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Fix error in discovery with DeepXDE adapter #8

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Merged
Yaroslav-Muravev merged 1 commit into from
Jul 28, 2026
Merged

Fix error in discovery with DeepXDE adapter #8

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29 changes: 18 additions & 11 deletions epde/integrate/deepxde_integration.py
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Original file line number Diff line number Diff line change
Expand Up @@ -18,7 +18,6 @@ def solve(self, eq_list: List[Equation], var_names: List[str],
adapter: 'DeepXDEAdapter') -> Tuple[List[np.ndarray], float]:
pass


class Solver1D(SolverStrategy):
def solve(self, eq_list, var_names, grids, data_list, adapter):
t = grids[0]
Expand Down Expand Up @@ -68,9 +67,11 @@ def func(x):
model = dde.Model(data_obj, net)
model.compile(adapter.optimizer, lr=adapter.lr)
try:
losshistory, train_state = model.train(epochs=adapter.epochs) # <-- ИСПРАВЛЕНО
final_loss = float(losshistory.loss_train[-1][0]) if losshistory.loss_train else np.nan
losshistory, train_state = model.train(epochs=adapter.epochs)
final_loss = float(
losshistory.loss_train[-1][0]) if losshistory.loss_train else np.nan
except Exception as e:
print(f"Exception: {e}")
y_pred = [np.full(data.shape, np.nan) for data in data_list]
return y_pred, np.nan

Expand Down Expand Up @@ -144,9 +145,10 @@ def func(x):
model = dde.Model(data_obj, net)
model.compile(adapter.optimizer, lr=adapter.lr)
try:
losshistory, train_state = model.train(epochs=adapter.epochs) # <- исправлено
losshistory, train_state = model.train(epochs=adapter.epochs) # <-- ИСПРАВЛЕНО
final_loss = float(losshistory.loss_train[-1][0]) if losshistory.loss_train else np.nan
except Exception as e:
print(f"Exception: {e}")
y_pred = [np.full(data.shape, np.nan) for data in data_list]
return y_pred, np.nan

Expand Down Expand Up @@ -236,9 +238,10 @@ def func(x):
model = dde.Model(data_obj, net)
model.compile(adapter.optimizer, lr=adapter.lr)
try:
losshistory, train_state = model.train(epochs=adapter.epochs) # <- исправлено
losshistory, train_state = model.train(epochs=adapter.epochs) # <-- ИСПРАВЛЕНО
final_loss = float(losshistory.loss_train[-1][0]) if losshistory.loss_train else np.nan
except Exception as e:
print(f"Exception: {e}")
y_pred = [np.full(data.shape, np.nan) for data in data_list]
return y_pred, np.nan

Expand Down Expand Up @@ -302,7 +305,10 @@ def pde(x, y):
for term_idx, term in enumerate(all_terms):
if term_idx == tgt:
continue
coeff = float(eq.weights_final[term_idx]) if use_weights else 1.0
if use_weights and len(eq.weights_final) > term_idx:
coeff = float(eq.weights_final[term_idx])
else:
coeff = 1.0
term_val = 1.0
for factor in term.structure:
fv = self._factor_value_with_map(dde, factor, x, y, self.coord_map, var_idx_map)
Expand All @@ -311,11 +317,12 @@ def pde(x, y):
if use_weights and len(eq.weights_final) > len(all_terms):
residual += float(eq.weights_final[-1]) * (y[:, 0:1] * 0.0 + 1.0)
target = eq.target
target_val = 1.0
for factor in target.structure:
fv = self._factor_value_with_map(dde, factor, x, y, self.coord_map, var_idx_map)
target_val *= fv
residual -= target_val
if target is not None:
target_val = 1.0
for factor in target.structure:
fv = self._factor_value_with_map(dde, factor, x, y, self.coord_map, var_idx_map)
target_val *= fv
residual -= target_val
residuals.append(residual)
return residuals

Expand Down
4 changes: 2 additions & 2 deletions epde/operators/common/fitness.py
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Original file line number Diff line number Diff line change
Expand Up @@ -232,7 +232,7 @@ def set_adapter(self, net=None, pretrained_net=None):

def apply(self, objective: SoEq, arguments: dict, force_out_of_place: bool = False):
self_args, subop_args = self.parse_suboperator_args(arguments=arguments)
if force_out_of_place:
if force_out_of_place or not getattr(objective, 'weights_internal_evald', False):
self.suboperators['sparsity'].apply(objective, subop_args['sparsity'])
self.suboperators['coeff_calc'].apply(objective, subop_args['coeff_calc'])

