adapt to BundleWorkflow interface and val metric

README.md

@@ -117,13 +117,13 @@ 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).
@@ -131,24 +131,24 @@ 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']"
 ```
 
 #### Override the `train` config and `evaluate` config to execute multi-GPU evaluation
 
 ```
-torchrun --standalone --nnodes=1 --nproc_per_node=2 -m monai.bundle run evaluating --meta_file configs/metadata.json --config_file "['configs/train.json','configs/evaluate.json','configs/multi_gpu_evaluate.json']" --logging_file configs/logging.conf
+torchrun --standalone --nnodes=1 --nproc_per_node=2 -m monai.bundle run --config_file "['configs/train.json','configs/evaluate.json','configs/multi_gpu_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
 ```
 #### Execute inference with Data Samples
 
 ```
-python -m monai.bundle run evaluating --meta_file configs/metadata.json --config_file configs/inference.json --logging_file configs/logging.conf --datalist "['sampledata/imagesTr/s0037.nii.gz','sampledata/imagesTr/s0038.nii.gz']"
+python -m monai.bundle run --config_file configs/inference.json --datalist "['sampledata/imagesTr/s0037.nii.gz','sampledata/imagesTr/s0038.nii.gz']"
 ```
 
 

configs/evaluate.json

@@ -8,31 +8,31 @@
                 "softmax": true
             },
             {
-                "_target_": "AsDiscreted",
+                "_target_": "Invertd",
                 "keys": [
                     "pred",
                     "label"
                 ],
-                "argmax": [
+                "transform": "@validate#preprocessing",
+                "orig_keys": "image",
+                "meta_key_postfix": "meta_dict",
+                "nearest_interp": [
                     true,
-                    false
+                    true
                 ],
-                "to_onehot": 105
+                "to_tensor": true
             },
             {
-                "_target_": "Invertd",
+                "_target_": "AsDiscreted",
                 "keys": [
                     "pred",
                     "label"
                 ],
-                "transform": "@validate#preprocessing",
-                "orig_keys": "image",
-                "meta_key_postfix": "meta_dict",
-                "nearest_interp": [
+                "argmax": [
                     true,
-                    true
+                    false
                 ],
-                "to_tensor": true
+                "to_onehot": 105
             },
             {
                 "_target_": "SaveImaged",
@@ -71,8 +71,10 @@
             "summary_ops": "*"
         }
     ],
-    "evaluating": [
-        "$setattr(torch.backends.cudnn, 'benchmark', True)",
+    "initialize": [
+        "$setattr(torch.backends.cudnn, 'benchmark', True)"
+    ],
+    "run": [
         "$@validate#evaluator.run()"
     ]
 }

configs/inference.json

@@ -152,8 +152,10 @@
         "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

@@ -1,13 +1,14 @@
 {
     "schema": "https://github.com/Project-MONAI/MONAI-extra-test-data/releases/download/0.8.1/meta_schema_20220324.json",
-    "version": "0.1.0",
+    "version": "0.1.1",
     "changelog": {
+        "0.1.1": "adapt to BundleWorkflow interface and val metric",
         "0.1.0": "complete the model package",
         "0.0.1": "initialize the model package structure"
     },
-    "monai_version": "1.1.0",
-    "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": "4.0.1",
         "pytorch-ignite": "0.4.9"
@@ -23,7 +24,7 @@
     "label_classes": "0 is the background, others are whole body segments",
     "pred_classes": "0 is the background, 104 other chanels are whole body segments",
     "eval_metrics": {
-        "mean_dice": 0.5
+        "mean_dice": 0.8
     },
     "intended_use": "This is an example, not to be used for diagnostic purposes",
     "references": [

configs/multi_gpu_evaluate.json

@@ -15,14 +15,18 @@
     },
     "validate#dataloader#sampler": "@validate#sampler",
     "validate#handlers#1#_disabled_": "$dist.get_rank() > 0",
-    "evaluating": [
+    "initialize": [
         "$import torch.distributed as dist",
-        "$dist.init_process_group(backend='nccl')",
+        "$dist.is_initialized() or dist.init_process_group(backend='nccl')",
         "$torch.cuda.set_device(@device)",
         "$setattr(torch.backends.cudnn, 'benchmark', True)",
         "$import logging",
-        "$@validate#evaluator.logger.setLevel(logging.WARNING if dist.get_rank() > 0 else logging.INFO)",
-        "$@validate#evaluator.run()",
+        "$@validate#evaluator.logger.setLevel(logging.WARNING if dist.get_rank() > 0 else logging.INFO)"
+    ],
+    "run": [
+        "$@validate#evaluator.run()"
+    ],
+    "finalize": [
         "$dist.destroy_process_group()"
     ]
 }

configs/multi_gpu_train.json

@@ -24,16 +24,20 @@
     },
     "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)",
         "$setattr(torch.backends.cudnn, 'benchmark', True)",
         "$import logging",
         "$@train#trainer.logger.setLevel(logging.WARNING if dist.get_rank() > 0 else logging.INFO)",
-        "$@validate#evaluator.logger.setLevel(logging.WARNING if dist.get_rank() > 0 else logging.INFO)",
-        "$@train#trainer.run()",
+        "$@validate#evaluator.logger.setLevel(logging.WARNING if dist.get_rank() > 0 else logging.INFO)"
+    ],
+    "run": [
+        "$@train#trainer.run()"
+    ],
+    "finalize": [
         "$dist.destroy_process_group()"
     ]
 }

configs/train.json

@@ -414,9 +414,11 @@
             "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

@@ -110,13 +110,13 @@ 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).
@@ -124,24 +124,24 @@ 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']"
 ```
 
 #### Override the `train` config and `evaluate` config to execute multi-GPU evaluation
 
 ```
-torchrun --standalone --nnodes=1 --nproc_per_node=2 -m monai.bundle run evaluating --meta_file configs/metadata.json --config_file "['configs/train.json','configs/evaluate.json','configs/multi_gpu_evaluate.json']" --logging_file configs/logging.conf
+torchrun --standalone --nnodes=1 --nproc_per_node=2 -m monai.bundle run --config_file "['configs/train.json','configs/evaluate.json','configs/multi_gpu_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
 ```
 #### Execute inference with Data Samples
 
 ```
-python -m monai.bundle run evaluating --meta_file configs/metadata.json --config_file configs/inference.json --logging_file configs/logging.conf --datalist "['sampledata/imagesTr/s0037.nii.gz','sampledata/imagesTr/s0038.nii.gz']"
+python -m monai.bundle run --config_file configs/inference.json --datalist "['sampledata/imagesTr/s0037.nii.gz','sampledata/imagesTr/s0038.nii.gz']"
 ```