[fix][minor] Q/K/V needs to be divisible by heads, not more (#269)

* Fixing #264, thanks @dnnspark
* changelog addendum
* moving the dimension check to post projection

CHANGELOG.md

@@ -8,9 +8,11 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
 ### Fixed
 - Fix some torchscriptability [#246]
 - Fix FourierMix being compatible with AMP [#258]
+- Better asserts on QKV dimensions [#264]
 
 ### Added
 - Simplicial Embeddings [#259]
+- Mem efficient attention, FW pass [#267]
 
 ## [0.0.10] - 2022-03-14
 ### Fixed

xformers/components/multi_head_dispatch.py

@@ -116,11 +116,6 @@ def __init__(
         if isinstance(self.proj, nn.Linear) and self.proj.bias is not None:
             constant_(self.proj.bias, 0.0)
 
-    def _check(self, t, name):
-        assert (
-            t.shape[2] % self.dim_k == 0
-        ), f"the {name} embeddings need to be divisible by the number of heads"
-
     def forward(
         self,
         query: torch.Tensor,
@@ -139,11 +134,6 @@ def forward(
         if value is None:
             value = query
 
-        # Check the dimensions properly
-        self._check(query, "query")
-        self._check(value, "value")
-        self._check(key, "key")
-
         if query.shape[0] != key.shape[0] or query.shape[0] != value.shape[0]:
             max_batch = max((query.shape[0], key.shape[0], value.shape[0]))
             query, key, value = map(
@@ -176,6 +166,16 @@ def forward(
         else:
             k, q, v = key, query, value
 
+        # Check the dimensions properly
+        def check(t, name):
+            assert (
+                t.shape[2] % self.num_heads == 0
+            ), f"the {name} embeddings need to be divisible by the number of heads"
+
+        check(q, "projected query")
+        check(v, "projected value")
+        check(k, "projected key")
+
         # Optional: rotary embedding, add relative positioning information
         if self.rotary_embeddings:
             # rotary requires the head dimension