make data to use 1 rather than 2 size list

graph_dit/models/conditions.py

@@ -76,6 +76,8 @@ class CategoricalEmbedder(nn.Module):
             embeddings = embeddings + noise
         return embeddings
     
+# 相似的condition cluster起来
+# size 
 class ClusterContinuousEmbedder(nn.Module):
     def __init__(self, input_size, hidden_size, dropout_prob):
         super().__init__()
@@ -108,6 +110,8 @@ class ClusterContinuousEmbedder(nn.Module):
         
         if drop_ids is not None:
             embeddings = torch.zeros((labels.shape[0], self.hidden_size), device=labels.device)
+            # print(labels[~drop_ids].shape)
+            # torch.Size([1200])
             embeddings[~drop_ids] = self.mlp(labels[~drop_ids])
             embeddings[drop_ids] += self.embedding_drop.weight[0]
         else: