maintain same behavior as an mlp when no batch dim

lucidrains · Oct 30, 2024 · 9917a88 · 9917a88
1 parent 1ccccaa
commit 9917a88
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Showing 2 changed files with 9 additions and 1 deletion.
diff --git a/setup.py b/setup.py
@@ -3,7 +3,7 @@
 setup(
   name = 'x-transformers',
   packages = find_packages(exclude=['examples']),
-  version = '1.42.0',
+  version = '1.42.2',
   license='MIT',
   description = 'X-Transformers - Pytorch',
   author = 'Phil Wang',

diff --git a/x_transformers/neo_mlp.py b/x_transformers/neo_mlp.py
@@ -94,6 +94,11 @@ def forward(
         x,
         return_embeds = False
     ):
+        no_batch = x.ndim == 1
+
+        if no_batch:
+            x = rearrange(x, '... -> 1 ...')
+
         batch = x.shape[0]
 
         fouriered_input = self.random_fourier(x)
@@ -121,6 +126,9 @@ def forward(
         output = einsum(output_embed, self.to_output_weights, 'b n d, n d -> b n')
         output = output + self.to_output_bias
 
+        if no_batch:
+            output = rearrange(output, '1 ... -> ...')
+
         if not return_embeds:
             return output