This is a simple wrapper around gin-config (https://github.com/google/gin-config/) with connection to Weights&Biases, comet.ml and S3 to train Keras models and keep track of them. Please see the documentation for gin-config for more information on how to use gin.
pip install gin-train
- examples/mnist - train a model on the mnist dataset
$ gt --help
usage: gt [-h] [--gin-bindings GIN_BINDINGS] [--gpu GPU]
[--framework FRAMEWORK] [-c COMETML_PROJECT] [-w WANDB_PROJECT]
[--remote-dir REMOTE_DIR] [--run-id RUN_ID] [-n NOTE_PARAMS]
[--force-overwrite]
gin-files output-dir
Train a model using gin-config
Args:
gin_file: comma separated list of gin files
output_dir: where to store the results. Note: a subdirectory `run_id`
will be created in `output_dir`.
gin_bindings: comma separated list of additional gin-bindings to use
gpu: which gpu to use. Example: gpu=1
framework: which framework to use. Available: tf
cometml_project: comet_ml project name. Example: Avsecz/basepair.
If not specified, cometml will not get used
wandb_project: wandb `<entity>/<project>` name. Example: Avsecz/test.
If not specified, wandb will not be used
remote_dir: additional path to the remote directory. Can be an s3 path.
Example: `s3://mybucket/model1/exp1`
run_id: manual run id. If not specified, it will be either randomly
generated or re-used from wandb or comet.ml.
note_params: take note of additional key=value pairs.
Example: --note-params note='my custom note',feature_set=this
force_overwrite: if True, the output directory will be overwritten
positional arguments:
gin-files -
output-dir -
optional arguments:
-h, --help show this help message and exit
--gin-bindings GIN_BINDINGS
''
--gpu GPU 0
--framework FRAMEWORK
'tf'
-c COMETML_PROJECT, --cometml-project COMETML_PROJECT
''
-w WANDB_PROJECT, --wandb-project WANDB_PROJECT
''
--remote-dir REMOTE_DIR
''
--run-id RUN_ID -
-n NOTE_PARAMS, --note-params NOTE_PARAMS
''
--force-overwrite False
gin_file
can be a single or multiple gin files. That allows you to re-use for example the problem definition parts of the gin config and the model definition part of gin-config.
gt problem.gin,model.gin default/ --gpu=1 -c Avsecz/basepair-chipseq-cls -f
where the gin files are the following: