Make current file & the extension with condor match output & error files? (to have PBS and Slurm have same output files) - hpc

Question

How do I make condor name my files as follow:
meta_learning_experiments_submission.py.e451863 meta_learning_experiments_submission.py.o444375
$(FILENAME).e$(CLUSTER)
$(FILENAME).e$(CLUSTER)
I tried it but it doesn't seem to work.
e.g. so that it matches the default behaviour of PBS when I do qsub?
I also like to know how to make slurm also match it, it would be perfect (so all three clusters are working).
I tried:
#SBATCH --error="(filename).%j.%N.err"
but that didn't work
Bounty
I want to set the file name automatically without hardcoding it.
related:
https://www.quora.com/unanswered/How-do-I-make-a-current-file-the-extension-with-condor-match-output-error-files-to-have-PBS-and-Slurm-have-the-same-output-files
For context here is my current submit file:
####################
#
# Experiments script
# Simple HTCondor submit description file
#
#
# chmod a+x test_condor.py
# chmod a+x experiments_meta_model_optimization.py
# chmod a+x meta_learning_experiments_submission.py
# chmod a+x download_miniImagenet.py
# chmod a+x ~/meta-learning-lstm-pytorch/main.py
# chmod a+x /home/miranda9/automl-meta-learning/automl-proj/meta_learning/datasets/rand_fc_nn_vec_mu_ls_gen.py
# chmod a+x /home/miranda9/automl-meta-learning/automl-proj/experiments/meta_learning/supervised_experiments_submission.py
# chmod a+x /home/miranda9/automl-meta-learning/results_plots/is_rapid_learning_real.py
# condor_submit -i
# condor_submit job.sub
#
####################
Path = /home/miranda9/automl-meta-learning/
Path = /home/miranda9/ML4Coq/
# Executable = /home/miranda9/automl-meta-learning/automl-proj/experiments/meta_learning/supervised_experiments_submission.py
# Executable = /home/miranda9/automl-meta-learning/automl-proj/experiments/meta_learning/meta_learning_experiments_submission.py
# Executable = /home/miranda9/meta-learning-lstm-pytorch/main.py
# Executable = /home/miranda9/automl-meta-learning/automl-proj/meta_learning/datasets/rand_fc_nn_vec_mu_ls_gen.py
# Executable = /home/miranda9/automl-meta-learning/results_plots/is_rapid_learning_real.py
## Output Files
Log = experiment_output_job.$(CLUSTER).log.out
Output = experiment_output_job.$(CLUSTER).out.out
Error = experiment_output_job.$(CLUSTER).err.out
Output = %(FILENAME).o$(CLUSTER)
# Use this to make sure 1 gpu is available. The key words are case insensitive.
# REquest_gpus = 1
# requirements = (CUDADeviceName != "Tesla K40m")
# requirements = (CUDADeviceName == "Quadro RTX 6000")
# requirements = ((CUDADeviceName = "Tesla K40m")) && (TARGET.Arch == "X86_64") && (TARGET.OpSys == "LINUX") && (TARGET.Disk >= RequestDisk) && (TARGET.Memory >= RequestMemory) && (TARGET.Cpus >= RequestCpus) && (TARGET.gpus >= Requestgpus) && ((TARGET.FileSystemDomain == MY.FileSystemDomain) || (TARGET.HasFileTransfer))
# requirements = (CUDADeviceName == "Tesla K40m")
# requirements = (CUDADeviceName == "GeForce GTX TITAN X")
# Note: to use multiple CPUs instead of the default (one CPU), use request_cpus as well
# Request_cpus = 4
Request_cpus = 16
# E-mail option
Notify_user = me#gmail.com
Notification = always
Environment = MY_CONDOR_JOB_ID= $(CLUSTER)
# "Queue" means add the setup until this line to the queue (needs to be at the end of script).
Queue
Alternatively, if I can use my executable script as the submission script with the parameters at the top that would work too
I usually use my submission script be the same as my executable script, e.g. see my qsub example:
#!/homes/miranda9/.conda/envs/automl-meta-learning/bin/python
#PBS -V
#PBS -M mee#gmail.com
#PBS -m abe
#PBS -lselect=1:ncpus=112
import sys
import os
for p in sys.path:
print(p)
print(os.environ)

Answer 1

HTCondor doesn't set FILENAME by default, but you could set that yourself, e.g.
FILENAME = meta_learning_experiments_submission.py
output = $(FILENAME).o.$(CLUSTER)
error = $(FILENAME).e.$(CLUSTER)