder/ForDataGenTrainTestVal''' I get: GT_bladder Slide_bladder ... and so one. Best,
Hi, I guess this has something to do with the how the data gets downloaded, could you check that your data is found correctly? For instance, in my local directory if I use this command line: ''' ls datafolder/ForDataGenTrainTestVal''' I get: GT_bladder Slide_bladder ... and so one. Best,
The problem is solved, just as you guessed, it is the data problem. Thanks.
But another error occurred when it run CreateRecords (7)
process.
The detailed log about the error:
Jan-05 15:09:58.221 [Task monitor] DEBUG n.processor.TaskPollingMonitor - Task completed > TaskHandler[id: 13; name: CreateRecords (7); status: COMPLETED; exit: 137; error: -; workDir: /home/qingbo/Documents/DRFNS-master/work/83/6af659bcbd36b5352100f0374d99a7]
Jan-05 15:09:58.369 [Task monitor] ERROR nextflow.processor.TaskProcessor - Error executing process > 'CreateRecords (7)'
Caused by:
Process CreateRecords (7)
terminated with an error exit status (137)
Command executed:
python TFRecords.py --tf_record train_DIST.tfrecords --split train --path ToAnnotateDistance --crop 16 --UNet --size_train 212 --size_test 0 --seed 42 --epoch 80 --type JUST_READ
Command exit status: 137
Command output: (empty)
Command error:
/home/qingbo/.local/lib/python2.7/site-packages/h5py/init.py:36: FutureWarning: Conversion of the second argument of issubdtype from float
to np.floating
is deprecated. In future, it will be treated as np.float64 == np.dtype(float).type
.
from ._conv import register_converters as _register_converters
/home/qingbo/miniconda3/envs/nuclei_2.7/lib/python2.7/site-packages/skimage/util/dtype.py:130: UserWarning: Possible precision loss when converting from float64 to uint8
.format(dtypeobj_in, dtypeobj_out))
.command.sh: line 2: 1899 Killed python TFRecords.py --tf_record train_DIST.tfrecords --split train --path ToAnnotateDistance --crop 16 --UNet --size_train 212 --size_test 0 --seed 42 --epoch 80 --type JUST_READ
Could you kindly give me one hint, many thanks.
Hi,
I don't really know, it seems that the process was killed by the system and there could many reasons why this fails. How are you running the nextflow pipeline? On a single compute/cluster? To help debug, don't hesitate to go to the workdir: /home/qingbo/Documents/DRFNS-master/work/83/6af659bcbd36b5352100f0374d99a7 and run the file '.command.sh' or the file '.command.run'.
Hi, I guess this has something to do with the how the data gets downloaded, could you check that your data is found correctly? For instance, in my local directory if I use this command line: ''' ls datafolder/ForDataGenTrainTestVal''' I get: GT_bladder Slide_bladder ... and so one. Best,
The problem is solved, just as you guessed, it is the data problem. Thanks.
But another error occurred when it run
CreateRecords (7)
process. The detailed log about the error: Jan-05 15:09:58.221 [Task monitor] DEBUG n.processor.TaskPollingMonitor - Task completed > TaskHandler[id: 13; name: CreateRecords (7); status: COMPLETED; exit: 137; error: -; workDir: /home/qingbo/Documents/DRFNS-master/work/83/6af659bcbd36b5352100f0374d99a7] Jan-05 15:09:58.369 [Task monitor] ERROR nextflow.processor.TaskProcessor - Error executing process > 'CreateRecords (7)'Caused by: Process
CreateRecords (7)
terminated with an error exit status (137)Command executed:
python TFRecords.py --tf_record train_DIST.tfrecords --split train --path ToAnnotateDistance --crop 16 --UNet --size_train 212 --size_test 0 --seed 42 --epoch 80 --type JUST_READ
Command exit status: 137
Command output: (empty)
Command error: /home/qingbo/.local/lib/python2.7/site-packages/h5py/init.py:36: FutureWarning: Conversion of the second argument of issubdtype from
float
tonp.floating
is deprecated. In future, it will be treated asnp.float64 == np.dtype(float).type
. from ._conv import register_converters as _register_converters /home/qingbo/miniconda3/envs/nuclei_2.7/lib/python2.7/site-packages/skimage/util/dtype.py:130: UserWarning: Possible precision loss when converting from float64 to uint8 .format(dtypeobj_in, dtypeobj_out)) .command.sh: line 2: 1899 Killed python TFRecords.py --tf_record train_DIST.tfrecords --split train --path ToAnnotateDistance --crop 16 --UNet --size_train 212 --size_test 0 --seed 42 --epoch 80 --type JUST_READCould you kindly give me one hint, many thanks.
