update numbers

README.md

@@ -59,7 +59,7 @@ The training as performed with the following:
 - 13: Left adrenal gland
 
 ## Performance
-Dice score was used for evaluating the performance of the model. This model achieves a mean dice score of 0.8269
+Dice score was used for evaluating the performance of the model. This model achieves a mean dice score of 0.8120
 
 #### Training Loss
 ![The figure shows the training loss curve for 10K iterations.](https://developer.download.nvidia.com/assets/Clara/Images/monai_swin_unetr_btcv_segmentation_trainloss_v1.png)
@@ -76,13 +76,13 @@ For more details usage instructions, visit the [MONAI Bundle Configuration Page]
 #### Execute training:
 
 ```
-python -m monai.bundle run training --meta_file configs/metadata.json --config_file configs/train.json --logging_file configs/logging.conf
+python -m monai.bundle run --config_file configs/train.json
 ```
 
 #### Override the `train` config to execute multi-GPU training:
 
 ```
-torchrun --standalone --nnodes=1 --nproc_per_node=2 -m monai.bundle run training --meta_file configs/metadata.json --config_file "['configs/train.json','configs/multi_gpu_train.json']" --logging_file configs/logging.conf
+torchrun --standalone --nnodes=1 --nproc_per_node=2 -m monai.bundle run --config_file "['configs/train.json','configs/multi_gpu_train.json']"
 ```
 
 Please note that the distributed training-related options depend on the actual running environment; thus, users may need to remove `--standalone`, modify `--nnodes`, or do some other necessary changes according to the machine used. For more details, please refer to [pytorch's official tutorial](https://pytorch.org/tutorials/intermediate/ddp_tutorial.html).
@@ -90,13 +90,13 @@ Please note that the distributed training-related options depend on the actual r
 #### Override the `train` config to execute evaluation with the trained model:
 
 ```
-python -m monai.bundle run evaluating --meta_file configs/metadata.json --config_file "['configs/train.json','configs/evaluate.json']" --logging_file configs/logging.conf
+python -m monai.bundle run --config_file "['configs/train.json','configs/evaluate.json']"
 ```
 
 #### Execute inference:
 
 ```
-python -m monai.bundle run evaluating --meta_file configs/metadata.json --config_file configs/inference.json --logging_file configs/logging.conf
+python -m monai.bundle run --config_file configs/inference.json
 ```
 
 #### Export checkpoint to TorchScript file:

configs/evaluate.json

@@ -70,8 +70,10 @@
             "summary_ops": "*"
         }
     ],
-    "evaluating": [
-        "$setattr(torch.backends.cudnn, 'benchmark', True)",
+    "initialize": [
+        "$setattr(torch.backends.cudnn, 'benchmark', True)"
+    ],
+    "run": [
         "$@validate#evaluator.run()"
     ]
 }

configs/inference.json

@@ -3,9 +3,9 @@
         "$import glob",
         "$import os"
     ],
-    "bundle_root": "/workspace/MONAI_Bundle/swin_unetr_btcv_segmentation/",
+    "bundle_root": ".",
     "output_dir": "$@bundle_root + '/eval'",
-    "dataset_dir": "/dataset/dataset0",
+    "dataset_dir": "/workspace/data/RawData/",
     "datalist": "$list(sorted(glob.glob(@dataset_dir + '/imagesTs/*.nii.gz')))",
     "device": "$torch.device('cuda:0' if torch.cuda.is_available() else 'cpu')",
     "network_def": {
@@ -135,8 +135,10 @@
         "val_handlers": "@handlers",
         "amp": true
     },
-    "evaluating": [
-        "$setattr(torch.backends.cudnn, 'benchmark', True)",
+    "initialize": [
+        "$setattr(torch.backends.cudnn, 'benchmark', True)"
+    ],
+    "run": [
         "$@evaluator.run()"
     ]
 }

configs/metadata.json

@@ -1,7 +1,9 @@
 {
     "schema": "https://github.com/Project-MONAI/MONAI-extra-test-data/releases/download/0.8.1/meta_schema_20220324.json",
-    "version": "0.4.2",
+    "version": "0.4.4",
     "changelog": {
+        "0.4.4": "update numbers",
+        "0.4.3": "adapt to BundleWorkflow interface",
         "0.4.2": "fix train params of use_checkpoint",
         "0.4.1": "update params to supprot torch.jit.trace torchscript conversion",
         "0.4.0": "add name tag",
@@ -19,12 +21,12 @@
         "0.1.0": "complete the model package",
         "0.0.1": "initialize the model package structure"
     },
-    "monai_version": "1.0.1",
-    "pytorch_version": "1.13.0",
-    "numpy_version": "1.21.2",
+    "monai_version": "1.2.0rc3",
+    "pytorch_version": "1.13.1",
+    "numpy_version": "1.22.2",
     "optional_packages_version": {
-        "nibabel": "3.2.1",
-        "pytorch-ignite": "0.4.8",
+        "nibabel": "4.0.1",
+        "pytorch-ignite": "0.4.9",
         "einops": "0.4.1"
     },
     "name": "Swin UNETR BTCV segmentation",
@@ -38,7 +40,7 @@
     "label_classes": "multi-channel data,0:background,1:spleen, 2:Right Kidney, 3:Left Kideny, 4:Gallbladder, 5:Esophagus, 6:Liver, 7:Stomach, 8:Aorta, 9:IVC, 10:Portal and Splenic Veins, 11:Pancreas, 12:Right adrenal gland, 13:Left adrenal gland",
     "pred_classes": "14 channels OneHot data, 0:background,1:spleen, 2:Right Kidney, 3:Left Kideny, 4:Gallbladder, 5:Esophagus, 6:Liver, 7:Stomach, 8:Aorta, 9:IVC, 10:Portal and Splenic Veins, 11:Pancreas, 12:Right adrenal gland, 13:Left adrenal gland",
     "eval_metrics": {
-        "mean_dice": 0.8269
+        "mean_dice": 0.812
     },
     "intended_use": "This is an example, not to be used for diagnostic purposes",
     "references": [

