Some refactoring: from_tokens -> encode_from_tokens

comfy/sd.py

@@ -375,13 +375,9 @@ class CLIP:
     def tokenize(self, text, return_word_ids=False):
         return self.tokenizer.tokenize_with_weights(text, return_word_ids)
 
-    def encode(self, text, from_tokens=False):
+    def encode_from_tokens(self, tokens):
         if self.layer_idx is not None:
             self.cond_stage_model.clip_layer(self.layer_idx)
-        if from_tokens:
-            tokens = text
-        else:
-            tokens = self.tokenizer.tokenize_with_weights(text)
         try:
             self.patcher.patch_model()
             cond = self.cond_stage_model.encode_token_weights(tokens)
@@ -391,6 +387,10 @@ class CLIP:
             raise e
         return cond
 
+    def encode(self, text):
+        tokens = self.tokenizer.tokenize_with_weights(text)
+        return self.encode_from_tokens(tokens)
+
 class VAE:
     def __init__(self, ckpt_path=None, scale_factor=0.18215, device=None, config=None):
         if config is None:

comfy/sd1_clip.py

@@ -315,7 +315,7 @@ class SD1Tokenizer:
                         continue
                 #parse word
                 tokens.append([(t, weight) for t in self.tokenizer(word)["input_ids"][1:-1]])
-        
+
         #reshape token array to CLIP input size
         batched_tokens = []
         batch = [(self.start_token, 1.0, 0)]
@@ -338,11 +338,11 @@ class SD1Tokenizer:
                         batch.extend([(pad_token, 1.0, 0)] * (remaining_length))
                     #start new batch
                     batch = [(self.start_token, 1.0, 0)]
-                    batched_tokens.append(batch)    
+                    batched_tokens.append(batch)
                 else:
                     batch.extend([(t,w,i+1) for t,w in t_group])
                     t_group = []
-        
+
         #fill last batch
         batch.extend([(self.end_token, 1.0, 0)] + [(pad_token, 1.0, 0)] * (self.max_length - len(batch) - 1))
 

comfy/sd2_clip.py

@@ -1,4 +1,4 @@
-import sd1_clip
+from comfy import sd1_clip
 import torch
 import os