Update from dev branch: v0.0.9 release

CHANGELOG.md

@@ -1,15 +1,33 @@
 # Upcoming Release
 
-(The updated changelog in pre-release will be included in stable release, `v0.0.9`)
+## New Features:
+
+No changes to highlight.
+
+## Bug Fixes:
+
+No changes to highlight.
+
+## Breaking Changes:
+
+No changes to highlight.
+
+## Other Changes:
+
+No changes to highlight.
+
+# v0.0.9
 
 ## New Features:
 
-- Add CSPDarknet by `@illian01` in [PR 195](https://github.com/Nota-NetsPresso/netspresso-trainer/pull/195)
+- Add YOLOX model by `@illian01` in [PR 195](https://github.com/Nota-NetsPresso/netspresso-trainer/pull/195), [PR 212](https://github.com/Nota-NetsPresso/netspresso-trainer/pull/212)
 - Fix Faster R-CNN detection head to compat with PyNP compressor by `@illian01` in [PR 184](https://github.com/Nota-NetsPresso/netspresso-trainer/pull/184), [PR 194](https://github.com/Nota-NetsPresso/netspresso-trainer/pull/194), [PR 204](https://github.com/Nota-NetsPresso/netspresso-trainer/pull/204)
+- Support multi-GPU training with `netspresso-train` entrypoint by `@deepkyu`, `@illian01` and `@Only-bottle` in [PR 213](https://github.com/Nota-NetsPresso/netspresso-trainer/pull/213)
 
 ## Bug Fixes:
 
 - Remove fx training flag in entry point by `@illian01` in [PR 188](https://github.com/Nota-NetsPresso/netspresso-trainer/pull/188)
+- Fix bounding box coordinates computing error on random flip augmentation by `@illian01` in [PR 211](https://github.com/Nota-NetsPresso/netspresso-trainer/pull/211)
 
 ## Breaking Changes:
 
@@ -22,6 +40,7 @@
 - Parameterize activation function of BasicBlock and Bottleneck by `@illian01` in [PR193](https://github.com/Nota-NetsPresso/netspresso-trainer/pull/193)
 - Modify MobileNetV3 to stage format and remove forward hook by `@illian01` in [PR 199](https://github.com/Nota-NetsPresso/netspresso-trainer/pull/199)
 - Substitute MACs counter with `fvcore` library to sync with NetsPresso by `@deepkyu` and `@Only-bottle` in [PR 202](https://github.com/Nota-NetsPresso/netspresso-trainer/pull/202)
+- Enable to compute metric with all training samples by `@illian01` in [PR 210](https://github.com/Nota-NetsPresso/netspresso-trainer/pull/210)
 
 # v0.0.8
 

config/model/yolox/yolox-detection.yaml

@@ -0,0 +1,17 @@
+model:
+  task: detection
+  checkpoint: ./weights/yolox/yolox_s.pth
+  fx_model_checkpoint: ~
+  resume_optimizer_checkpoint: ~
+  freeze_backbone: False
+  architecture:
+    full: ~ # auto
+    backbone:
+      name: cspdarknet
+      dep_mul: 0.33
+      wid_mul: 0.5
+    head:
+      name: yolo_head
+  losses:
+    - criterion: yolox_loss
+      weight: ~

scripts/example_train.sh

@@ -107,34 +107,11 @@ netspresso-train\
 # Put the number of GPU(s) to use in training at `--nproc_per_node`
 #### (END)
 
-# python -m torch.distributed.launch\
-#   --nproc_per_node 4\
-#   train.py\
-#   --data config/data/chess.yaml\
+# netspresso-train\
+#   --gpus 0,1,2,3\
+#   --data config/data/beans.yaml\
 #   --augmentation config/augmentation/classification.yaml\
 #   --model config/model/resnet/resnet50-classification.yaml\
 #   --training config/training/classification.yaml\
 #   --logging config/logging.yaml\
-#   --environment config/environment.yaml
-
-
-# python -m torch.distributed.launch\
-#   --nproc_per_node 4\
-#   train.py\
-#   --data config/data/sidewalk-semantic.yaml\
-#   --augmentation config/augmentation/segmentation.yaml\
-#   --model config/model/pidnet/pidnet-s-segmentation.yaml\
-#   --training config/training/segmentation.yaml\
-#   --logging config/logging.yaml\
-#   --environment config/environment.yaml
-
-
-# python -m torch.distributed.launch\
-#   --nproc_per_node 4\
-#   train.py\
-#   --data config/data/traffic-sign.yaml\
-#   --augmentation config/augmentation/detection.yaml\
-#   --model config/model/efficientformer/efficientformer-l1-detection.yaml\
-#   --training config/training/detection.yaml\
-#   --logging config/logging.yaml\
 #   --environment config/environment.yaml

setup.py

@@ -26,7 +26,7 @@
     python_requires=">=3.8",
     entry_points={
         "console_scripts": [
-            "netspresso-train = netspresso_trainer.train:train_with_yaml",
+            "netspresso-train = netspresso_trainer.trainer_cli:train_cli",
         ],
     },
     classifiers=[

src/netspresso_trainer/VERSION

@@ -1 +1 @@
-0.0.9.b0
+0.0.9

src/netspresso_trainer/__init__.py

@@ -1,9 +1,12 @@
 from pathlib import Path
 
-from .cfg import TrainerConfig
-from .trainer import export_config_as_yaml, parse_args_netspresso, set_arguments, train_with_config, train_with_yaml
+from netspresso_trainer.cfg import TrainerConfig
+from netspresso_trainer.trainer_cli import parse_args_netspresso, set_arguments, train_cli
+from netspresso_trainer.trainer_inline import export_config_as_yaml, train_with_config, train_with_yaml
 
-train = train_with_config
+### Starting from v0.0.9, the default train function runs with yaml configuration
+train = train_with_yaml
+# train = train_with_config
 
 version = (Path(__file__).parent / "VERSION").read_text().strip()
 

src/netspresso_trainer/dataloaders/augmentation/custom.py

@@ -122,7 +122,7 @@ def __call__(self, image, mask=None, bbox=None):
             if mask is not None:
                 mask = F.hflip(mask)
             if bbox is not None:
-                bbox[..., 0:4:2] = w - bbox[..., 0:4:2]
+                bbox[..., 2::-2] = w - bbox[..., 0:4:2]
         return image, mask, bbox
 
     def __repr__(self):
@@ -142,7 +142,7 @@ def __call__(self, image, mask=None, bbox=None):
             if mask is not None:
                 mask = F.vflip(mask)
             if bbox is not None:
-                bbox[..., 1:4:2] = h - bbox[..., 1:4:2]
+                bbox[..., 3::-2] = h - bbox[..., 1:4:2]
         return image, mask, bbox
 
     def __repr__(self):

src/netspresso_trainer/losses/detection/__init__.py

@@ -1 +1,2 @@
-from .fastrcnn import RoiHeadLoss, RPNLoss
+from .fastrcnn import RoiHeadLoss, RPNLoss
+from .yolox import YOLOXLoss