update input names

src/diffusers/models/unet.py

@@ -287,14 +287,14 @@ class UNetModel(ModelMixin, ConfigMixin):
         self.norm_out = Normalize(block_in)
         self.conv_out = torch.nn.Conv2d(block_in, out_ch, kernel_size=3, stride=1, padding=1)
 
-    def forward(self, x, t):
+    def forward(self, x, timesteps):
         assert x.shape[2] == x.shape[3] == self.resolution
 
-        if not torch.is_tensor(t):
-            t = torch.tensor([t], dtype=torch.long, device=x.device)
+        if not torch.is_tensor(timesteps):
+            timesteps = torch.tensor([timesteps], dtype=torch.long, device=x.device)
 
         # timestep embedding
-        temb = get_timestep_embedding(t, self.ch)
+        temb = get_timestep_embedding(timesteps, self.ch)
         temb = self.temb.dense[0](temb)
         temb = nonlinearity(temb)
         temb = self.temb.dense[1](temb)