phygnn.layers.custom_layers

Custom tf layers.

Classes

ExpandDims(*args, **kwargs)	Layer to add an extra dimension to a tensor.
FNO(*args, **kwargs)	Custom layer for fourier neural operator block
FlattenAxis(*args, **kwargs)	Layer to flatten an axis from a 5D spatiotemporal Tensor into axis-0 observations.
FlexiblePadding(*args, **kwargs)	Class to perform padding on tensors
FunctionalLayer(*args, **kwargs)	Custom layer to implement the tensorflow layer functions (e.g., add, subtract, multiply, maximum, and minimum) with a constant value.
GaussianAveragePooling2D(*args, **kwargs)	Custom layer to implement tensorflow average pooling layer but with a gaussian kernel.
GaussianNoiseAxis(*args, **kwargs)	Layer to apply random noise along a given axis.
LogTransform(*args, **kwargs)	Log transform or inverse transform of data
SigLin(*args, **kwargs)	Sigmoid linear unit.
SkipConnection(*args, **kwargs)	Custom layer to implement a skip connection.
SpatialExpansion(*args, **kwargs)	Class to expand the spatial dimensions of tensors with shape: (n_observations, n_spatial_0, n_spatial_1, n_features)
SpatioTemporalExpansion(*args, **kwargs)	Class to expand the spatiotemporal dimensions of tensors with shape: (n_observations, n_spatial_0, n_spatial_1, n_temporal, n_features)
SqueezeAndExcitation(*args, **kwargs)	Custom layer for squeeze and excitation block for convolutional networks
Sup3rAdder(*args, **kwargs)	Layer to add high-resolution data to a sup3r model in the middle of a super resolution forward pass.
Sup3rConcat(*args, **kwargs)	Layer to concatenate a high-resolution feature to a sup3r model in the middle of a super resolution forward pass.
TileLayer(*args, **kwargs)	Layer to tile (repeat) data across a given axis.
UnitConversion(*args, **kwargs)	Layer to convert units per feature channel using the linear transform: y = x * scalar + adder