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Getting Started

  • Getting started
    • Backends
    • Installation

Tutorials:

  • Delira Introduction
    • Loading Data
      • The Dataset
      • The Dataloader
      • The Datamanager
      • Sampler
    • Models
      • __init__
      • closure
      • prepare_batch
    • Abstract Networks for specific Backends
      • PyTorch
        • forward
        • prepare_batch
        • closure example
      • Other examples
    • Training
      • Parameters
      • Trainer
      • Experiment
    • Logging
      • MultiStreamHandler
      • Logging with Visdom - The trixi Loggers
    • More Examples
  • Classification with Delira - A very short introduction
    • Logging and Visualization
    • Data Preparation
      • Loading
      • Augmentation
    • Training
    • See Also
  • Generative Adversarial Nets with Delira - A very short introduction
    • HyperParameters
    • Logging and Visualization
    • Data Preparation
      • Loading
      • Augmentation
    • Training
    • See Also
  • Segmentation in 2D using U-Nets with Delira - A very short introduction
    • Logging and Visualization
    • Data Praparation
      • Loading
      • Augmentation
    • Training
    • See Also
  • Segmentation in 3D using U-Nets with Delira - A very short introduction
    • Logging and Visualization
    • Data Praparation
      • Loading
      • Augmentation
    • Training
    • See Also

API Documentation:

  • API Documentation
    • Delira
      • Data Loading
        • Arbitrary Data
        • Nii
        • Sampler
      • IO
      • Logging
        • MultiStreamHandler
        • TrixiHandler
      • Models
        • Classification
        • Generative Adversarial Networks
        • Segmentation
      • Training
        • Parameters
        • Network Trainer
        • Predictor
        • Experiment
        • Callbacks
        • Losses
        • Metrics
        • convert_batch_to_numpy_identity
        • float_to_pytorch_tensor
        • create_optims_default_pytorch
        • create_optims_gan_pytorch
        • convert_torch_tensor_to_npy
        • create_optims_default_tf
        • initialize_uninitialized
        • convert_tf_tensor_to_npy
      • Utilities
      • Backend Resolution
      • Class Hierarchy Diagrams
  • GitHub
delira
  • Docs »
  • Overview: module code

All modules for which code is available

  • delira
    • delira.data_loading.data_loader
    • delira.data_loading.data_manager
    • delira.data_loading.dataset
    • delira.data_loading.load_utils
    • delira.data_loading.nii
    • delira.data_loading.sampler.abstract_sampler
    • delira.data_loading.sampler.lambda_sampler
    • delira.data_loading.sampler.random_sampler
    • delira.data_loading.sampler.sequential_sampler
    • delira.data_loading.sampler.weighted_sampler
    • delira.io.tf
    • delira.io.torch
    • delira.logging.multistream_handler
    • delira.logging.trixi_handler
    • delira.models.abstract_network
    • delira.models.classification.classification_network
    • delira.models.classification.classification_network_3D
    • delira.models.classification.classification_network_tf
    • delira.models.gan.generative_adversarial_network
    • delira.models.segmentation.unet
    • delira.training.base_trainer
    • delira.training.callbacks.abstract_callback
    • delira.training.callbacks.early_stopping
    • delira.training.callbacks.pytorch_schedulers
    • delira.training.experiment
    • delira.training.losses
    • delira.training.metrics
    • delira.training.parameters
    • delira.training.predictor
    • delira.training.pytorch_trainer
    • delira.training.tf_trainer
    • delira.training.train_utils
    • delira.utils.config
    • delira.utils.context_managers
    • delira.utils.decorators
    • delira.utils.imageops
    • delira.utils.path
    • delira.utils.time
  • logging

© Copyright 2019, Justus Schock, Oliver Rippel, Christoph Haarburger Revision 71368ce3.

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