add DeepMoD_PC #13
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…d of importing the numpy module inside ngclearn
refactor importing
rxng8
reviewed
Feb 8, 2025
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| cov_cria = (coeff_track - coeff).mean() | ||
| coeff_track = coeff | ||
| if jnp.abs(cov_cria) <= 5e-8 or i==n_epochs-1: |
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if we have run all the epochs, and cov_cria has not converged yet, we cannot call it converged. So I think we should remove the i == n_epochs - 1 condition and further optimize the model
| self.model.reset() | ||
| self.model.clamps(input, target) | ||
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| z_codes = self.model._process(jnp.array([[self.dt * i, self.dt] for i in range(self.T)])) |
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z_codes was not used, is this needed?
I think it's fine to leave it there if it serves the ._process purpose, leaving a comment will clarify for the reader
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| coeff_track = 0 | ||
| for i in range(n_epochs): | ||
| coeff, loss_pred = deepmod.process(ts_scaled, X) |
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The loss in this case is smaller than 0, you then checked if the absolute value of the loss is smaller than some constant (5e-8), is this behavior desired?
I asked that because normally, the loss is greater than 0, and often converge toward 0.
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