torch_ecg.preprocessors.PREPROCESSORS

torch_ecg.preprocessors.PREPROCESSORS = Registry(name=preprocessors, items=['BandPass', 'bandpass', 'BaselineRemove', 'baseline_remove', 'Normalize', 'normalize', 'MinMaxNormalize', 'min_max_normalize', 'NaiveNormalize', 'naive_normalize', 'ZScoreNormalize', 'z_score_normalize', 'Resample', 'resample'])

Registry for managing and building modules.

A registry is used to map strings (module names) to classes, and provides a unified interface to instantiate modules from configurations.

Parameters:

name (str) – Name of the registry.

Examples

>>> BACKBONES = Registry("backbones")
>>> @BACKBONES.register()
... class ResNet(nn.Module):
...     def __init__(self, depth):
...         self.depth = depth
>>> # Build from string
>>> model = BACKBONES.build("ResNet", depth=50)
>>> # Build from config dict
>>> model = BACKBONES.build({"name": "ResNet", "depth": 101})