2019-11-19 03:43:39 +01:00
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# map2map
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Neural network emulators to transform field/map data
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2020-03-04 02:23:13 +01:00
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## Installation
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Install in editable mode
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```bash
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pip install -e .
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```
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## Usage
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Take a look at the examples in `scripts/*.slurm`, and the command line options
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in `map2map/args.py` or by `m2m.py -h`.
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### data
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Structure your data to start with the channel axis and then the spatial
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dimensions.
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Put each sample in one file.
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Specify the data path with glob patterns.
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#### data normalization
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Input and target (output) data can be normalized by functions defined in
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`map2map2/data/norms/`.
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### model
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Find the models in `map2map/models/`.
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Customize the existing models, or add new models there and edit the `__init__.py`.
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2020-04-19 20:34:23 +02:00
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### Training
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#### Files generated
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* `*.out`: job stdout and stderr
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* `state_*.pth`: training state including the model parameters
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* `checkpoint.pth`: symlink to the latest state
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* `runs/`: directories of tensorboard logs
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#### Tracking
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Install tensorboard and launch it by
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```bash
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tensorboard --logdir PATH --samples_per_plugin images=IMAGES --port PORT
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```
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* Use `.` as `PATH` in the training directory, or use the path to some parent
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directory for tensorboard to search recursively for multiple jobs.
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* Show `IMAGES` images, or all of them by setting it to 0.
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* Pick a free `PORT`. For remote jobs, do ssh port forwarding.
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