diff --git a/dalle2_pytorch/dalle2_pytorch.py b/dalle2_pytorch/dalle2_pytorch.py
index d02cda1..f84794e 100644
--- a/dalle2_pytorch/dalle2_pytorch.py
+++ b/dalle2_pytorch/dalle2_pytorch.py
@@ -871,7 +871,7 @@ class DiffusionPriorNetwork(nn.Module):
         if not exists(text_encodings):
             text_encodings = torch.empty((batch, 0, dim), device = device, dtype = dtype)
 
-        if not exists(mask):
+        if not exists(mask) or mask.numel() == 0:
             mask = torch.any(text_encodings != 0., dim = -1)
 
         # classifier free guidance
@@ -1818,7 +1818,7 @@ class Unet(nn.Module):
         if exists(text_encodings) and self.cond_on_text_encodings:
             assert self.text_embed_dim == text_encodings.shape[-1], f'the text encodings you are passing in have a dimension of {text_encodings.shape[-1]}, but the unet was created with text_embed_dim of {self.text_embed_dim}.'
 
-            if not exists(text_mask):
+            if not exists(text_mask) or text_mask.numel() == 0:
                 text_mask = torch.any(text_encodings != 0., dim = -1)
 
             text_tokens = self.text_to_cond(text_encodings)
@@ -1835,7 +1835,7 @@ class Unet(nn.Module):
 
             text_mask = rearrange(text_mask, 'b n -> b n 1')
 
-            assert text_mask.shape[0] == text_keep_mask.shape[0], f'text_mask has shape of {text_mask.shape} while text_keep_mask has shape {text_keep_mask.shape}'
+            assert text_mask.shape[0] == text_keep_mask.shape[0], f'text_mask has shape of {text_mask.shape} while text_keep_mask has shape {text_keep_mask.shape}. text encoding is of shape {text_encodings.shape}'
             text_keep_mask = text_mask & text_keep_mask
 
             null_text_embed = self.null_text_embed.to(text_tokens.dtype) # for some reason pytorch AMP not working
diff --git a/dalle2_pytorch/version.py b/dalle2_pytorch/version.py
index e9734d4..ebcbb29 100644
--- a/dalle2_pytorch/version.py
+++ b/dalle2_pytorch/version.py
@@ -1 +1 @@
-__version__ = '0.21.2'
+__version__ = '0.21.3'