mlreco.models.layers.common.configuration module

mlreco.models.layers.common.configuration.setup_cnn_configuration(self, cfg, name)[source]

Base function for global network parameters (CNN-based models). This avoids repeating everywhere the same base configuration. For example, typical usage would be:

class UResNetEncoder(torch.nn.Module):
    def __init__(self, cfg, name='uresnet_encoder'):
        super(UResNetEncoder, self).__init__()
        setup_cnn_configuration(self, cfg, name)

Defines the following default configuration:

Configuration

  • data_dim (int, default 3)

  • num_input (int, default 1)

  • allow_bias (bool, default False)

  • spatial_size (int, default 512)

  • leakiness (float, default 0.33)

  • activation (dict) – For activation function, defaults to {‘name’: ‘lrelu’, ‘args’: {}}

  • norm_layer (dict) – For normalization function, defaults to {‘name’: ‘batch_norm’, ‘args’: {}}

mlreco.models.layers.common.cnn_encoder module mlreco.models.layers.common.dbscan module