# AUTOGENERATED BY NBDEV! DO NOT EDIT!

__all__ = ["index", "modules", "custom_doc_links", "git_url"]

index = {"MAX_PIXEL_VAL": "00_dataloader.ipynb",
         "MEAN": "00_dataloader.ipynb",
         "STDDEV": "00_dataloader.ipynb",
         "INPUT_DIM": "00_dataloader.ipynb",
         "read_dir": "00_dataloader.ipynb",
         "read_labels": "00_dataloader.ipynb",
         "MRNetDataset": "00_dataloader.ipynb",
         "RandomCrop": "00_dataloader.ipynb",
         "TriplePrep": "00_dataloader.ipynb",
         "RandomRotate": "00_dataloader.ipynb",
         "MiddleCrop": "00_dataloader.ipynb",
         "Rescale": "00_dataloader.ipynb",
         "ToTensor": "00_dataloader.ipynb",
         "Normalize": "00_dataloader.ipynb",
         "load_mrnet_datasets": "00_dataloader.ipynb",
         "test_dataset": "00_dataloader.ipynb",
         "load_test_batch": "00_dataloader.ipynb",
         "GaussianBlur": "00_dataloader.ipynb",
         "TwoCropsTransform": "00_dataloader.ipynb",
         "load_kneexray_datasets": "00_dataloader.ipynb",
         "get_loader": "00_dataloader.ipynb",
         "instance_std": "01_architecture.ipynb",
         "group_std": "01_architecture.ipynb",
         "EvoNorm2D": "01_architecture.ipynb",
         "weights_init": "01_architecture.ipynb",
         "Quantize": "01_architecture.ipynb",
         "ResNetBlock": "01_architecture.ipynb",
         "ConvBn": "01_architecture.ipynb",
         "ConvTpBn": "01_architecture.ipynb",
         "LinearSigmoid": "01_architecture.ipynb",
         "DownUpConv": "01_architecture.ipynb",
         "Encoder": "01_architecture.ipynb",
         "Decoder": "01_architecture.ipynb",
         "Discriminator": "01_architecture.ipynb",
         "LOG": "02_utils.ipynb",
         "Tracker": "02_utils.ipynb",
         "plot_roc_curve": "02_utils.ipynb",
         "plot_confusion_matrix": "02_utils.ipynb",
         "get_dataset_args": "03_parameters.ipynb",
         "get_dataset_mrnet_args": "03_parameters.ipynb",
         "get_dataset_kneexray_args": "03_parameters.ipynb",
         "get_model_args": "03_parameters.ipynb",
         "get_architecture_args": "03_parameters.ipynb",
         "get_opt_args": "03_parameters.ipynb",
         "get_vis_args": "03_parameters.ipynb",
         "get_introvae_args": "03_parameters.ipynb",
         "get_dcgan_args": "03_parameters.ipynb",
         "get_bigan_args": "03_parameters.ipynb",
         "get_vqvae_args": "03_parameters.ipynb",
         "get_mrnet_args": "03_parameters.ipynb",
         "get_rnn_vae_args": "03_parameters.ipynb",
         "get_mocoae_args": "03_parameters.ipynb",
         "compat_args": "03_parameters.ipynb",
         "get_all_args": "03_parameters.ipynb",
         "SEED": "04_train_loop.ipynb",
         "get_model": "04_train_loop.ipynb",
         "get_dataset": "04_train_loop.ipynb",
         "test_one_batch": "04_train_loop.ipynb",
         "batch_info": "04_train_loop.ipynb",
         "main_loop": "04_train_loop.ipynb",
         "evaluate_model": "04_train_loop.ipynb",
         "AbsModel": "05_abstract_model.ipynb",
         "Classify": "10_diagnosis.ipynb",
         "ClassifyRNN": "10_diagnosis.ipynb",
         "Compressor": "10_diagnosis.ipynb",
         "TripleMRNet": "10_diagnosis.ipynb",
         "DCGAN": "20_dcgan.ipynb",
         "IntroVAE": "21_introvae.ipynb",
         "EncQuantDec": "22_vqvae.ipynb",
         "VQVAE2": "22_vqvae.ipynb",
         "DisBiGan": "23_bigan.ipynb",
         "BiGAN": "23_bigan.ipynb",
         "MoCoAE": "24_mocoae.ipynb",
         "concat_all_gather": "24_mocoae.ipynb",
         "copy_q2k_params": "24_mocoae.ipynb",
         "momentum_update": "24_mocoae.ipynb",
         "momentumContrastiveLoss": "24_mocoae.ipynb",
         "ce_loss": "24_mocoae.ipynb",
         "Predictor": "25_simsiamae.ipynb",
         "SimSiamAE": "25_simsiamae.ipynb",
         "mod_batch_2d": "33_rnn_vae.ipynb",
         "mod_batch_3d": "33_rnn_vae.ipynb",
         "Transition": "33_rnn_vae.ipynb",
         "RNNAE": "33_rnn_vae.ipynb",
         "RNNVAE": "33_rnn_vae.ipynb",
         "RNNINTROVAE": "33_rnn_vae.ipynb",
         "RNNBIGAN": "33_rnn_vae.ipynb",
         "creator_rnn_ae": "33_rnn_vae.ipynb"}

modules = ["dataloader.py",
           "architecture.py",
           "utils.py",
           "parameters.py",
           "train_loop.py",
           "abs_model.py",
           "model/diagnosis.py",
           "model/dcgan.py",
           "model/introvae.py",
           "model/vqvae.py",
           "model/bigan.py",
           "model/mocoae.py",
           "model/simsiamae.py",
           "model/rnnvae.py"]

doc_url = "https://NikonPic.github.io/deeptool/"

git_url = "https://github.com/NikonPic/deeptool/tree/master/"

def custom_doc_links(name): return None
