AbstractShapeNetwork

class AbstractShapeNetwork(**kwargs)

Bases: sphinx.ext.autodoc.importer._MockObject

Abstract base Class to provide a convenient norm_class_mapping

static norm_type_to_class(norm_type)

helper function to map a string to an actual normalization class

Parameters:norm_type (str) – string specifying the normalization class Returns:Normalization Class (subclass of torch.nn.Module) Return type:type

AbstractFeatureExtractor

class AbstractFeatureExtractor(in_channels, out_params, norm_class, p_dropout=0)

Bases: sphinx.ext.autodoc.importer._MockObject

Abstract Feature Extractor Class all further feature extracotrs should be derived from

static _build_model(in_channels, out_features, norm_class, p_dropout)

Build the actual model structure

Parameters:

• in_channels (int) – number of input channels
• out_features (int) – number of outputs
• norm_class (Any) – class implementing a normalization
• p_dropout (float) – dropout probability

Returns:

ensembled model

Return type:

torch.nn.Module

forward(input_batch)

Feed batch through network

Parameters:input_batch (torch.Tensor) – batch to feed through network Returns:exracted features Return type:torch.Tensor