python src/main.py session=train
python src/main.py session=evaluate
Set session mode to train. Overwrite learning rate, batch size and number of episodes set in config files.
python src/main.py session=train model.learning_rate=0.001 train.batch_size=32 train.num_episodes=100
Change environment
python src/main.py session=train environment=mspacman
python src/main.py session=train environment=asterix
python src/main.py session=train model=crop_model
python src/main.py session=train model=resize_model
python src/main.py session=train model=stretch_mode
NOTE that this changes the input size of the model. This means that models trained with one setting are not compatible with each other.
Currently, API key from s174274 is used (set in config file).
You can see runs here https://wandb.ai/philipwastaken/02456_project
.
You can disable WandB if you so chose.
src/hparams/model/exp1.yaml
contains the field model_path
. This is the name of the model you wish to either train
or run. ONLY input the name of the model file, NO preceding directories (e.g. models/<model_name_here>
.
If this is set to an empty string (i.e., ''
), a new model is generated and trained from scratch.
If you set this parameter to a previously trained model, you can continue training the model (and even use different
hyperparameters).
It is important that you set this parameter if you wish to run the model. Otherwise it simply chooses the most recently modified model for convinience.
Acceptable device settings are auto
, cpu
or gpu
. auto
will prefer gpu
if possible and fallback to cpu
. If gpu
is chosen but not available, the program exits.