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Quickstart
Installation
User Guide
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- 1. Manipulating neuroimaging data
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  - 1.1. Data structures
  - 1.2. Reading neuroimaging datasets
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    - 1.2.1. Reading BIDS datasets
    - 1.2.2. Reading neuroimaging datasets: advanced tips
  - 1.3. Transforming data
  - 1.4. Splitting data
  - 1.5. Batching data for training
- 2. Building a deep learning workflow
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- 3. Experiment management and reproducibility
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  - 3.1. Configuration classes
  - 3.2. MAPS
- 4. Customising your ClinicaDL experiment
API Reference
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- clinicadl.callbacks
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- clinicadl.data
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  - clinicadl.data.datasets
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  - clinicadl.data.dataloader
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  - clinicadl.data.structures
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  - clinicadl.data.utils
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    - clinicadl.data.utils.remove_tensors
- clinicadl.infer
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- clinicadl.io
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  - clinicadl.io.bids
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  - clinicadl.io.maps
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    - clinicadl.io.maps.Maps
- clinicadl.losses
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- clinicadl.metrics
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- clinicadl.models
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- clinicadl.networks
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  - clinicadl.networks.nn
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  - clinicadl.networks.config
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- clinicadl.optim
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  - clinicadl.optim.OptimizationConfig
  - clinicadl.optim.optimizers.config
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  - clinicadl.optim.lr_schedulers.config
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- clinicadl.split
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- clinicadl.transforms
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- clinicadl.train
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- clinicadl.utils
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  - clinicadl.utils.seed.seed_everything
  - clinicadl.utils.seed.seed_everything_context
Glossary

development

Contributing
What’s new?
GitHub

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clinicadl.losses.config.L1LossConfig¶

clinicadl.losses.config.L1LossConfig[source]¶

Config class for torch.nn.L1Loss.

parameter reduction: Reduction = 'mean'¶

clinicadl.losses.config.SmoothL1LossConfig

clinicadl.losses.config.MSELossConfig

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clinicadl.losses.config.L1LossConfig
- L1LossConfig
  - L1LossConfig.reduction