Drop vendored nnunetv2; depend on upstream pip package (v1.3.0)

BREAKING CHANGE: distillation/nnunetv2/ is removed and replaced with a
pip dependency on nnunetv2>=2.5,<3.0. Users must reinstall to pick up
the new layout.

What changed:
- Removed entire distillation/nnunetv2/ vendored tree (~190 files, 1.7 MB).
  The only file we had authored was nnUNetDistillationTrainer.py; the rest
  was a stale snapshot of upstream nnUNet that the repo had to manually
  keep in sync.
- Moved the trainer to distillation/nnunet_distillation_trainer.py at the
  top of the package so it sits next to the entry-point scripts.
- Updated the four entry-point scripts to import the trainer from its new
  location and dropped the sys.path.insert hack that forced the vendored
  copy to win over pip.
- setup.py: pin nnunetv2>=2.5,<3.0, list nnunet_distillation_trainer in
  py_modules, bump version 1.2.1 -> 1.3.0.

Compatibility fix surfaced by the refactor:
- nnunetv2 2.7 renamed nnUNetLogger to LocalLogger. Updated the trainer's
  import and instantiation accordingly. (The vendored copy hid this drift.)

Verified locally:
- python -m py_compile passes on all touched files.
- After `pip install -e .` in distillation/, the four console entry points
  (nnUNetv2_distillation_train, nnUNetv2_resenc_distillation_train,
  nnUNetv2_distillation_export_onnx, nnUNetv2_resenc_distillation_export_onnx)
  all run --help successfully against pip-installed nnunetv2 2.7.0.
- nnunet_distillation_trainer exposes nnUNetDistillationTrainer,
  nnUNetDistillationTrainerDA5, LiteNNUNetStudent, LiteResEncStudent.

Not yet verified (requires GPU + dataset):
- An end-to-end training step. The autocast/Logger changes need a real
  training run before this is shipped.

Author: 77even

distillation/fast_nnunet_distillation_export_onnx.py

@@ -25,14 +25,10 @@
 import numpy as np
 from batchgenerators.utilities.file_and_folder_operations import join, isfile
 
-# Ensure using nnunetv2 from current directory
-nnunet_dir = os.path.join(os.path.dirname(os.path.abspath(__file__)))
-sys.path.insert(0, nnunet_dir)
-
-# Import paths and related functionalities from nnunetv2
 from nnunetv2.paths import nnUNet_results, nnUNet_raw, nnUNet_preprocessed
 from nnunetv2.utilities.label_handling.label_handling import determine_num_input_channels
-from nnunetv2.training.nnUNetTrainer.variants.nnUNetDistillationTrainer import nnUNetDistillationTrainer, nnUNetDistillationTrainerDA5, LiteNNUNetStudent
+
+from nnunet_distillation_trainer import nnUNetDistillationTrainer, nnUNetDistillationTrainerDA5, LiteNNUNetStudent
 
 def get_dataset_name_from_id(dataset_id):
     """Get the complete dataset name from dataset ID"""

distillation/fast_nnunet_distillation_train.py

@@ -28,17 +28,11 @@
 import json
 from batchgenerators.utilities.file_and_folder_operations import join
 
-# Ensure using nnunetv2 from current directory
-nnunet_dir = os.path.join(os.path.dirname(os.path.abspath(__file__)))
-sys.path.insert(0, nnunet_dir)
-
-# Import paths from nnunetv2
 from nnunetv2.paths import nnUNet_results, nnUNet_raw, nnUNet_preprocessed
-
-# Import nnUNetDistillationTrainer directly
-from nnunetv2.training.nnUNetTrainer.variants.nnUNetDistillationTrainer import nnUNetDistillationTrainer, nnUNetDistillationTrainerDA5
 from nnunetv2.utilities.label_handling.label_handling import determine_num_input_channels
 
