feat: 'README'

modeling_flame.py

@@ -732,11 +732,9 @@ class FLAMEModel(nn.Module):
         # decoding
         x_dec = self.decoder(x_enc, x_rec)
 
-        proj = nn.Linear(self.d_model, inference_patch_len, bias=False)
-        proj.weight.data = resample(old=self.proj.weight.data.T,
-                                    new_patch_len=inference_patch_len).T
+        resampled_weight = resample(old=self.proj.weight.data.T, new_patch_len=inference_patch_len).T
+        dec_out = F.linear(x_dec, resampled_weight)
 
-        dec_out = proj(x_dec)
         point_forecasts = rearrange(dec_out, 'b n p -> b (n p)')
         return point_forecasts[:, :pred_len]