fix(dataset): normalize tokenizer config and change hash from tokenizer class to tokenizer path (#1298)

* fix(dataset): normalize tokenizer config and change hash from tokenizer class to tokenizer path

* fix: normalize config

src/axolotl/utils/config/__init__.py

@@ -119,6 +119,10 @@ def normalize_config(cfg):
     model_config = load_model_config(cfg)
     cfg.model_config_type = model_config.model_type
 
+    cfg.tokenizer_config = (
+        cfg.tokenizer_config or cfg.base_model_config or cfg.base_model
+    )
+
     # figure out if the model is llama
     cfg.is_llama_derived_model = (
         (hasattr(model_config, "model_type") and model_config.model_type == "llama")

src/axolotl/utils/data.py

@@ -134,7 +134,7 @@ def load_tokenized_prepared_datasets(
     split="train",
 ) -> Tuple[DatasetDict, List[Prompter]]:
     cfg_datasets = cfg.test_datasets if split == "test" else cfg.datasets
-    tokenizer_name = tokenizer.__class__.__name__
+    tokenizer_name = cfg.tokenizer_config
     ds_hash = str(
         md5(
             (

src/axolotl/utils/models.py

@@ -134,9 +134,8 @@ def load_tokenizer(cfg):
     if cfg.tokenizer_type:
         tokenizer_cls = getattr(transformers, cfg.tokenizer_type)
 
-    tokenizer_config = cfg.tokenizer_config or cfg.base_model_config or cfg.base_model
     tokenizer = tokenizer_cls.from_pretrained(
-        tokenizer_config,
+        cfg.tokenizer_config,
         trust_remote_code=cfg.trust_remote_code or False,
         use_fast=use_fast,
         **tokenizer_kwargs,

tests/core/test_trainer_builder.py

@@ -1,16 +1,18 @@
 """
 unit tests for axolotl.core.trainer_builder
 """
+
 import pytest
 
 from axolotl.core.trainer_builder import HFDPOTrainerBuilder
+from axolotl.utils.config import normalize_config
 from axolotl.utils.dict import DictDefault
 from axolotl.utils.models import load_model, load_tokenizer
 
 
 @pytest.fixture(name="cfg")
 def fixture_cfg():
-    return DictDefault(
+    cfg = DictDefault(
         {
             "base_model": "TinyLlama/TinyLlama-1.1B-Chat-v0.6",
             "model_type": "AutoModelForCausalLM",
@@ -34,6 +36,10 @@ def fixture_cfg():
         }
     )
 
+    normalize_config(cfg)
+
+    return cfg
+
 
 @pytest.fixture(name="tokenizer")
 def fixture_tokenizer(cfg):