handle weighted forces in pytorch test entry point#12
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caic99
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Aug 26, 2025
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| masked_diff = diff_f[mask] | ||
| if masked_diff.size > 0: | ||
| mae_f = np.mean(np.abs(masked_diff)) | ||
| rmse_f = np.sqrt(np.mean(masked_diff * masked_diff)) | ||
| else: | ||
| mae_f = 0.0 | ||
| rmse_f = 0.0 |
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@anyangml please check if this is what you mean
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Summary
atom_prefweights intest_enerand report both weighted and unweighted force errorsTesting
pytest source/tests/pt/test_dp_test.py::TestDPTestSeA::test_dp_test_1_frame source/tests/pt/test_dp_test.py::TestDPTestSeASpin::test_dp_test_1_frame source/tests/pt/test_dp_test.py::TestDPTestPropertySeA::test_dp_test_1_frame source/tests/pt/test_dp_test.py::TestDPTestForceWeight::test_force_weight -q(fails: This deepmd-kit package was compiled with CXX11_ABI_FLAG=0, but PyTorch runtime was compiled with CXX11_ABI_FLAG=1)https://chatgpt.com/codex/tasks/task_b_689de8068a9c8332aa2a402469da6293