[advanced dreambooth lora training script][bug_fix] change token_abstraction type to str (huggingface#6040)

* improve help tags

* style fix

* changes token_abstraction type to string.
support multiple concepts for pivotal using a comma separated string.

* style fixup

* changed logger to warning (not yet available)

* moved the token_abstraction parsing to be in the same block as where we create the mapping of identifier to token

---------

Co-authored-by: Linoy <[email protected]>

Author: linoytsaban

examples/advanced_diffusion_training/train_dreambooth_lora_sdxl_advanced.py

@@ -300,16 +300,18 @@ def parse_args(input_args=None):
     )
     parser.add_argument(
         "--token_abstraction",
+        type=str,
         default="TOK",
         help="identifier specifying the instance(or instances) as used in instance_prompt, validation prompt, "
-        "captions - e.g. TOK",
+        "captions - e.g. TOK. To use multiple identifiers, please specify them in a comma seperated string - e.g. "
+        "'TOK,TOK2,TOK3' etc.",
     )
 
     parser.add_argument(
         "--num_new_tokens_per_abstraction",
         type=int,
         default=2,
-        help="number of new tokens inserted to the tokenizers per token_abstraction value when "
+        help="number of new tokens inserted to the tokenizers per token_abstraction identifier when "
         "--train_text_encoder_ti = True. By default, each --token_abstraction (e.g. TOK) is mapped to 2 new "
         "tokens - <si><si+1> ",
     )
@@ -660,17 +662,6 @@ def parse_args(input_args=None):
             "inversion training check `--train_text_encoder_ti`"
         )
 
-    if args.train_text_encoder_ti:
-        if isinstance(args.token_abstraction, str):
-            args.token_abstraction = [args.token_abstraction]
-        elif isinstance(args.token_abstraction, List):
-            args.token_abstraction = args.token_abstraction
-        else:
-            raise ValueError(
-                f"Unsupported type for --args.token_abstraction: {type(args.token_abstraction)}. "
-                f"Supported types are: str (for a single instance identifier) or List[str] (for multiple concepts)"
-            )
-
     env_local_rank = int(os.environ.get("LOCAL_RANK", -1))
     if env_local_rank != -1 and env_local_rank != args.local_rank:
         args.local_rank = env_local_rank
@@ -1155,9 +1146,14 @@ def main(args):
     )
 
     if args.train_text_encoder_ti:
+        # we parse the provided token identifier (or identifiers) into a list. s.t. - "TOK" -> ["TOK"], "TOK,
+        # TOK2" -> ["TOK", "TOK2"] etc.
+        token_abstraction_list = "".join(args.token_abstraction.split()).split(",")
+        logger.info(f"list of token identifiers: {token_abstraction_list}")
+
         token_abstraction_dict = {}
         token_idx = 0
-        for i, token in enumerate(args.token_abstraction):
+        for i, token in enumerate(token_abstraction_list):
             token_abstraction_dict[token] = [
                 f"<s{token_idx + i + j}>" for j in range(args.num_new_tokens_per_abstraction)
             ]