first try after rebase and new config

clinicadl/commandline/pipelines/prepare_data/prepare_data_cli.py

@@ -12,12 +12,6 @@
     preprocessing,
 )
 from clinicadl.prepare_data.prepare_data import DeepLearningPrepareData
-from clinicadl.prepare_data.prepare_data_config import (
-    PrepareDataImageConfig,
-    PrepareDataPatchConfig,
-    PrepareDataROIConfig,
-    PrepareDataSliceConfig,
-)
 from clinicadl.utils.enum import (
     BIDSModality,
     DTIMeasure,

clinicadl/interpret/config.py

@@ -10,12 +10,10 @@
     load_data_test,
 )
 from clinicadl.caps_dataset.dataloader_config import DataLoaderConfig
-from clinicadl.config.config import (
-    ComputationalConfig,
-    CrossValidationConfig,
-    MapsManagerConfig,
-    ValidationConfig,
-)
+from clinicadl.config.config.computational import ComputationalConfig
+from clinicadl.config.config.cross_validation import CrossValidationConfig
+from clinicadl.config.config.maps_manager import MapsManagerConfig
+from clinicadl.config.config.validation import ValidationConfig
 from clinicadl.interpret.gradients import GradCam, Gradients, VanillaBackProp
 from clinicadl.utils.enum import InterpretationMethod
 

clinicadl/predict/predict_manager.py

@@ -11,7 +11,7 @@
 from torch.utils.data import DataLoader
 from torch.utils.data.distributed import DistributedSampler
 
-from clinicadl.caps_dataset.data_utils import (
+from clinicadl.caps_dataset.data import (
     return_dataset,
 )
 from clinicadl.interpret.config import InterpretConfig

clinicadl/quality_check/pet_linear/cli.py

@@ -1,7 +1,12 @@
 import click
 
-from clinicadl.config import arguments
-from clinicadl.config.options import data, dataloader, modality, preprocessing
+from clinicadl.commandline import arguments
+from clinicadl.commandline.modules_options import (
+    data,
+    dataloader,
+    modality,
+    preprocessing,
+)
 
 
 @click.command(name="pet-linear", no_args_is_help=True)

clinicadl/quality_check/t1_linear/cli.py

@@ -2,8 +2,8 @@
 
 import click
 
-from clinicadl.config import arguments
-from clinicadl.config.options import (
+from clinicadl.commandline import arguments
+from clinicadl.commandline.modules_options import (
     computational,
     data,
     dataloader,

clinicadl/quality_check/t1_volume/cli.py

@@ -1,7 +1,7 @@
 import click
 
-from clinicadl.config import arguments
-from clinicadl.config.options import (
+from clinicadl.commandline import arguments
+from clinicadl.commandline.modules_options import (
     computational,
     data,
     dataloader,

clinicadl/trainer/config/classification.py

@@ -4,8 +4,8 @@
 from pydantic import computed_field, field_validator
 
 from clinicadl.caps_dataset.data_config import DataConfig as BaseDataConfig
-from clinicadl.config.config import NetworkConfig as BaseNetworkConfig
-from clinicadl.config.config import ValidationConfig as BaseValidationConfig
+from clinicadl.config.config.validation import ValidationConfig as BaseValidationConfig
+from clinicadl.network.config import NetworkConfig as BaseNetworkConfig
 from clinicadl.trainer.config.train import TrainConfig
 from clinicadl.utils.enum import ClassificationLoss, ClassificationMetric, Task
 

clinicadl/trainer/config/reconstruction.py

@@ -4,8 +4,8 @@
 
 from pydantic import PositiveFloat, PositiveInt, computed_field, field_validator
 
-from clinicadl.config.config import NetworkConfig as BaseNetworkConfig
-from clinicadl.config.config import ValidationConfig as BaseValidationConfig
+from clinicadl.config.config.validation import ValidationConfig as BaseValidationConfig
+from clinicadl.network.config import NetworkConfig as BaseNetworkConfig
 from clinicadl.trainer.config.train import TrainConfig
 from clinicadl.utils.enum import (
     Normalization,

clinicadl/trainer/config/regression.py

@@ -5,8 +5,8 @@
 from pydantic import PositiveFloat, PositiveInt, computed_field, field_validator
 
 from clinicadl.caps_dataset.data_config import DataConfig as BaseDataConfig
-from clinicadl.config.config import NetworkConfig as BaseNetworkConfig
-from clinicadl.config.config import ValidationConfig as BaseValidationConfig
+from clinicadl.config.config.validation import ValidationConfig as BaseValidationConfig
+from clinicadl.network.config import NetworkConfig as BaseNetworkConfig
 from clinicadl.trainer.config.train import TrainConfig
 from clinicadl.utils.enum import RegressionLoss, RegressionMetric, Task
 

clinicadl/trainer/config/train.py

@@ -10,21 +10,19 @@
 from clinicadl.callbacks.config import CallbacksConfig
 from clinicadl.caps_dataset.data_config import DataConfig
 from clinicadl.caps_dataset.dataloader_config import DataLoaderConfig
-from clinicadl.config.config import (
-    ComputationalConfig,
-    CrossValidationConfig,
-    EarlyStoppingConfig,
-    LRschedulerConfig,
-    MapsManagerConfig,
-    ReproducibilityConfig,
-    SSDAConfig,
-    TransferLearningConfig,
-    TransformsConfig,
-    ValidationConfig,
-)
+from clinicadl.config.config.computational import ComputationalConfig
+from clinicadl.config.config.cross_validation import CrossValidationConfig
+from clinicadl.config.config.early_stopping import EarlyStoppingConfig
+from clinicadl.config.config.lr_scheduler import LRschedulerConfig
+from clinicadl.config.config.maps_manager import MapsManagerConfig
+from clinicadl.config.config.reproducibility import ReproducibilityConfig
+from clinicadl.config.config.ssda import SSDAConfig
+from clinicadl.config.config.transfer_learning import TransferLearningConfig
+from clinicadl.config.config.validation import ValidationConfig
 from clinicadl.network.config import NetworkConfig
 from clinicadl.optimizer.optimization import OptimizationConfig
 from clinicadl.optimizer.optimizer import OptimizerConfig
+from clinicadl.transforms.config import TransformsConfig
 from clinicadl.utils.enum import Task
 
 logger = getLogger("clinicadl.training_config")

clinicadl/trainer/trainer.py

@@ -14,7 +14,7 @@
 from torch.utils.data import DataLoader
 from torch.utils.data.distributed import DistributedSampler
 
-from clinicadl.caps_dataset.data_utils import return_dataset
+from clinicadl.caps_dataset.data import return_dataset
 from clinicadl.utils.early_stopping import EarlyStopping
 from clinicadl.utils.exceptions import MAPSError
 from clinicadl.utils.maps_manager.ddp import DDP, cluster