Write Strategy

Module containing different strategies for writing predictions.

`CacheTiles`

Bases: WriteStrategy

A write strategy that will cache tiles.

Tiles are cached until a whole image is predicted on. Then the stitched prediction is saved.

Parameters:

Name	Type	Description	Default
`write_func`	`WriteFunc`	Function used to save predictions.	required
`write_extension`	`str`	Extension added to prediction file paths.	required
`write_func_kwargs`	`dict of {str: Any}`	Extra kwargs to pass to `write_func`.	required

Attributes:

Name	Type	Description
`write_func`	`WriteFunc`	Function used to save predictions.
`write_extension`	`str`	Extension added to prediction file paths.
`write_func_kwargs`	`dict of {str: Any}`	Extra kwargs to pass to `write_func`.
`tile_cache`	`list of numpy.ndarray`	Tiles cached for stitching prediction.
`tile_info_cache`	`list of TileInformation`	Cached tile information for stitching prediction.

`last_tiles` `property`

List of bool to determine whether each tile in the cache is the last tile.

Returns:

Type	Description
`list of bool`	Whether each tile in the tile cache is the last tile.

`write_batch(trainer, pl_module, prediction, batch_indices, batch, batch_idx, dataloader_idx, dirpath)`

Cache tiles until the last tile is predicted; save the stitched prediction.

Parameters:

Name	Type	Description	Default
`trainer`	`Trainer`	PyTorch Lightning Trainer.	required
`pl_module`	`LightningModule`	PyTorch Lightning LightningModule.	required
`prediction`	`Any`	Predictions on `batch`.	required
`batch_indices`	`sequence of int`	Indices identifying the samples in the batch.	required
`batch`	`Any`	Input batch.	required
`batch_idx`	`int`	Batch index.	required
`dataloader_idx`	`int`	Dataloader index.	required
`dirpath`	`Path`	Path to directory to save predictions to.	required

`WriteImage`

Bases: WriteStrategy

A strategy for writing image predictions (i.e. un-tiled predictions).

Parameters:

Name	Type	Description	Default
`write_func`	`WriteFunc`	Function used to save predictions.	required
`write_extension`	`str`	Extension added to prediction file paths.	required
`write_func_kwargs`	`dict of {str: Any}`	Extra kwargs to pass to `write_func`.	required

Attributes:

Name	Type	Description
`write_func`	`WriteFunc`	Function used to save predictions.
`write_extension`	`str`	Extension added to prediction file paths.
`write_func_kwargs`	`dict of {str: Any}`	Extra kwargs to pass to `write_func`.

`write_batch(trainer, pl_module, prediction, batch_indices, batch, batch_idx, dataloader_idx, dirpath)`

Save full images.

Parameters:

Name	Type	Description	Default
`trainer`	`Trainer`	PyTorch Lightning Trainer.	required
`pl_module`	`LightningModule`	PyTorch Lightning LightningModule.	required
`prediction`	`Any`	Predictions on `batch`.	required
`batch_indices`	`sequence of int`	Indices identifying the samples in the batch.	required
`batch`	`Any`	Input batch.	required
`batch_idx`	`int`	Batch index.	required
`dataloader_idx`	`int`	Dataloader index.	required
`dirpath`	`Path`	Path to directory to save predictions to.	required

Raises:

Type	Description
`TypeError`	If trainer prediction dataset is not `IterablePredDataset`.

`WriteStrategy`

Bases: Protocol

Protocol for write strategy classes.

`write_batch(trainer, pl_module, prediction, batch_indices, batch, batch_idx, dataloader_idx, dirpath)`

WriteStrategy subclasses must contain this function to write a batch.

Parameters:

Name	Type	Description	Default
`trainer`	`Trainer`	PyTorch Lightning Trainer.	required
`pl_module`	`LightningModule`	PyTorch Lightning LightningModule.	required
`prediction`	`Any`	Predictions on `batch`.	required
`batch_indices`	`sequence of int`	Indices identifying the samples in the batch.	required
`batch`	`Any`	Input batch.	required
`batch_idx`	`int`	Batch index.	required
`dataloader_idx`	`int`	Dataloader index.	required
`dirpath`	`Path`	Path to directory to save predictions to.	required

`WriteTilesZarr`

Bases: WriteStrategy

Strategy to write tiles to Zarr file.

`write_batch(trainer, pl_module, prediction, batch_indices, batch, batch_idx, dataloader_idx, dirpath)`

Write tiles to zarr file.

Parameters:

Name	Type	Description	Default
`trainer`	`Trainer`	PyTorch Lightning Trainer.	required
`pl_module`	`LightningModule`	PyTorch Lightning LightningModule.	required
`prediction`	`Any`	Predictions on `batch`.	required
`batch_indices`	`sequence of int`	Indices identifying the samples in the batch.	required
`batch`	`Any`	Input batch.	required
`batch_idx`	`int`	Batch index.	required
`dataloader_idx`	`int`	Dataloader index.	required
`dirpath`	`Path`	Path to directory to save predictions to.	required

Raises:

Type	Description
`NotImplementedError`

Write Strategy

CacheTiles

last_tiles property

write_batch(trainer, pl_module, prediction, batch_indices, batch, batch_idx, dataloader_idx, dirpath)

WriteImage

write_batch(trainer, pl_module, prediction, batch_indices, batch, batch_idx, dataloader_idx, dirpath)

WriteStrategy

write_batch(trainer, pl_module, prediction, batch_indices, batch, batch_idx, dataloader_idx, dirpath)

WriteTilesZarr

write_batch(trainer, pl_module, prediction, batch_indices, batch, batch_idx, dataloader_idx, dirpath)

`CacheTiles`

`last_tiles` `property`

`write_batch(trainer, pl_module, prediction, batch_indices, batch, batch_idx, dataloader_idx, dirpath)`

`WriteImage`

`write_batch(trainer, pl_module, prediction, batch_indices, batch, batch_idx, dataloader_idx, dirpath)`

`WriteStrategy`

`write_batch(trainer, pl_module, prediction, batch_indices, batch, batch_idx, dataloader_idx, dirpath)`

`WriteTilesZarr`

`write_batch(trainer, pl_module, prediction, batch_indices, batch, batch_idx, dataloader_idx, dirpath)`