update chat

multimodal/open_flamingo/chat/conversation.py

@@ -262,7 +262,6 @@ def preprocess_conv(data):
 
 class Chat:
     def __init__(self, model, vis_processor, tokenizer, vis_embed_size ):
-        self.device = device
         self.model = model
         self.vis_processor = vis_processor
         self.tokenizer = tokenizer
@@ -400,20 +399,20 @@ class Chat:
         # self.conv.append_message(self.conv.roles[1], msg)
         return msg
 
-    def get_context_emb(self, conv, img_list):
-        prompt = conv.get_prompt()
-        prompt_segs = prompt.split('<ImageHere>')
-        assert len(prompt_segs) == len(img_list) + 1, "Unmatched numbers of image placeholders and images."
-        seg_tokens = [
-            self.model.llama_tokenizer(
-                seg, return_tensors="pt", add_special_tokens=i == 0).to(self.device).input_ids
-            # only add bos to the first seg
-            for i, seg in enumerate(prompt_segs)
-        ]
-        seg_embs = [self.model.llama_model.model.embed_tokens(seg_t) for seg_t in seg_tokens]
-        mixed_embs = [emb for pair in zip(seg_embs[:-1], img_list) for emb in pair] + [seg_embs[-1]]
-        mixed_embs = torch.cat(mixed_embs, dim=1)
-        return mixed_embs
+    # def get_context_emb(self, conv, img_list):
+    #     prompt = conv.get_prompt()
+    #     prompt_segs = prompt.split('<ImageHere>')
+    #     assert len(prompt_segs) == len(img_list) + 1, "Unmatched numbers of image placeholders and images."
+    #     seg_tokens = [
+    #         self.model.llama_tokenizer(
+    #             seg, return_tensors="pt", add_special_tokens=i == 0).to(self.device).input_ids
+    #         # only add bos to the first seg
+    #         for i, seg in enumerate(prompt_segs)
+    #     ]
+    #     seg_embs = [self.model.llama_model.model.embed_tokens(seg_t) for seg_t in seg_tokens]
+    #     mixed_embs = [emb for pair in zip(seg_embs[:-1], img_list) for emb in pair] + [seg_embs[-1]]
+    #     mixed_embs = torch.cat(mixed_embs, dim=1)
+    #     return mixed_embs
     
 def evaluate_exp(
     model,