gninatorch package

PyTorch implementation of GNINA scoring function

Submodules

• gninatorch.dataloaders module
  • GriddedExamplesLoader
• gninatorch.gnina module
  • load_gnina_model()
  • load_gnina_models()
  • main()
  • options()
  • setup_gnina_model()
• gninatorch.inference module
  • inference()
  • options()
• gninatorch.losses module
  • AffinityLoss
    • AffinityLoss.forward()
  • ScaledNLLLoss
    • ScaledNLLLoss.forward()
• gninatorch.metrics module
  • setup_metrics()
• gninatorch.models module
  • Default2017
    • Default2017.forward()
  • Default2017Affinity
    • Default2017Affinity.forward()
  • Default2017Flex
    • Default2017Flex.forward()
  • Default2017Pose
    • Default2017Pose.forward()
  • Default2018
    • Default2018.forward()
  • Default2018Affinity
    • Default2018Affinity.forward()
  • Default2018Flex
    • Default2018Flex.forward()
  • Default2018Pose
    • Default2018Pose.forward()
  • Dense
    • Dense.forward()
  • DenseAffinity
    • DenseAffinity.forward()
  • DenseBlock
    • DenseBlock.forward()
    • DenseBlock.out_features()
  • DenseFlex
    • DenseFlex.forward()
  • DensePose
    • DensePose.forward()
  • GNINAModelEnsemble
    • GNINAModelEnsemble.forward()
  • HiResAffinity
    • HiResAffinity.forward()
  • HiResPose
    • HiResPose.forward()
  • Model
    • Model.affinity
    • Model.flex
    • Model.model
  • weights_and_biases_init()
• gninatorch.setup module
  • setup_example_provider()
  • setup_grid_maker()
• gninatorch.training module
  • options()
  • training()
• gninatorch.transforms module
  • output_transform_ROC()
  • output_transform_ROC_flex()
  • output_transform_select_affinity()
  • output_transform_select_affinity_abs()
  • output_transform_select_flex()
  • output_transform_select_log_flex()
  • output_transform_select_log_pose()
  • output_transform_select_pose()
• gninatorch.utils module
  • log_print()
  • print_args()
  • set_device()