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Download LightZero/lzero/mcts/tests/test_utils.py from OpenDILabCommunity/gomoku: direct link, hf CLI and curl.
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https://huggingface.co/spaces/OpenDILabCommunity/gomoku/resolve/main/LightZero/lzero/mcts/tests/test_utils.py
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| import numpy as np | |
| import pytest | |
| from lzero.mcts.utils import get_augmented_data | |
| class TestUtils(): | |
| def test_get_augmented_data(self): | |
| num_of_data = 100 | |
| board_size = 15 | |
| state = np.random.randint(0, 3, (board_size, board_size, 3), dtype=np.uint8) | |
| mcts_prob = np.random.randn(board_size, board_size) | |
| winner = np.random.randint(0, 2, 1, dtype=np.uint8) | |
| play_data = [{'state': state, 'mcts_prob': mcts_prob, 'winner': winner} for _ in range(num_of_data)] | |
| augmented_data = get_augmented_data(board_size, play_data) | |
| assert len(augmented_data) == num_of_data * 8 | |
| # TODO(pu): augmented data shape is not same as original data? | |
| # assert augmented_data[0]['state'].shape == state.shape | |
| assert augmented_data[0]['state'].flatten().shape == state.flatten().shape | |
| assert augmented_data[0]['mcts_prob'].shape == mcts_prob.flatten().shape | |
| assert augmented_data[0]['winner'].shape == winner.shape | |