mapreader.classify.custom_models

Classes

twoParallelModels

A class for building a model that contains two parallel branches, with

Module Contents

class mapreader.classify.custom_models.twoParallelModels(patch_model, context_model, fc_layer)

Bases: torch.nn.Module

A class for building a model that contains two parallel branches, with separate input pipelines, but shares a fully connected layer at the end. This class inherits from PyTorch’s nn.Module.

Parameters:

• patch_model (torch.nn.Module)

• context_model (torch.nn.Module)

• fc_layer (torch.nn.Linear)

patch_model

context_model

fc_layer

forward(x1, x2)

Defines the computation performed at every forward pass. Receives two inputs, x1 and x2, and feeds them through the respective feature extractor modules, then concatenates the output and passes it through the fully connected layer.

Parameters:

x1torch.Tensor

The input tensor for the patch only pipeline.

x2torch.Tensor

The input tensor for the context pipeline.

Returns:

torch.Tensor

The output tensor of the model.

Parameters:

• x1 (torch.Tensor)

• x2 (torch.Tensor)

Return type:

torch.Tensor