dataset/condition_classinput_inference/test.py

import os
import sys
if __name__ == "__main__":
    from train import *
else:  # relative import
    from .train import *




try:
    test_item = sys.argv[1]
except IndexError:
    assert __name__ == "__main__"
    test_item = "./checkpoint_test"
test_items = []
if os.path.isdir(test_item):
    for item in os.listdir(test_item):
        item = os.path.join(test_item, item)
        test_items.append(item)
elif os.path.isfile(test_item):
    test_items.append(test_item)




for item in test_items:
    state = torch.load(item, map_location="cpu")
    model.load_state_dict({key: value.to(torch.float32).to(device) for key, value in state.items()})
    loss, acc, all_targets, all_predicts = test(model=model)