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The code block below results in error:
solver = Solver(equation=pde, ndims=2,constraints=constraints,domain=domain,layout='fa fa f', units=(10,20,1), activation='Sigmoid') solver.fit(batch_size=100, niters=5000, lr=0.01,optimizer='LBFGS')
Error:
0%| | 0/5000 [00:00<?, ?it/s] --------------------------------------------------------------------------- TypeError Traceback (most recent call last) File <timed exec>:8, in <module> File D:\anaconda3\envs\pydens_gpu\lib\site-packages\pydens\model_torch.py:461, in Solver.fit(self, niters, batch_size, sampler, loss_terms, optimizer, criterion, lr, **kwargs) 459 # Optimizer step. 460 loss.backward() --> 461 self.optimizer.step() 463 # Gather and store training stats. 464 self.losses.append(loss.detach().cpu().numpy()) File D:\anaconda3\envs\pydens_gpu\lib\site-packages\torch\optim\optimizer.py:88, in Optimizer._hook_for_profile.<locals>.profile_hook_step.<locals>.wrapper(*args, **kwargs) 86 profile_name = "Optimizer.step#{}.step".format(obj.__class__.__name__) 87 with torch.autograd.profiler.record_function(profile_name): ---> 88 return func(*args, **kwargs) File D:\anaconda3\envs\pydens_gpu\lib\site-packages\torch\autograd\grad_mode.py:27, in _DecoratorContextManager.__call__.<locals>.decorate_context(*args, **kwargs) 24 @functools.wraps(func) 25 def decorate_context(*args, **kwargs): 26 with self.clone(): ---> 27 return func(*args, **kwargs) TypeError: step() missing 1 required positional argument: 'closure'
Any idea on how to use LBFGS optimizer ?
The text was updated successfully, but these errors were encountered:
akoryagin
SergeyTsimfer
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The code block below results in error:
Error:
Any idea on how to use LBFGS optimizer ?
The text was updated successfully, but these errors were encountered: