Update autoregressive/models/generate.py

autoregressive/models/generate.py

@@ -137,15 +137,12 @@ def decode_n_tokens(
 
 @torch.no_grad()
 def generate(model, cond, max_new_tokens, emb_masks=None, cfg_scale=1.0, cfg_interval=-1, condition=None, condition_null=None, condition_token_nums=0, **sampling_kwargs):
-    condition = condition.to(torch.float32)
-    print(condition)
     if condition is not None:
         with torch.no_grad():
             print(model.adapter.model.embeddings.patch_embeddings.projection.weight)
             condition = model.adapter(condition)
             print(condition)
             condition = model.adapter_mlp(condition)
-            print(condition)
     if model.model_type == 'c2i':
         if cfg_scale > 1.0:
             cond_null = torch.ones_like(cond) * model.num_classes