Module neurop.deeponet

Sub-modules

neurop.deeponet.deeponet

Classes

class DeepONet (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 DeepONet(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

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