quantax.model.Triangular_ResSum#
- quantax.model.Triangular_ResSum(nblocks: int, channels: int, final_activation: ~typing.Callable | None = None, trans_symm: ~quantax.symmetry.symmetry.Symmetry | None = None, dtype: ~numpy.dtype = <class 'jax.numpy.float32'>)#
The
ResSum
equivalence forTriangular
andTriangularB
lattices. The kernel size is fixed as \(3\times3\).- Parameters:
nblocks – The number of residual blocks. Each block contains two convolutional layers.
channels – The number of channels. Each layer has the same amount of channels.
final_activation – The activation function in the last layer. By default,
Exp
is used.trans_symm – The translation symmetry to be applied in the last layer, see
ConvSymmetrize
.dtype – The data type of the parameters.