API reference

Data: torchmil.data

• Introduction
• Batches in torchmil
• Spatial and sequential representation

Datasets: torchmil.datasets

• Introduction
• Binary classification dataset
• CAMELYON16 dataset
• CTScan dataset
• False Frequency dataset
• Multi-Concept Standard dataset
• PANDA dataset
• Processed MIL dataset
• RSNA dataset
• Single Concept Standard dataset
• Shifted Mean MIL Dataset
• Traffic Anomaly Detection (TAD) MIL Dataset
• Toy dataset
• Trident WSI dataset
• Video Classification Dataset

Modules: torchmil.nn

• Introduction
• Attention
  • Attention Pool
  • iRPE Multihead Self-Attention
  • Multihead Cross-Attention
  • Multihead Self-Attention
  • Nyström Attention
  • Prob Smooth Attention Pool
  • Sm Attention Pool
• Graph Neural Networks (GNNs)
  • ChebConv
  • DeepGCNLayer
  • Dense MinCut pooling
  • GCNConv
• Transformers
  • Transformer base class
  • Conventional Transformer
  • iRPE Transformer
  • Nyström Transformer
  • Sm Transformer
  • Tokens-to-Token (T2T)
• Max Pool
• Mean Pool
• Multi-Layer Perceptron (MLP)
• Sm operator
• Variational Autoencoder (VAE)

Models: torchmil.models

• Introduction
• ABMIL
• CAMIL
• CLAM
• DeepGraphSurv
• DSMIL
• DFTDMIL
• GTP
• IIBMIL
• General MIL model
• PatchGCN
• ProbSmoothABMIL
• SETMIL
• SmABMIL
• SmTransformerABMIL
• TransformerABMIL
• TransformerProbSmoothABMIL
• TransMIL
• VAEABMIL

Visualize: torchmil.visualize

• Introduction
• Visualizing CT scans
• Visualizing WSIs

Utils: torchmil.utils

• Introduction
• Annealing Scheduler
• Graph utils
• Trainer