from polyaxon_client.tracking import Experiment
experiment = Experiment()
print(experiment.get_experiment_info())
experiment.log_params(activation='sigmoid', lr=0.001)
experiment.log_params(dropout=0.5)
experiment.log_metrics(step=123, loss=0.023, accuracy=0.91)
experiment.log_data_ref(data="/data/cifar10-batches-py",
data_name='my_dataset')
+ "_"
+ hparams.outer_model.replace(".", "_")
)
print(f'This will run on polyaxon: {str(hparams.on_polyaxon)}')
# hparams.device = torch.device('cuda' if hparams.on_polyaxon else 'cpu')
hparams.device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')
print('torch.cuda.is_available(): ', torch.cuda.is_available())
print('device: ', hparams.device)
if hparams.on_polyaxon:
from polyaxon_client.tracking import Experiment, get_data_paths, get_outputs_path
hparams.data_root = get_data_paths()['data1'] + polyaxon_folder
hparams.output_path = get_outputs_path()
poly_experiment_info = Experiment.get_experiment_info()
poly_experiment_nr = poly_experiment_info['experiment_name'].split(".")[-1]
hparams.name = poly_experiment_nr + "_" + exp_name
print(f'get_outputs_path: {get_outputs_path()} \n '
f'experiment_info: {poly_experiment_info} \n experiment_name: {poly_experiment_nr}')
else:
date_str = datetime.now().strftime("%y%m%d-%H%M%S_")
hparams.name = 'local_' + date_str + exp_name
# hparams.output_path = Path(hparams.output_path).absolute() / hparams.name
wandb_logger = WandbLogger(name=hparams.name,
project=f"aortaSegm-{hparams.outer_model.split('.')[-1]}-{hparams.inner_module.split('.')[-1]}")
# wandb.init(project=f"aortaSegm-{hparams.outer_model.split('.')[-1]}-{hparams.inner_module.split('.')[-1]}")
argparse_summary(hparams, parser)
