From dc463a6b8ef120b7a0643569b66f9109ed38c652 Mon Sep 17 00:00:00 2001
From: Volpeon <git@volpeon.ink>
Date: Sat, 31 Dec 2022 14:07:44 +0100
Subject: Simplified multi-vector embedding code

---
 common.py                |  3 +--
 models/clip/tokenizer.py | 23 +++++++++++------------
 train_ti.py              |  5 ++---
 3 files changed, 14 insertions(+), 17 deletions(-)

diff --git a/common.py b/common.py
index e8d3ac1..1e7f4b9 100644
--- a/common.py
+++ b/common.py
@@ -32,7 +32,6 @@ def load_embeddings_from_dir(tokenizer: MultiCLIPTokenizer, embeddings: ManagedC
                 embed = file.get_tensor("embed")
 
                 added = tokenizer.add_multi_tokens(filename.stem, embed.shape[0])
-                embeddings.add_embed(added.placeholder_id)
-                embeddings.add_embed(added.multi_ids, embed)
+                embeddings.add_embed(added.ids, embed)
 
     return tokens
diff --git a/models/clip/tokenizer.py b/models/clip/tokenizer.py
index 78871db..7e08287 100644
--- a/models/clip/tokenizer.py
+++ b/models/clip/tokenizer.py
@@ -8,8 +8,8 @@ from transformers import CLIPTokenizer
 
 class MultiCLIPTokenizerItem(NamedTuple):
     token: str
-    placeholder_id: int
-    multi_ids: list[int]
+    meta_id: int
+    ids: list[int]
 
 
 class MultiCLIPTokenizer(CLIPTokenizer):
@@ -30,20 +30,19 @@ class MultiCLIPTokenizer(CLIPTokenizer):
         if isinstance(num_vectors, list):
             raise ValueError("Expected num_vectors to be int for single token")
 
-        super().add_tokens(new_tokens)
+        if num_vectors < 1:
+            raise ValueError("Expected num_vectors to be >= 1")
 
-        if num_vectors == 1:
-            multi_token = [new_tokens]
-        else:
-            multi_token = [f"{new_tokens}_{i}" for i in range(num_vectors)]
-            super().add_tokens(multi_token)
+        multi_token = [new_tokens] + [f"{new_tokens}_{i}" for i in range(1, num_vectors)]
 
-        meta_id = super().convert_tokens_to_ids(new_tokens)
-        multi_ids = super().convert_tokens_to_ids(multi_token)
+        super().add_tokens(multi_token)
 
-        self.token_map[meta_id] = multi_ids
+        ids = super().convert_tokens_to_ids(multi_token)
+        meta_id = ids[0]
 
-        return MultiCLIPTokenizerItem(new_tokens, meta_id, multi_ids)
+        self.token_map[meta_id] = ids
+
+        return MultiCLIPTokenizerItem(new_tokens, meta_id, ids)
 
     def encode(self, *args, vector_shuffle=True, **kwargs):
         ids = super().encode(*args, **kwargs)
diff --git a/train_ti.py b/train_ti.py
index 3a5cfed..3776eb2 100644
--- a/train_ti.py
+++ b/train_ti.py
@@ -438,7 +438,7 @@ class Checkpointer(CheckpointerBase):
 
         for new_token in self.new_tokens:
             text_encoder.text_model.embeddings.save_embed(
-                new_token.multi_ids,
+                new_token.ids,
                 checkpoints_path.joinpath(f"{slugify(new_token.token)}_{step}_{postfix}.bin")
             )
 
@@ -537,8 +537,7 @@ def main():
     new_tokens = tokenizer.add_multi_tokens(args.placeholder_token, args.num_vectors)
 
     for (new_token, init_ids) in zip(new_tokens, initializer_token_ids):
-        embeddings.add_embed(new_token.placeholder_id)
-        embeddings.add_embed(new_token.multi_ids, init_ids)
+        embeddings.add_embed(new_token.ids, init_ids)
 
     print(f"Added {len(new_tokens)} new tokens.")
 
-- 
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