X-Git-Url: https://fleuret.org/cgi-bin/gitweb/gitweb.cgi?a=blobdiff_plain;f=mygpt.py;h=ab16e1e184bdc513f5cd189112cf78908d76abd0;hb=086ec8f8d2ffeaac270fbedd991bb79122db7fdf;hp=37fe6aff89b6b2b07acb1d1d8e5be632a025cc01;hpb=a4145c0493bf53f1d076f98d1ecc36cebf36478c;p=mygpt.git

diff --git a/mygpt.py b/mygpt.py
index 37fe6af..ab16e1e 100755
--- a/mygpt.py
+++ b/mygpt.py
@@ -57,7 +57,7 @@ class QKVAttention(nn.Module):
         self.w_q = randw(nb_heads, dim_qk, dim_in)
         self.w_k = randw(nb_heads, dim_qk, dim_in)
         self.w_v = randw(nb_heads, dim_v, dim_in)
-        self.w_o = randw(dim_in, dim_v * nb_heads)
+        self.w_o = randw(dim_v * nb_heads, dim_in)
 
     def forward(self, x_q, x_kv = None):
         if x_kv is None: x_kv = x_q
@@ -111,7 +111,6 @@ class MyGPT(nn.Module):
                         nb_heads = nb_heads,
                         causal = True, attention_dropout = dropout
                     ),
-                    nn.Linear(in_features = dim_model, out_features = dim_model),
                 ),
                 Residual(
                     nn.LayerNorm(dim_model),
@@ -127,10 +126,11 @@ class MyGPT(nn.Module):
         self.readout = nn.Linear(in_features = dim_model, out_features = vocabulary_size)
 
     def forward(self, x):
+        x = F.pad(x, (1, 0))
         x = self.embedding(x)
         x = self.trunk(x)
         x = self.readout(x)
-        return x
+        return x[:, :-1]
 
 ######################################################################
 
@@ -142,7 +142,7 @@ if __name__ == '__main__':
 
     model = MyGPT(
         vocabulary_size = vocabulary_size,
-        dim_model = 16, dim_keys = 50, dim_hidden = 100,
+        dim_model = 18, dim_keys = 50, dim_hidden = 100,
         nb_heads = 2, nb_blocks = 3,
         dropout = 0.1
     )