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 for Triangular and TriangularB 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.