added token counter next to txt2img and img2img prompts

1 files changed, 22 insertions, 8 deletions

diff --git a/modules/sd_hijack.py b/modules/sd_hijack.py
index 7b2030d4..4d799ac0 100644
--- a/modules/sd_hijack.py
+++ b/modules/sd_hijack.py
@@ -180,6 +180,7 @@ class StableDiffusionModelHijack:
     dir_mtime = None

     layers = None

     circular_enabled = False

+    clip = None

 

     def load_textual_inversion_embeddings(self, dirname, model):

         mt = os.path.getmtime(dirname)

@@ -242,6 +243,7 @@ class StableDiffusionModelHijack:
 

         model_embeddings.token_embedding = EmbeddingsWithFixes(model_embeddings.token_embedding, self)

         m.cond_stage_model = FrozenCLIPEmbedderWithCustomWords(m.cond_stage_model, self)

+        self.clip = m.cond_stage_model

 

         if cmd_opts.opt_split_attention_v1:

             ldm.modules.attention.CrossAttention.forward = split_cross_attention_forward_v1

@@ -268,6 +270,11 @@ class StableDiffusionModelHijack:
         for layer in [layer for layer in self.layers if type(layer) == torch.nn.Conv2d]:

             layer.padding_mode = 'circular' if enable else 'zeros'

 

+    def tokenize(self, text):

+        max_length = self.clip.max_length - 2

+        _, remade_batch_tokens, _, _, _, token_count = self.clip.process_text([text])

+        return {"tokens": remade_batch_tokens[0], "token_count":token_count, "max_length":max_length}

+        

 

 class FrozenCLIPEmbedderWithCustomWords(torch.nn.Module):

     def __init__(self, wrapped, hijack):

@@ -294,14 +301,16 @@ class FrozenCLIPEmbedderWithCustomWords(torch.nn.Module):
             if mult != 1.0:

                 self.token_mults[ident] = mult

 

-    def forward(self, text):

-        self.hijack.fixes = []

-        self.hijack.comments = []

-        remade_batch_tokens = []

+    def process_text(self, text):

         id_start = self.wrapped.tokenizer.bos_token_id

         id_end = self.wrapped.tokenizer.eos_token_id

         maxlen = self.wrapped.max_length

         used_custom_terms = []

+        remade_batch_tokens = []

+        overflowing_words = []

+        hijack_comments = []

+        hijack_fixes = []

+        token_count = 0

 

         cache = {}

         batch_tokens = self.wrapped.tokenizer(text, truncation=False, add_special_tokens=False)["input_ids"]

@@ -353,9 +362,8 @@ class FrozenCLIPEmbedderWithCustomWords(torch.nn.Module):
                     ovf = remade_tokens[maxlen - 2:]

                     overflowing_words = [vocab.get(int(x), "") for x in ovf]

                     overflowing_text = self.wrapped.tokenizer.convert_tokens_to_string(''.join(overflowing_words))

-

-                    self.hijack.comments.append(f"Warning: too many input tokens; some ({len(overflowing_words)}) have been truncated:\n{overflowing_text}\n")

-

+                    hijack_comments.append(f"Warning: too many input tokens; some ({len(overflowing_words)}) have been truncated:\n{overflowing_text}\n")

+                token_count = len(remade_tokens)

                 remade_tokens = remade_tokens + [id_end] * (maxlen - 2 - len(remade_tokens))

                 remade_tokens = [id_start] + remade_tokens[0:maxlen-2] + [id_end]

                 cache[tuple_tokens] = (remade_tokens, fixes, multipliers)

@@ -364,8 +372,14 @@ class FrozenCLIPEmbedderWithCustomWords(torch.nn.Module):
             multipliers = [1.0] + multipliers[0:maxlen - 2] + [1.0]

 

             remade_batch_tokens.append(remade_tokens)

-            self.hijack.fixes.append(fixes)

+            hijack_fixes.append(fixes)

             batch_multipliers.append(multipliers)

+        return batch_multipliers, remade_batch_tokens, used_custom_terms, hijack_comments, hijack_fixes, token_count

+

+    def forward(self, text):

+        batch_multipliers, remade_batch_tokens, used_custom_terms, hijack_comments, hijack_fixes, token_count = self.process_text(text)

+        self.hijack.fixes = hijack_fixes

+        self.hijack.comments = hijack_comments

 

         if len(used_custom_terms) > 0:

             self.hijack.comments.append("Used custom terms: " + ", ".join([f'{word} [{checksum}]' for word, checksum in used_custom_terms]))