def very_simple_param_count(model):
result = sum([p.numel() for p in model.parameters()])
return result
if __name__ == "__main__":
torch.set_num_threads(4) # 4 thread
experiment = Experiment(project_name=PROJECT_NAME, api_key=COMET_ML_API)
device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
print(device)
args = meow_parse()
print(args)
experiment.set_name(args.task_id)
experiment.set_cmd_args()
experiment.log_text(args.note)
DATA_PATH = args.input
TRAIN_PATH = os.path.join(DATA_PATH, "train_data")
TEST_PATH = os.path.join(DATA_PATH, "test_data")
dataset_name = args.datasetname
if dataset_name=="shanghaitech":
print("will use shanghaitech dataset with crop ")
elif dataset_name == "shanghaitech_keepfull":
print("will use shanghaitech_keepfull")
else:
print("cannot detect dataset_name")
print("current dataset_name is ", dataset_name)
# create list
