AlphaGenome PyTorch Documentation# PyTorch implementation of the AlphaGenome DNA sequence-to-function model. Contents: Installation Basic Installation Building documentation Quick Start Loading the Model Preparing Input Inference Understanding Outputs GPU Inference Mixed Precision Next Steps Named Outputs Setup Output types and track counts Track metadata fields Filtering tracks Masks and indices Resolution-independent queries Cross-head filtering Variant effect scoring Padding tracks Loading and building metadata catalogs Comparison with JAX AlphaGenome Full Chromosome Prediction Command-Line Script Python API Tiling Configuration Supported Heads Performance Tips API Reference Command-Line Interface (agt) Global options agt info agt predict agt finetune agt score agt convert agt preprocess agt serve Dependency Gating Performance Tips torch.compile Mixed Precision Resolution Selection Head Selection Gradient Checkpointing Batch Size Combining Optimizations Finetuning Overview Quick Start API Reference Model Layers Training Indices and tables# Index Module Index Search Page