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train_gcn.submit_file
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# ----------------------------------------------------------------------------------------------------------------------
#executable = /vol/research/SignRecognition/anaconda3/envs/slt/bin/python
executable = /envs/msg3d/bin/python3
arguments = $(script) $(args)
# ----------------------------------------------------------------------------------------------------------------------
universe = docker
docker_image =joedinn/slt:0
JobBatchName = slt_gcn
should_transfer_files = YES
environment = mount=/vol/research/SignRecognition,/vol/research/SignTranslation,/vol/research/NOBACKUP,/vol/research/extol
# ----------------------------------------------------------------------------------------------------------------------
log = /vol/research/SignRecognition/swisstxt/logs/c$(cluster).p$(process).log
output = /vol/research/SignRecognition/swisstxt/logs/c$(cluster).p$(process).out
error = /vol/research/SignRecognition/swisstxt/logs/c$(cluster).p$(process).error
stream_output = True
# ----------------------------------------------------------------------------------------------------------------------
requirements = (HasDocker == true) && \
(HasStornext == true) && \
(CUDACapability>=5.0) && \
(CUDAGlobalMemoryMb > 15000)
#(machine != "dori.eps.surrey.ac.uk")
#(machine != "gloin.eps.surrey.ac.uk") && \
#(CUDACapability>=5.0)
# && \
# (NotProjectOwned == True)
# ----------------------------------------------------------------------------------------------------------------------
request_GPUs = 1
request_CPUs = 1
request_memory = 60G
request_disk = 10G
+GPUMem = 15000
+CanCheckpoint = False
+JobRunTime = 4
# ----------------------------------------------------------------------------------------------------------------------
#priority = -1
# ----------------------------------------------------------------------------------------------------------------------
script = /vol/research/SignRecognition/slt/signjoey/__main__.py train ../configs/gcn.yaml --wkdir /vol/research/SignRecognition/slt/signjoey
queue