+from nnunet_distillation_trainer import nnUNetDistillationTrainer, nnUNetDistillationTrainerDA5
+
 def get_dataset_name_from_id(dataset_id):
     """Get the complete dataset name from dataset ID"""
     # Try to convert dataset_id to integer

distillation/fast_nnunet_resenc_distillation_export_onnx.py

@@ -36,18 +36,12 @@
 from onnxruntime import InferenceSession
 from torch.onnx import export as torch_onnx_export
 
-# Ensure using nnunetv2 from current directory
-nnunet_dir = os.path.join(os.path.dirname(os.path.abspath(__file__)))
-sys.path.insert(0, nnunet_dir)
-
-# Import paths from nnunetv2
 from nnunetv2.paths import nnUNet_results, nnUNet_raw, nnUNet_preprocessed
-
-# Import nnUNetDistillationTrainer directly
-from nnunetv2.training.nnUNetTrainer.variants.nnUNetDistillationTrainer import nnUNetDistillationTrainer, nnUNetDistillationTrainerDA5, LiteNNUNetStudent, LiteResEncStudent
 from nnunetv2.utilities.label_handling.label_handling import determine_num_input_channels
 from nnunetv2.inference.predict_from_raw_data import nnUNetPredictor
 
+from nnunet_distillation_trainer import nnUNetDistillationTrainer, nnUNetDistillationTrainerDA5, LiteNNUNetStudent, LiteResEncStudent
+
 def get_dataset_name_from_id(dataset_id):
     """Get the complete dataset name from dataset ID"""
     # Try to convert dataset_id to integer

distillation/fast_nnunet_resenc_distillation_train.py

@@ -28,17 +28,11 @@
 import json
 from batchgenerators.utilities.file_and_folder_operations import join
 
-# Ensure using nnunetv2 from current directory
-nnunet_dir = os.path.join(os.path.dirname(os.path.abspath(__file__)))
-sys.path.insert(0, nnunet_dir)
-
-# Import paths from nnunetv2
 from nnunetv2.paths import nnUNet_results, nnUNet_raw, nnUNet_preprocessed
-
-# Import nnUNetDistillationTrainer directly
-from nnunetv2.training.nnUNetTrainer.variants.nnUNetDistillationTrainer import nnUNetDistillationTrainer, nnUNetDistillationTrainerDA5
 from nnunetv2.utilities.label_handling.label_handling import determine_num_input_channels
 
+from nnunet_distillation_trainer import nnUNetDistillationTrainer, nnUNetDistillationTrainerDA5
+
 def get_dataset_name_from_id(dataset_id):
     """Get the complete dataset name from dataset ID"""
     # Try to convert dataset_id to integer

…er/variants/nnUNetDistillationTrainer.py …tillation/nnunet_distillation_trainer.pydistillation/nnunetv2/training/nnUNetTrainer/variants/nnUNetDistillationTrainer.py renamed to distillation/nnunet_distillation_trainer.py distillation/nnunetv2/training/nnUNetTrainer/variants/nnUNetDistillationTrainer.py renamed to distillation/nnunet_distillation_trainer.py

@@ -67,7 +67,7 @@ def _default_norm_op_for(conv_op):
 from nnunetv2.utilities.helpers import empty_cache
 from nnunetv2.paths import nnUNet_preprocessed, nnUNet_results
 from nnunetv2.utilities.plans_handling.plans_handler import PlansManager
-from nnunetv2.training.logging.nnunet_logger import nnUNetLogger
+from nnunetv2.training.logging.nnunet_logger import LocalLogger
 from datetime import datetime
 from time import sleep
 import sys
@@ -444,7 +444,7 @@ def patched_init(self, plans, configuration, fold, dataset_json, device):
             self.log_file = join(self.output_folder, "training_log_%d_%d_%d_%02.0d_%02.0d_%02.0d.txt" %
                                  (timestamp.year, timestamp.month, timestamp.day, timestamp.hour, timestamp.minute,
                                   timestamp.second))
-            self.logger = nnUNetLogger()
+            self.logger = LocalLogger()
 
             self.print_to_log_file("\n#######################################################################\n"
                                    "Please cite the following paper when using nnU-Net:\n"