Hi!

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

Hi!

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,

time_length=self.time_length,

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.

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