def test_Config_multi_output_levels(levels):
levels_set = list(set(levels))
str_levels = ",".join(str(s) for s in levels_set)
parser = argparse.ArgumentParser()
Config.register_parser(parser)
args = parser.parse_args(["--multi-output", "--levels", str_levels])
config = Config.from_args(args)
assert config.target.levels == levels_set
def test_Config_register_parser(args, loss_cls):
parser = argparse.ArgumentParser()
Config.register_parser(parser)
args = parser.parse_args(args)
config = Config.from_args(args)
assert isinstance(config, Config)
assert isinstance(config.target, loss_cls)
if args.relative_humidity:
assert config.relative_humidity
else:
assert not config.relative_humidity
id_ = pathlib.Path(os.getcwd()).name
with tf.summary.create_file_writer(f"data/emulator/{id_}").as_default():
emulator.batch_fit(train_dataset.shuffle(100_000),
validation_data=test_dataset)
train_scores = emulator.score(train_dataset)
test_scores = emulator.score(test_dataset)
if config.output_path:
os.makedirs(config.output_path, exist_ok=True)
with open(os.path.join(config.output_path, "scores.json"), "w") as f:
json.dump({"train": train_scores, "test": test_scores}, f)
emulator.dump(os.path.join(config.output_path, "model"))
if config.wandb_logger:
model = wandb.Artifact(f"model", type="model")
model.add_dir(os.path.join(config.output_path, "model"))
wandb.log_artifact(model)
if __name__ == "__main__":
parser = get_parser()
args = parser.parse_args()
config = Config.from_args(args)
print(config)
main(config)