Thank you very much for the information!
regarding kernel, I have additional questions.
you mentioned that “the weight parameter of the conv layers are the kernels”.
in the case, will bias will be included in the weights(kernel) when bias is set to “True”  in Convolution/ Transpose Convolution ? or
will the bias be added to output value when  bias is set to “True”
About the inltialization of weights,  i saw that  nn.init.uniform_ is used in one case and nn.init.xavier_uniform_ is used in other case.
is there any particular standard for the initialization?
in the linear layer, how can i adjust the size of weights, including bias?
thank you very much!