seq length in rope

Author: vpj

labml_nn/transformers/rope/__init__.py

@@ -168,6 +168,9 @@ def forward(self, x: torch.Tensor):
         # Cache $\cos$ and $\sin$ values
         self._build_cache(x)
 
+        # Sequence length
+        seq_len = x.shape[0]
+
         # Split the features, we can choose to apply rotary embeddings only to a partial set of features.
         x_rope, x_pass = x[..., :self.d], x[..., self.d:]
 
@@ -185,7 +188,7 @@ def forward(self, x: torch.Tensor):
         # \end{align}
         #
         # for $i \in {1, 2, ..., \frac{d}{2}}$
-        x_rope = (x_rope * self.cos_cached[:x.shape[0]]) + (neg_half_x * self.sin_cached[:x.shape[0]])
+        x_rope = (x_rope * self.cos_cached[:seq_len]) + (neg_half_x * self.sin_cached[:seq_len])
 
         #
         return torch.cat((x_rope, x_pass), dim=-1)