update ft validation api

Author: VipulMascarenhas

ads/aqua/finetuning/finetuning.py

@@ -5,7 +5,7 @@
 
 import json
 import os
-from dataclasses import asdict, fields
+from dataclasses import asdict, fields, MISSING
 from typing import Dict
 
 from oci.data_science.models import (
@@ -586,31 +586,32 @@ def get_finetuning_default_params(self, model_id: str) -> Dict:
 
         return default_params
 
-    def validate_finetuning_params(self, params: List[str] = None) -> Dict:
+    def validate_finetuning_params(self, params: Dict = None) -> Dict:
         """Validate if the fine-tuning parameters passed by the user can be overridden. Parameter values are not
         validated, only param keys are validated.
 
         Parameters
         ----------
-        params : List[str], optional
+        params :Dict, optional
             Params passed by the user.
 
         Returns
         -------
             Return a list of restricted params.
         """
-        restricted_params = []
-        if params:
-            dataclass_fields = {field.name for field in fields(AquaFineTuningParams)}
-            params_dict = get_params_dict(params)
-            for key, items in params_dict.items():
-                key = key.lstrip("--")
-                if key not in dataclass_fields:
-                    restricted_params.append(key)
-
-        if restricted_params:
+        try:
+            AquaFineTuningParams(
+                **params,
+            )
+        except Exception as e:
+            logger.debug(str(e))
+            allowed_fine_tuning_parameters = ", ".join(
+                f"{field.name} (required)" if field.default is MISSING else field.name
+                for field in fields(AquaFineTuningParams)
+            ).rstrip()
             raise AquaValueError(
-                f"Parameters {restricted_params} are set by Aqua "
-                f"and cannot be overridden or are invalid."
+                f"Invalid fine tuning parameters. Allowable parameters are: "
+                f"{allowed_fine_tuning_parameters}."
             )
+
         return dict(valid=True)

tests/unitary/with_extras/aqua/test_finetuning.py

@@ -267,28 +267,28 @@ def test_get_finetuning_default_params(self):
     @parameterized.expand(
         [
             (
-                [
-                    "--batch_size 1",
-                    "--sequence_len 2048",
-                    "--sample_packing true",
-                    "--pad_to_sequence_len true",
-                    "--learning_rate 0.0002",
-                    "--lora_r 32",
-                    "--lora_alpha 16",
-                    "--lora_dropout 0.05",
-                    "--lora_target_linear true",
-                    "--lora_target_modules q_proj,k_proj",
-                ],
+                {
+                    "epochs": 1,
+                    "learning_rate": 0.0002,
+                    "batch_size": 1,
+                    "sequence_len": 2048,
+                    "sample_packing": True,
+                    "pad_to_sequence_len": True,
+                    "lora_alpha": 16,
+                    "lora_dropout": 0.05,
+                    "lora_target_linear": True,
+                    "lora_target_modules": ["q_proj", " k_proj"],
+                },
                 True,
             ),
             (
-                [
-                    "--micro_batch_size 1",
-                    "--max_sequence_len 2048",
-                    "--flash_attention true",
-                    "--pad_to_sequence_len true",
-                    "--lr_scheduler cosine",
-                ],
+                {
+                    "micro_batch_size": 1,
+                    "max_sequence_len": 2048,
+                    "flash_attention": True,
+                    "pad_to_sequence_len": True,
+                    "lr_scheduler": "cosine",
+                },
                 False,
             ),
         ]