Improve algorithm validation messages.

exareme2/controller/services/api/algorithm_request_validator.py

@@ -54,7 +54,7 @@ def validate_algorithm_request(
     (
         training_datasets,
         validation_datasets,
-    ) = worker_landscape_aggregator.get_train_and_validation_datasets(
+    ) = worker_landscape_aggregator.get_training_and_validation_datasets(
         algorithm_request_dto.inputdata.data_model
     )
     data_model_cdes = worker_landscape_aggregator.get_cdes(
@@ -92,14 +92,11 @@ def _validate_algorithm_request_body(
     smpc_enabled: bool,
     smpc_optional: bool,
 ):
-    _ensure_validation_criteria(
-        algorithm_request_dto.inputdata.validation_datasets,
-        algorithm_specs.inputdata.validation,
-    )
     _validate_inputdata(
         inputdata=algorithm_request_dto.inputdata,
         inputdata_specs=algorithm_specs.inputdata,
         training_datasets=training_datasets,
+        algorithm_specification_validation_flag=algorithm_specs.inputdata.validation,
         validation_datasets=validation_datasets,
         data_model_cdes=data_model_cdes,
     )
@@ -125,42 +122,23 @@ def _validate_algorithm_request_body(
     )
 
 
-def _ensure_validation_criteria(validation_datasets: List[str], validation: bool):
-    """
-    Validates the input based on the provided validation flag and datasets.
-
-    Parameters:
-        validation_datasets (List[str]): List of validation datasets.
-        validation (bool): Flag indicating if validation is required.
-
-    Raises:
-        BadUserInput: If the input conditions are not met.
-    """
-    if not validation and validation_datasets:
-        raise BadUserInput(
-            "Validation is false, but validation datasets were provided."
-        )
-    elif validation and not validation_datasets:
-        raise BadUserInput(
-            "Validation is true, but no validation datasets were provided."
-        )
-
-
 def _validate_inputdata(
     inputdata: AlgorithmInputDataDTO,
     inputdata_specs: InputDataSpecifications,
     training_datasets: List[str],
+    algorithm_specification_validation_flag: Optional[bool],
     validation_datasets: List[str],
     data_model_cdes: Dict[str, CommonDataElement],
 ):
     _validate_inputdata_training_datasets(
         requested_data_model=inputdata.data_model,
-        requested_datasets=inputdata.datasets,
+        requested_training_datasets=inputdata.datasets,
         training_datasets=training_datasets,
     )
     _validate_inputdata_validation_datasets(
         requested_data_model=inputdata.data_model,
         requested_validation_datasets=inputdata.validation_datasets,
+        algorithm_specification_validation_flag=algorithm_specification_validation_flag,
         validation_datasets=validation_datasets,
     )
     _validate_inputdata_filter(inputdata.data_model, inputdata.filters, data_model_cdes)
@@ -169,14 +147,16 @@ def _validate_inputdata(
 
 def _validate_inputdata_training_datasets(
     requested_data_model: str,
-    requested_datasets: List[str],
+    requested_training_datasets: List[str],
     training_datasets: List[str],
 ):
     """
-    Validates that the dataset values exist and that the datasets.
+    Validates that the dataset values exist.
     """
     non_existing_datasets = [
-        dataset for dataset in requested_datasets if dataset not in training_datasets
+        dataset
+        for dataset in requested_training_datasets
+        if dataset not in training_datasets
     ]
     if non_existing_datasets:
         raise BadUserInput(
@@ -187,11 +167,21 @@ def _validate_inputdata_training_datasets(
 def _validate_inputdata_validation_datasets(
     requested_data_model: str,
     requested_validation_datasets: List[str],
+    algorithm_specification_validation_flag,
     validation_datasets: List[str],
 ):
     """
-    Validates that the validation dataset values exist and that the validation_datasets.
+    Validates that the validation dataset values exist.
     """
+    if not algorithm_specification_validation_flag and requested_validation_datasets:
+        raise BadUserInput(
+            "The algorithm does not have a validation flow, but 'validation_datasets' were provided in the 'inputdata'."
+        )
+    elif algorithm_specification_validation_flag and not requested_validation_datasets:
+        raise BadUserInput(
+            "The algorithm requires 'validation_datasets', in the 'inputdata', but none were provided."
+        )
+
     if not requested_validation_datasets:
         return
 

exareme2/controller/services/api/algorithm_spec_dtos.py

@@ -122,7 +122,7 @@ def _get_data_model_input_data_specification_dto():
     )
 
 
-def _get_valiadtion_datasets_input_data_specification_dto():
+def _get_validation_datasets_input_data_specification_dto():
     return InputDataSpecificationDTO(
         label="Set of data to validate.",
         desc="The set of data to validate the algorithm model on.",
@@ -163,15 +163,15 @@ def _convert_inputdata_specifications_to_dto(spec: InputDataSpecifications):
     # These parameters are not added by the algorithm developer.
     y = _convert_inputdata_specification_to_dto(spec.y)
     x = _convert_inputdata_specification_to_dto(spec.x) if spec.x else None
-    validation_datasets = (
-        _get_valiadtion_datasets_input_data_specification_dto()
+    validation_datasets_dto = (
+        _get_validation_datasets_input_data_specification_dto()
         if spec.validation
         else None
     )
     return InputDataSpecificationsDTO(
         y=y,
         x=x,
-        validation_datasets=validation_datasets,
+        validation_datasets=validation_datasets_dto,
         data_model=_get_data_model_input_data_specification_dto(),
         datasets=_get_datasets_input_data_specification_dto(),
         filter=_get_filters_input_data_specification_dto(),

exareme2/controller/services/worker_landscape_aggregator/worker_landscape_aggregator.py

@@ -516,7 +516,7 @@ def get_cdes_per_data_model(self) -> DataModelsCDES:
     def get_datasets_locations(self) -> DatasetsLocations:
         return self._registries.data_model_registry.datasets_locations
 
-    def get_train_and_validation_datasets(
+    def get_training_and_validation_datasets(
         self, data_model: str
     ) -> Tuple[List[str], List[str]]:
         """
@@ -527,8 +527,8 @@ def get_train_and_validation_datasets(
 
         Returns:
             Tuple[List[str], List[str]]: A tuple containing two lists:
-                - The first list contains training datasets.
-                - The second list contains validation datasets.
+                - The first list contains training datasets (Data loaded inside the localworkers).
+                - The second list contains validation datasets (Data loaded inside the globalworker).
         """
         training_datasets = []
         validation_datasets = []

tests/standalone_tests/controller/services/api/test_validate_algorithm_request.py

@@ -1412,7 +1412,7 @@ def get_parametrization_list_exception_cases():
             ),
             (
                 BadUserInput,
-                "Validation is false, but validation datasets were provided.",
+                "The algorithm does not have a validation flow, but 'validation_datasets' were provided in the 'inputdata'.",
             ),
             id="Validation datasets on algorithm without validation",
         ),
@@ -1428,7 +1428,7 @@ def get_parametrization_list_exception_cases():
             ),
             (
                 BadUserInput,
-                "Validation is true, but no validation datasets were provided.",
+                "The algorithm requires 'validation_datasets', in the 'inputdata', but none were provided.",
             ),
             id="Missing validation datasets on algorithm validation",
         ),