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Python library to easily log experiments and parallelize hyperparameter search for neural networks

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I'm attempting to train a PytorchLightning model on a slurm cluster, and the PytorchLightning documentation recommends use of the SlurmCluster class in this package to automate submission of slurm scripts....

I am trying to extend my existing argparse with the `HyperOptArgumentParser` class. In my current argparse I have two options which are `nargs` list. When I do the following, ```...

Currently the SlurmCluster object builds a slurm script with some default parameters (time=15:00, per_experiment_nb_gpus=1, etc). This PR changes the behavior so users have to specify which slurm directives they want...

When I first started using the package (great work btw, thanks a lot!) I assumed that the intended behaviour for HyperOptArgumentParser is to only only iterate over the hyperparams if...

Added the possibility of sending an email when time_limit is reached in the form of an argument to the Cluster.notify_job_status() function. I did not set it to False by default,...

I had a setup in ubuntu with python version 3.6 manually install below library bleach==1.5.0 certifi==2016.2.28 cycler==0.10.0 decorator==4.1.2 html5lib==0.9999999 Markdown==2.6.9 matplotlib==2.1.0 networkx==2.0 nltk==3.2.5 numpy==1.13.3 olefile==0.44 pandas==0.21.0 Pillow==4.3.0 protobuf==3.4.0 pyparsing==2.2.0 python-dateutil==2.6.1...

When using `SlurmCluster.optimize_parallel_cluster_gpu`, is there a way to turn **off** the auto-resubmit for continuation? Would simply setting `cluster.minutes_to_checkpoint_before_walltime = 0` do the trick?

Hi! Thank you for the library! Using it in par with pytorch-lightning to search network's hyperparameters. Right now the following line: ```python parser = HyperOptArgumentParser() parser.opt_range('--batch-size', type=int, default=1500, tunable=True, low=16,...