Python Module Index

b | c | d | f | i | l | n | p | r | s | t | v | w


	b
	`batcher`	Collecting samples in mini-batches for GPU-based training.
	`booster`	Boosting of wrongly predicted samples

	c
	`checkpoint`	Conveniency class to create checkpoints for network training.
	`common`	Common nuts
	`config`	Handling of configuration files.

	d
	`datautil`	Utility functions for non-image data

	f
	`fileutil`	File system utilities.

	i
	`imageutil`	Basic image processing utilities

	l
	`logger`	Data logging

	n
	`network`	Wrapper around other network APIs such as Lasagne, Keras and Pytorch to enable usage within nuts-flow/ml. For instance, with a wrapped network one can write: samples >> build_batch >> network.train() >> log_loss >> Consume()
	`nutsml`
	`nutsml.batcher`
	`nutsml.booster`
	`nutsml.checkpoint`
	`nutsml.common`
	`nutsml.config`
	`nutsml.datautil`
	`nutsml.examples`
	`nutsml.fileutil`
	`nutsml.imageutil`
	`nutsml.logger`
	`nutsml.network`
	`nutsml.plotter`
	`nutsml.reader`
	`nutsml.stratify`
	`nutsml.transformer`
	`nutsml.viewer`
	`nutsml.writer`

	p
	`plotter`	Plotting of data, e.g. loss over epochs

	r
	`reader`	Reading of sample data and images

	s
	`stratify`	Stratification of sample sets

	t
	`transformer`	Data and image transformations

	v
	`viewer`	Viewing of sample data

	w
	`writer`	Writing of sample and image data