1 files changed, 111 insertions, 0 deletions
diff --git a/merge_embeddings.py b/merge_embeddings.py
new file mode 100644
index 0000000..3bb7493
--- /dev/null
+++ b/merge_embeddings.py
@@ -0,0 +1,111 @@
+from ldm.modules.encoders.modules import FrozenCLIPEmbedder, BERTEmbedder
+from ldm.modules.embedding_manager import EmbeddingManager
+
+import argparse, os
+from functools import partial
+
+import torch
+
+def get_placeholder_loop(placeholder_string, embedder, is_sd):
+    
+    new_placeholder   = None
+    
+    while True:
+        if new_placeholder is None:
+            new_placeholder = input(f"Placeholder string {placeholder_string} was already used. Please enter a replacement string: ")
+        else:
+            new_placeholder = input(f"Placeholder string '{new_placeholder}' maps to more than a single token. Please enter another string: ")
+
+        token = get_clip_token_for_string(embedder.tokenizer, new_placeholder) if is_sd else get_bert_token_for_string(embedder.tknz_fn, new_placeholder)
+
+        if token is not None:
+            return new_placeholder, token
+            
+def get_clip_token_for_string(tokenizer, string):
+    batch_encoding = tokenizer(string, truncation=True, max_length=77, return_length=True,
+                               return_overflowing_tokens=False, padding="max_length", return_tensors="pt")
+    tokens = batch_encoding["input_ids"]
+
+    if torch.count_nonzero(tokens - 49407) == 2:
+        return tokens[0, 1]
+    
+    return None
+
+def get_bert_token_for_string(tokenizer, string):
+    token = tokenizer(string)
+    if torch.count_nonzero(token) == 3:
+        return token[0, 1]
+
+    return None
+
+
+if __name__ == "__main__":
+
+    parser = argparse.ArgumentParser()
+
+    parser.add_argument(
+        "--manager_ckpts", 
+        type=str, 
+        nargs="+", 
+        required=True,
+        help="Paths to a set of embedding managers to be merged."
+    )
+
+    parser.add_argument(
+        "--output_path",
+        type=str,
+        required=True,
+        help="Output path for the merged manager",
+    )
+
+    parser.add_argument(
+        "-sd", "--stable_diffusion",
+        action="store_true",
+        help="Flag to denote that we are merging stable diffusion embeddings"
+    )
+
+    args = parser.parse_args()
+
+    if args.stable_diffusion:
+        embedder = FrozenCLIPEmbedder().cuda()
+    else:
+        embedder = BERTEmbedder(n_embed=1280, n_layer=32).cuda()
+
+    EmbeddingManager = partial(EmbeddingManager, embedder, ["*"])
+
+    string_to_token_dict = {}    
+    string_to_param_dict = torch.nn.ParameterDict()
+
+    placeholder_to_src = {}
+
+    for manager_ckpt in args.manager_ckpts:
+        print(f"Parsing {manager_ckpt}...")
+
+        manager = EmbeddingManager()
+        manager.load(manager_ckpt)
+
+        for placeholder_string in manager.string_to_token_dict:
+            if not placeholder_string in string_to_token_dict:
+                string_to_token_dict[placeholder_string] = manager.string_to_token_dict[placeholder_string]
+                string_to_param_dict[placeholder_string] = manager.string_to_param_dict[placeholder_string]
+
+                placeholder_to_src[placeholder_string] = manager_ckpt
+            else:
+                new_placeholder, new_token = get_placeholder_loop(placeholder_string, embedder, is_sd=args.stable_diffusion)
+                string_to_token_dict[new_placeholder] = new_token
+                string_to_param_dict[new_placeholder] = manager.string_to_param_dict[placeholder_string]
+
+                placeholder_to_src[new_placeholder] = manager_ckpt
+
+    print("Saving combined manager...")
+    merged_manager = EmbeddingManager()
+    merged_manager.string_to_param_dict = string_to_param_dict
+    merged_manager.string_to_token_dict = string_to_token_dict
+    merged_manager.save(args.output_path)
+
+    print("Managers merged. Final list of placeholders: ")
+    print(placeholder_to_src)
+
+
+
+