ramjet.models.components.light_curve_network_block¶

Classes¶

class LightCurveNetworkBlock(filters: int, kernel_size: int, pooling_size: int, dropout_rate: float = 0.1, batch_normalization: bool = True, spatial: bool = True, l2_regularization: float = 0.0)[source]¶

Bases: tensorflow.keras.layers.Layer

A block containing a convolution and all the fixings that go with it.

__init__(self, filters: int, kernel_size: int, pooling_size: int, dropout_rate: float = 0.1, batch_normalization: bool = True, spatial: bool = True, l2_regularization: float = 0.0)[source]¶

Initialize self. See help(type(self)) for accurate signature.

call(self, inputs, training=False, mask=None)[source]¶

The forward pass of the layer.

Parameters:	inputs – The input tensor. training – A boolean specifying if the layer should be in training mode. mask – A mask for the input tensor.
Returns:	The output tensor of the layer.