Module neurop.fno.fno1d

Classes

class FNO1D (readin: torch.nn.modules.module.Module,
kernel_integral: torch.nn.modules.module.Module,
readout: torch.nn.modules.module.Module,
optimizer: torch.optim.optimizer.Optimizer | None,
activation_function: Callable[[torch.Tensor], torch.Tensor] = <built-in method relu of type object>)

Expand source code

class FNO1D(NeuralOperator):
    pass

Abstract class for Neural Operators.

Instance Attributes:

readin: (torch.nn.Module) 
    Reads in input data and projects to higher dimensional space

kernel_integral: (torch.nn.Module) 
    Performs the kernel operator on the data

readout: (torch.nn.Module)
    Reads out data to lower dimensional space

optimizer: (torch.optim.Optimizer) 
    Optimization algorithm to choose. Defaults to Adam(lr=1e-3)

parameters: (torch.nn.Parameter)
    Neural operator parameters

activation_function: (Callable[[Tensor], Tensor])
    Activation to introduce nonlinearity between kernel operations

Ancestors

• NeuralOperator
• torch.nn.modules.module.Module
• abc.ABC

Instance variables

var kernel_integral : torch.nn.modules.module.Module

var optimizer : torch.optim.optimizer.Optimizer | None

var readin : torch.nn.modules.module.Module

var readout : torch.nn.modules.module.Module

Methods

def activation_function(...) ‑> Callable[[torch.Tensor], torch.Tensor]

Inherited members

• NeuralOperator:
  • calculate_metrics
  • evaluate
  • forward
  • load
  • loss
  • save
  • to_device
  • train_step