How did you solve this problem? I have the same bug recently, could you help me with this? Thanks a lot!!
Hi, I guess this has something to do with the how the data gets downloaded, could you check that your data is found correctly? For instance, in my local directory if I use this command line: ''' ls datafolder/ForDataGenTrainTestVal''' I get: GT_bladder Slide_bladder ... and so one. Best,
The problem is solved, just as you guessed, it is the data problem. Thanks. But another error occurred when it run
CreateRecords (7)
process. The detailed log about the error: Jan-05 15:09:58.221 [Task monitor] DEBUG n.processor.TaskPollingMonitor - Task completed > TaskHandler[id: 13; name: CreateRecords (7); status: COMPLETED; exit: 137; error: -; workDir: /home/qingbo/Documents/DRFNS-master/work/83/6af659bcbd36b5352100f0374d99a7] Jan-05 15:09:58.369 [Task monitor] ERROR nextflow.processor.TaskProcessor - Error executing process > 'CreateRecords (7)' Caused by: ProcessCreateRecords (7)
terminated with an error exit status (137) Command executed: python TFRecords.py --tf_record train_DIST.tfrecords --split train --path ToAnnotateDistance --crop 16 --UNet --size_train 212 --size_test 0 --seed 42 --epoch 80 --type JUST_READ Command exit status: 137 Command output: (empty) Command error: /home/qingbo/.local/lib/python2.7/site-packages/h5py/init.py:36: FutureWarning: Conversion of the second argument of issubdtype fromfloat
tonp.floating
is deprecated. In future, it will be treated asnp.float64 == np.dtype(float).type
. from ._conv import register_converters as _register_converters /home/qingbo/miniconda3/envs/nuclei_2.7/lib/python2.7/site-packages/skimage/util/dtype.py:130: UserWarning: Possible precision loss when converting from float64 to uint8 .format(dtypeobj_in, dtypeobj_out)) .command.sh: line 2: 1899 Killed python TFRecords.py --tf_record train_DIST.tfrecords --split train --path ToAnnotateDistance --crop 16 --UNet --size_train 212 --size_test 0 --seed 42 --epoch 80 --type JUST_READ Could you kindly give me one hint, many thanks.How did you solve this problem? I have the same bug recently, could you help me with this? Thanks a lot!!
Did you solve this error? I met the same problem.
When I try to run the pipeline with the real data, I have already download the image dataset, but an error also occurs, below is the details of the error: N E X T F L O W ~ version 18.10.1 Launching
realdataset.nf
[magical_fermat] - revision: a123f1f4db [warm up] executor > local [70/e05036] Submitted process > ChangeInput (1) [9a/411b81] Submitted process > ChangeInput (2) [7b/dc403c] Submitted process > BinToDistance [69/dbe9ce] Submitted process > Mean (1) [06/9490fb] Submitted process > CreateRecords (3) [63/4c30bd] Submitted process > CreateRecords (2) [c6/da1e67] Submitted process > CreateRecords (1) [d4/14ea00] Submitted process > Mean (3) [01/2ae9df] Submitted process > CreateRecords (5) [7a/3cc304] Submitted process > Mean (2) [a9/49338d] Submitted process > CreateRecords (4) [20/cb397a] Submitted process > CreateRecords (6) [9c/c07d37] Submitted process > CreateRecords (7) [4a/c6c5e0] Submitted process > CreateRecords (8) [af/e8b5d3] Submitted process > CreateRecords (9) ERROR ~ Error executing process > 'Mean (1)'Caused by: Process
Mean (1)
terminated with an error exit status (1)Command executed:
python MeanCalculation.py --path ImageFolder --output .
Command exit status: 1
It seems that something is wrong in src_ReadData/Data/DataGenRandomT.py file: raise ValueError("sample larger than population") ValueError: sample larger than population
Can anyone help me with this?
Thanks.