What is en_ksize/de_ksize and max_diffusion_step?


I am learning how to change parameters of a model to train. However, I do not know what en_ksize/de_ksize and max_diffusion_step are, not even sure what they are for. Thanks

en_ksize: [3, 3, 3]
de_ksize: [3, 3, 3]
max_diffusion_step: 1


Could you please share more details about the model or framework you are using to assist you better?

Thank you!

The model is pretty complex that I don’t really understand, not really sure if it’s helpful. I think it’s an rnn model.

TempUNet(input_dims=self.feature_dims, num_vertices=self.num_vertices,
mode=‘nearest’, norm=‘batch’, act_en=‘elu’, act_de=‘leaky_relu’,
en_ksize=self.en_ksize, de_ksize=self.de_ksize,
regularizer_scale=self.regularizer_scale, hidden_dims=self.hidden_dims)

MGConv(self.hidden_dims, {‘XXXX’: self.L_XXXX}, max_diffusion_step, self.num_vertices,
self.regularizer_scale, lambda_max=lambda_max)

XXXX here is npz file.


Could you please share details of framework or library that you are using?

Thank you!

import numpy as np
import tensorflow as tf
import scipy.sparse as sp
from scipy.sparse import linalg
from tensorflow import keras

one of the py file is called unet_model, maybe the user used keras unet?


AFAIU, en_ksize and de_ksize are the kernel sizes used in the encoder and decoder of the TempUNet model, where as max_diffusion_step is the maximum number of diffusion steps for message passing in the graph convolution.

Thank you!

1 Like

The number of layers is 3, and my en_ksize and de_ksize are both [3,3,3]. What does [3,3,3] mean and look like? Are they related to my number of layers? Can change my de_ksize to [4,7,9] or [1,2,3,4,5]? Thank you so much