轻量投影/MLP BF16

psnr指标反而比只量化扩散主干模型要低，原因不明

scripts/evaluation/base_model_inference.py

@@ -289,13 +289,15 @@ def image_guided_synthesis(model: torch.nn.Module,
     if not text_input:
         prompts = [""] * batch_size
 
-    b, c, t, h, w = videos.shape
-    img = videos[:, :, 0]
-    img_emb = model.embedder(img)
-    img_emb = model.image_proj_model(img_emb)
-    img_emb = rearrange(img_emb, 'b (t l) c -> (b t) l c', t=t)
-    cond_emb = model.get_learned_conditioning(prompts)
-    cond_emb = cond_emb.repeat_interleave(repeats=t, dim=0)
+    b, c, t, h, w = videos.shape
+    img = videos[:, :, 0]
+    img_emb = model.embedder(img)
+    cond_emb = model.get_learned_conditioning(prompts)
+    target_dtype = cond_emb.dtype
+    img_emb = model._projector_forward(model.image_proj_model, img_emb,
+                                       target_dtype)
+    img_emb = rearrange(img_emb, 'b (t l) c -> (b t) l c', t=t)
+    cond_emb = cond_emb.repeat_interleave(repeats=t, dim=0)
 
     cond = {"c_crossattn": [torch.cat([cond_emb, img_emb], dim=1)]}
     if model.model.conditioning_key == 'hybrid':