Upload AutoEncoder

model.safetensors

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:e25c1acc996e01cfcae7e106a00d1cb9b0f87489ef8ab0adc42f7baf6c82666b
+oid sha256:cf45d89286799f00cb616e4cf8a0e16c087162b7e23a5f4c4a98d5641ec51c4c
 size 133840

modeling_autoencoder.py

@@ -331,7 +331,7 @@ class AutoEncoder(PreTrainedModel):
             outputs.loss = loss_fn(outputs.logits.view(-1), outputs.labels.view(-1))
         elif not torch.is_floating_point(outputs.labels) and not torch.is_complex(outputs.labels):
             loss_fn = nn.CrossEntropyLoss()
-            outputs.loss = loss_fn(outputs.logits.view(-1, self.config.vocab_size), outputs.labels.view(-1))
+            outputs.loss = loss_fn(outputs.logits.reshape(-1, self.config.vocab_size), outputs.labels.view(-1))
         else:
             raise ValueError("Unsupported tensor dtype for these loss functions")