Replies: 1 comment 1 reply
-
almost the same, the only difference is that se_atten uses type embedding while se_a uses different embedding nets for different atom types. |
Beta Was this translation helpful? Give feedback.
1 reply
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment
Uh oh!
There was an error while loading. Please reload this page.
-
Dear all,
I try to build the model using the attention descriptor (se_attn_v2). I want to compress the model to be quickly calculated. However, as you show in the DeePMD-kit v2 paper, when we use se_attn type descriptor, the embedding matrix is embedded through attention layers depending on the number of attention layers (attn_layer). If attn_layer = 0, the embedding matrix equals to the matrix when we use "se_e2_a"?
Beta Was this translation helpful? Give feedback.
All reactions