tests ok

clinicadl/interpret/config.py

@@ -1,21 +1,33 @@
 from logging import getLogger
 from pathlib import Path
-from typing import Optional
+from typing import Any, Dict, Optional
 
 from pydantic import BaseModel, field_validator
 
 from clinicadl.caps_dataset.data_config import DataConfig as DataBaseConfig
 from clinicadl.caps_dataset.dataloader_config import DataLoaderConfig
 from clinicadl.interpret.gradients import GradCam, Gradients, VanillaBackProp
-from clinicadl.maps_manager.config import MapsManagerConfig
+from clinicadl.maps_manager.config import MapsManagerConfigBase
+from clinicadl.maps_manager.maps_manager import MapsManager
 from clinicadl.predictor.validation import ValidationConfig
 from clinicadl.splitter.config import SplitConfig
+from clinicadl.transforms.config import TransformsConfig
 from clinicadl.utils.computational.computational import ComputationalConfig
 from clinicadl.utils.enum import InterpretationMethod
+from clinicadl.utils.exceptions import ClinicaDLArgumentError
 
 logger = getLogger("clinicadl.interpret_config")
 
 
+class MapsManagerConfig(MapsManagerConfigBase):
+    def check_output_saving_tensor(self, network_task: str) -> None:
+        # Check if task is reconstruction for "save_tensor" and "save_nifti"
+        if self.save_tensor and network_task != "reconstruction":
+            raise ClinicaDLArgumentError(
+                "Cannot save tensors if the network task is not reconstruction. Please remove --save_tensor option."
+            )
+
+
 class DataConfig(DataBaseConfig):
     caps_directory: Optional[Path] = None
 
@@ -54,3 +66,54 @@ class InterpretConfig(BaseModel):
     dataloader: DataLoaderConfig
     split: SplitConfig
     interpret: InterpretBaseConfig
+
+    def __init__(self, **kwargs):
+        super().__init__(
+            maps_manager=kwargs,
+            computational=kwargs,
+            dataloader=kwargs,
+            data=kwargs,
+            split=kwargs,
+            validation=kwargs,
+            transforms=kwargs,
+        )
+
+    def _update(self, config_dict: Dict[str, Any]) -> None:
+        """Updates the configs with a dict given by the user."""
+        self.data.__dict__.update(config_dict)
+        self.split.__dict__.update(config_dict)
+        self.validation.__dict__.update(config_dict)
+        self.maps_manager.__dict__.update(config_dict)
+        self.split.__dict__.update(config_dict)
+        self.computational.__dict__.update(config_dict)
+        self.dataloader.__dict__.update(config_dict)
+        self.transforms.__dict__.update(config_dict)
+
+    def adapt_with_maps_manager_info(self, maps_manager: MapsManager):
+        self.maps_manager.check_output_saving_nifti(maps_manager.network_task)
+        self.data.diagnoses = (
+            maps_manager.diagnoses
+            if self.data.diagnoses is None or len(self.data.diagnoses) == 0
+            else self.data.diagnoses
+        )
+
+        self.dataloader.batch_size = (
+            maps_manager.batch_size
+            if not self.dataloader.batch_size
+            else self.dataloader.batch_size
+        )
+        self.dataloader.n_proc = (
+            maps_manager.n_proc
+            if not self.dataloader.n_proc
+            else self.dataloader.n_proc
+        )
+
+        self.split.adapt_cross_val_with_maps_manager_info(maps_manager)
+        self.maps_manager.check_output_saving_tensor(maps_manager.network_task)
+
+        self.transforms = TransformsConfig(
+            normalize=maps_manager.normalize,
+            data_augmentation=maps_manager.data_augmentation,
+            size_reduction=maps_manager.size_reduction,
+            size_reduction_factor=maps_manager.size_reduction_factor,
+        )