fix more

llmfoundry/models/hf/hf_causal_lm.py

@@ -100,8 +100,7 @@ def __init__(
                 'use_flash_attention_2 is set to True, but flash-attention 2 is not installed. '
                 + 'Please `pip install llm-foundry[gpu]`.')
 
-        peft_config_dict = peft_config
-        if peft_config_dict is not None and not peft_installed:
+        if peft_config is not None and not peft_installed:
             raise ValueError(
                 'PEFT is not installed, but peft_config was passed. Please install LLM Foundry with the peft extra to use peft_config.'
             )
@@ -248,8 +247,8 @@ def _autoset_attn_implementation_monkeypatch(
             model.tie_weights()
 
         peft_config = None
-        if peft_config_dict is not None:
-            peft_config = self._get_peft_config(peft_config_dict)
+        if peft_config is not None:
+            peft_config = self._get_peft_config(peft_config)
 
         if pretrained_lora_id_or_path is not None:
             if not peft_installed:

llmfoundry/utils/builders.py

@@ -376,10 +376,6 @@ def _extract_param_groups(
 def build_optimizer(model: torch.nn.Module, name: str,
                     optimizer_config: Dict[str, Any]) -> Optimizer:
 
-    for k, v in optimizer_config.items():
-        if isinstance(v, DictConfig):
-            optimizer_config[k] = om.to_container(v, resolve=True)
-
     params = _extract_param_groups(model, optimizer_config)
     kwargs = {**optimizer_config}
 

llmfoundry/utils/mosaicml_logger_utils.py

@@ -8,7 +8,6 @@
 from composer.loggers.logger_destination import LoggerDestination
 from composer.loggers.mosaicml_logger import (MOSAICML_ACCESS_TOKEN_ENV_VAR,
                                               MOSAICML_PLATFORM_ENV_VAR)
-from omegaconf import DictConfig, ListConfig
 
 _MODEL_KEYS_TO_LOG = [
     'pretrained_model_name_or_path',
@@ -38,9 +37,10 @@ def find_mosaicml_logger(
 
 
 def log_eval_analytics(mosaicml_logger: MosaicMLLogger,
-                       model_configs: ListConfig, icl_tasks: Union[str,
-                                                                   ListConfig],
-                       eval_gauntlet_config: Optional[Union[str, DictConfig]]):
+                       model_configs: List[Dict[str, Any]],
+                       icl_tasks: Union[str, List[Dict[str, Any]]],
+                       eval_gauntlet_config: Optional[Union[str, Dict[str,
+                                                                      Any]]]):
     """Logs analytics for runs using the `eval.py` script."""
     metrics: Dict[str, Any] = {
         'llmfoundry/script': 'eval',
@@ -67,14 +67,17 @@ def log_eval_analytics(mosaicml_logger: MosaicMLLogger,
 
 
 def log_train_analytics(mosaicml_logger: MosaicMLLogger,
-                        model_config: DictConfig,
-                        train_loader_config: DictConfig,
-                        eval_loader_config: Optional[Union[DictConfig,
-                                                           ListConfig]],
+                        model_config: Dict[str,
+                                           Any], train_loader_config: Dict[str,
+                                                                           Any],
+                        eval_loader_config: Optional[Union[Dict[str, Any],
+                                                           List[Dict[str,
+                                                                     Any]]]],
                         callback_configs: Optional[Dict[str, Any]],
                         tokenizer_name: str, load_path: Optional[str],
-                        icl_tasks_config: Optional[Union[ListConfig, str]],
-                        eval_gauntlet: Optional[Union[DictConfig, str]]):
+                        icl_tasks_config: Optional[Union[List[Dict[str, Any]],
+                                                         str]],
+                        eval_gauntlet: Optional[Union[Dict[str, Any], str]]):
     """Logs analytics for runs using the `train.py` script."""
     train_loader_dataset = train_loader_config.get('dataset', {})
     metrics: Dict[str, Any] = {
@@ -106,10 +109,10 @@ def log_train_analytics(mosaicml_logger: MosaicMLLogger,
     if eval_loader_config is not None:
         metrics['llmfoundry/eval_loaders'] = []
 
-        if isinstance(eval_loader_config, ListConfig):
-            eval_loader_configs: ListConfig = eval_loader_config
+        if isinstance(eval_loader_config, list):
+            eval_loader_configs: list = eval_loader_config
         else:
-            eval_loader_configs = ListConfig([eval_loader_config])
+            eval_loader_configs = [eval_loader_config]
 
         for loader_config in eval_loader_configs:
             eval_loader_info = {}

scripts/eval/eval.py

@@ -59,11 +59,7 @@ def evaluate_model(
     logged_config: DictConfig,
     should_log_config: bool = True,
     load_path: Optional[str] = None,
-    **kwargs: Dict[str, Any],
 ):
-    model_extra_params = kwargs
-    warnings.warn(f'Extra parameters: {model_extra_params}')
-
     log.info(f'Evaluating model: {model_name}')
     # Build tokenizer and model
     tokenizer_cfg = tokenizer
@@ -103,7 +99,7 @@ def evaluate_model(
             'The FSDP config block is not supported when loading ' +
             'Hugging Face models in 8bit.')
 
-    init_context = process_init_device(DictConfig(model), fsdp_config)
+    init_context = process_init_device(model, fsdp_config)
 
     name = model.pop('name')
     composer_model = build_composer_model(name=name,
@@ -189,7 +185,7 @@ class EvalConfig:
     icl_tasks_str: Optional[str] = None
 
     # Logging parameters
-    python_log_level: Optional[str] = None
+    python_log_level: str = 'debug'
     loggers: Optional[Dict[str, Any]] = None
     log_config: bool = True
 
@@ -299,15 +295,14 @@ def main(cfg: DictConfig) -> Tuple[List[Trainer], pd.DataFrame]:
     reproducibility.seed_all(eval_config.seed)
     dist.initialize_dist(get_device(None), timeout=eval_config.dist_timeout)
 
-    if eval_config.python_log_level is not None:
-        logging.basicConfig(
-            # Example of format string
-            # 2022-06-29 11:22:26,152: rank0[822018][MainThread]: INFO: Message here
-            format=
-            f'%(asctime)s: rank{dist.get_global_rank()}[%(process)d][%(threadName)s]: %(levelname)s: %(name)s: %(message)s'
-        )
-        logging.getLogger('llmfoundry').setLevel(
-            eval_config.python_log_level.upper())
+    logging.basicConfig(
+        # Example of format string
+        # 2022-06-29 11:22:26,152: rank0[822018][MainThread]: INFO: Message here
+        format=
+        f'%(asctime)s: rank{dist.get_global_rank()}[%(process)d][%(threadName)s]: %(levelname)s: %(name)s: %(message)s'
+    )
+    logging.getLogger('llmfoundry').setLevel(
+        eval_config.python_log_level.upper())
 
     # Default argument values for evaluate_model
     eval_gauntlet_df = None