Expand Down Expand Up @@ -340,7 +340,7 @@ def _apply_deepxde(self, objective, force_out_of_place):
penalty_coeff=self.params.get('penalty_coeff', 0.2),
for_rps=False)
# Pack per-eq masked (solution, data) for DeepXDEError.
masked_solutions = [solution_list[i][mask_flat] for i in range(len(eqs))]
masked_solutions = [solution_list[i][mask_flat] for i in range(len(eqs))] # был solution_list
masked_data = [data_list[i] for i in range(len(eqs))]
sctx = SolverContext(solution=masked_solutions, loss_add=loss,
g_fun_vals=masked_data,
Expand Down
4 changes: 2 additions & 2 deletions epde/operators/utils/parameters/default_parameters_multi_objective.json
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Original file line number Diff line number Diff line change
Expand Up @@ -24,14 +24,14 @@
"pinn_loss_mult" : 1e4,
"error_metric": "rmse",
"deepxde_config": {
"net": [95, 100, 95],
"net": [50, 50, 50],
"activation": "tanh",
"optimizer": "adam",
"lr": 1e-3,
"num_domain": 1000,
"num_boundary": 200,
"num_initial": 200,
"epochs": 2000
"epochs": 1000
}
},
"_comment_legacy_aliases": "Param-registry aliases kept ONLY so the functional test harness (tests/functional) can fetch params by the historical operator names; the production search builds the new SolverFreeFitness / SolverBasedFitness hosts.",
Expand Down
2 changes: 1 addition & 1 deletion projects/pic/data/lv/lv.py
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Original file line number Diff line number Diff line change
Expand Up @@ -48,7 +48,7 @@ def lv_discovery(noise_level):
dimensionality=dimensionality)
grid_tokens = GridTokens(['x_0', ], dimensionality=dimensionality, max_power=2)

epde_search_obj = EpdeSearch(use_solver=False, multiobjective_mode=True, use_pic=True, boundary=15,
epde_search_obj = EpdeSearch(use_solver=True, multiobjective_mode=True, use_pic=True, boundary=15,
coordinate_tensors=(t,), verbose_params={'show_iter_idx': True},
device='cuda')

Expand Down
4 changes: 2 additions & 2 deletions projects/pic/data/ode/ode.py
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Original file line number Diff line number Diff line change
Expand Up @@ -38,15 +38,15 @@ def ODE_discovery(foldername, noise_level):
t = np.arange(start=0., stop=step * steps_num, step=step)
data = np.load(os.path.join(foldername, 'ode_data.npy'))
noised_data = noise_data(data, noise_level)
data_nn = load_pretrained_PINN(os.path.join(foldername, 'ode_0_ann.pickle')).cpu()
#data_nn = load_pretrained_PINN(os.path.join(foldername, 'ode_0_ann.pickle')).cpu()

dimensionality = 0

trig_tokens = TrigonometricTokens(freq=(2 - 1e-8, 2 + 1e-8),
dimensionality=dimensionality)
grid_tokens = GridTokens(['x_0', ], dimensionality=dimensionality, max_power=2)

epde_search_obj = EpdeSearch(use_solver=False, use_pic=True, boundary=20,
epde_search_obj = EpdeSearch(use_solver=True, use_pic=True, boundary=20,
coordinate_tensors=[t,], verbose_params={'show_iter_idx': True},
device='cuda')

Expand Down
4 changes: 2 additions & 2 deletions projects/pic/data/wave/wave.py
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Expand Up @@ -46,11 +46,11 @@ def wave_data(filename):
def wave_discovery(foldername, noise_level):
grid, data = wave_data(os.path.join(foldername, 'wave_sln_80.csv'))
noised_data = noise_data(data, noise_level)
data_nn = load_pretrained_PINN(os.path.join(foldername, 'ann_pretrained.pickle'))
#data_nn = load_pretrained_PINN(os.path.join(foldername, 'ann_pretrained.pickle'))

dimensionality = data.ndim - 1

epde_search_obj = EpdeSearch(use_solver=False, use_pic=True,
epde_search_obj = EpdeSearch(use_solver=True, use_pic=True,
boundary=20,
coordinate_tensors=(grid[..., 0], grid[..., 1]), device='cuda')

Expand Down
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