configs/multi_gpu_train.json

@@ -24,13 +24,17 @@
     },
     "validate#dataloader#sampler": "@validate#sampler",
     "validate#evaluator#val_handlers": "$None if dist.get_rank() > 0 else @validate#handlers",
-    "training": [
+    "initialize": [
         "$import torch.distributed as dist",
-        "$dist.init_process_group(backend='nccl')",
+        "$dist.is_initialized() or dist.init_process_group(backend='nccl')",
         "$torch.cuda.set_device(@device)",
         "$monai.utils.set_determinism(seed=123)",
-        "$setattr(torch.backends.cudnn, 'benchmark', True)",
-        "$@train#trainer.run()",
+        "$setattr(torch.backends.cudnn, 'benchmark', True)"
+    ],
+    "run": [
+        "$@train#trainer.run()"
+    ],
+    "finalize": [
         "$dist.destroy_process_group()"
     ]
 }

configs/train.json

@@ -4,10 +4,10 @@
         "$import os",
         "$import ignite"
     ],
-    "bundle_root": "/workspace/MONAI_Bundle/swin_unetr_btcv_segmentation/",
+    "bundle_root": ".",
     "ckpt_dir": "$@bundle_root + '/models'",
     "output_dir": "$@bundle_root + '/eval'",
-    "dataset_dir": "/dataset/dataset0",
+    "dataset_dir": "/workspace/data/RawData/",
     "images": "$list(sorted(glob.glob(@dataset_dir + '/imagesTr/*.nii.gz')))",
     "labels": "$list(sorted(glob.glob(@dataset_dir + '/labelsTr/*.nii.gz')))",
     "val_interval": 5,
@@ -318,9 +318,11 @@
             "amp": true
         }
     },
-    "training": [
+    "initialize": [
         "$monai.utils.set_determinism(seed=123)",
-        "$setattr(torch.backends.cudnn, 'benchmark', True)",
+        "$setattr(torch.backends.cudnn, 'benchmark', True)"
+    ],
+    "run": [
         "$@train#trainer.run()"
     ]
 }

docs/README.md

@@ -52,7 +52,7 @@ The training as performed with the following:
 - 13: Left adrenal gland
 
 ## Performance
-Dice score was used for evaluating the performance of the model. This model achieves a mean dice score of 0.8269
+Dice score was used for evaluating the performance of the model. This model achieves a mean dice score of 0.8120
 
 #### Training Loss
 ![The figure shows the training loss curve for 10K iterations.](https://developer.download.nvidia.com/assets/Clara/Images/monai_swin_unetr_btcv_segmentation_trainloss_v1.png)
@@ -69,13 +69,13 @@ For more details usage instructions, visit the [MONAI Bundle Configuration Page]
 #### Execute training:
 
 ```
-python -m monai.bundle run training --meta_file configs/metadata.json --config_file configs/train.json --logging_file configs/logging.conf
+python -m monai.bundle run --config_file configs/train.json
 ```
 
 #### Override the `train` config to execute multi-GPU training:
 
 ```
-torchrun --standalone --nnodes=1 --nproc_per_node=2 -m monai.bundle run training --meta_file configs/metadata.json --config_file "['configs/train.json','configs/multi_gpu_train.json']" --logging_file configs/logging.conf
+torchrun --standalone --nnodes=1 --nproc_per_node=2 -m monai.bundle run --config_file "['configs/train.json','configs/multi_gpu_train.json']"
 ```
 
 Please note that the distributed training-related options depend on the actual running environment; thus, users may need to remove `--standalone`, modify `--nnodes`, or do some other necessary changes according to the machine used. For more details, please refer to [pytorch's official tutorial](https://pytorch.org/tutorials/intermediate/ddp_tutorial.html).
@@ -83,13 +83,13 @@ Please note that the distributed training-related options depend on the actual r
 #### Override the `train` config to execute evaluation with the trained model:
 
 ```
-python -m monai.bundle run evaluating --meta_file configs/metadata.json --config_file "['configs/train.json','configs/evaluate.json']" --logging_file configs/logging.conf
+python -m monai.bundle run --config_file "['configs/train.json','configs/evaluate.json']"
 ```
 
 #### Execute inference:
 
 ```
-python -m monai.bundle run evaluating --meta_file configs/metadata.json --config_file configs/inference.json --logging_file configs/logging.conf
+python -m monai.bundle run --config_file configs/inference.json
 ```
 
 #### Export checkpoint to TorchScript file: