AbstractShapeNetwork

class AbstractShapeNetwork(**kwargs)[source]

Bases: sphinx.ext.autodoc.importer._MockObject

Abstract JIT Network

static norm_type_to_class(norm_type)[source]

AbstractFeatureExtractor

class AbstractFeatureExtractor(in_channels, out_params, norm_class, p_dropout=0)[source]

Bases: sphinx.ext.autodoc.importer._MockObject

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

static _build_model(in_channels, out_features, norm_class, p_dropout)[source]

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.jit.ScriptModule

forward(input_batch)[source]

Feed batch through network

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