Use `expand` instead of ones to broadcast tensor (#373)

Use `expand` instead of ones to broadcast tensor.

As suggested by @bes-dev. According the documentation this shouldn't
take any memory - it just plays with the strides.

src/diffusers/models/unet_2d_condition.py

@@ -152,7 +152,7 @@ class UNet2DConditionModel(ModelMixin, ConfigMixin):
             timesteps = timesteps[None].to(sample.device)
 
         # broadcast to batch dimension in a way that's compatible with ONNX/Core ML
-        timesteps = timesteps * torch.ones(sample.shape[0], dtype=timesteps.dtype, device=timesteps.device)
+        timesteps = timesteps.expand(sample.shape[0])
 
         t_emb = self.time_proj(timesteps)
         emb = self.time_embedding(t_emb)