hid_net #200
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hid_net #200
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gyzhou2000
reviewed
May 13, 2024
| # os.environ['TL_BACKEND'] = 'torch' | ||
| os.environ['TF_CPP_MIN_LOG_LEVEL'] = '2' | ||
| # os.environ['TF_CPP_MIN_LOG_LEVEL'] = '2' |
| @@ -7,8 +7,8 @@ | |||
| from ggl_build_extension import PyCudaExtension, PyCPUExtension | |||
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| # TODO will depend on different host | |||
| WITH_CUDA = False | |||
| # WITH_CUDA = True | |||
| #WITH_CUDA = False | |||
| @@ -18,8 +18,9 @@ | |||
| from .to_dense_adj import to_dense_adj | |||
| from .smiles import from_smiles | |||
| from .shortest_path import shortest_path_distance, batched_shortest_path_distance | |||
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| __all__ = [ | |||
| @@ -0,0 +1,228 @@ | |||
| import os | |||
| import sys | |||
| metrics.reset() | ||
| return rst | ||
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| def main(args): |
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这部分代码可以放在 if __name__=='__main__':中
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| val_accs = [] | ||
| test_accs = [] | ||
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如果只运行一次的话，不需要定义 val_accs, test_accs, accs 等变量，同时，记得删除多余的空行，删除之后更美观一些
| val_accs.append(val_acc) | ||
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| test_preds=tlx.gather(out,data['test_mask']) |
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在每个epoch中，只需要跑模型在验证集上的结果即可，模型训练完成之后，可以在测试集上进行测试，这部分代码可以参考其他模型的实现代码。
| parser = argparse.ArgumentParser() | ||
| parser.add_argument('--times', type=int, default=3, help='config times') | ||
| parser.add_argument('--seed', type=int, default=9, help='random seed') | ||
| parser.add_argument('--repeat', type=int, default=150, help='repeat time') |
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而且在超参数中，好像有些超参数有些并没有用到，后续可以删除。
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