adapt to BundleWorkflow interface

README.md

@@ -92,13 +92,13 @@ 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).
@@ -106,7 +106,7 @@ Please note that the distributed training-related options depend on the actual r
 #### Execute inference
 
 ```
-CUDA_LAUNCH_BLOCKING=1 python -m monai.bundle run evaluating --meta_file configs/metadata.json --config_file configs/inference.json --logging_file configs/logging.conf
+CUDA_LAUNCH_BLOCKING=1 python -m monai.bundle run --config_file configs/inference.json
 ```
 
 #### Evaluate FROC metric

configs/inference.json

@@ -125,8 +125,10 @@
         "amp": true,
         "decollate": false
     },
-    "evaluating": [
-        "$setattr(torch.backends.cudnn, 'benchmark', True)",
+    "initialize": [
+        "$setattr(torch.backends.cudnn, 'benchmark', True)"
+    ],
+    "run": [
         "$@evaluator.run()"
     ]
 }

configs/metadata.json

@@ -1,7 +1,8 @@
 {
     "schema": "https://github.com/Project-MONAI/MONAI-extra-test-data/releases/download/0.8.1/meta_schema_20220324.json",
-    "version": "0.4.8",
+    "version": "0.4.9",
     "changelog": {
+        "0.4.9": "adapt to BundleWorkflow interface",
         "0.4.8": "update the readme file with TensorRT convert",
         "0.4.7": "add name tag",
         "0.4.6": "modify dataset key name",
@@ -20,12 +21,12 @@
         "0.1.0": "initialize release of the bundle"
     },
     "monai_version": "1.2.0rc3",
-    "pytorch_version": "1.13.0",
-    "numpy_version": "1.21.2",
+    "pytorch_version": "1.13.1",
+    "numpy_version": "1.22.2",
     "optional_packages_version": {
-        "cucim": "22.04",
+        "cucim": "22.8.1",
         "pandas": "1.3.5",
-        "torchvision": "0.14.0"
+        "torchvision": "0.14.1"
     },
     "name": "Pathology tumor detection",
     "task": "Pathology metastasis detection",

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

@@ -371,9 +371,11 @@
             "amp": true
         }
     },
-    "training": [
+    "initialize": [
         "$monai.utils.set_determinism(seed=15)",
-        "$setattr(torch.backends.cudnn, 'benchmark', True)",
+        "$setattr(torch.backends.cudnn, 'benchmark', True)"
+    ],
+    "run": [
         "$@train#trainer.run()"
     ]
 }

docs/README.md

@@ -85,13 +85,13 @@ 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).
@@ -99,7 +99,7 @@ Please note that the distributed training-related options depend on the actual r
 #### Execute inference
 
 ```
-CUDA_LAUNCH_BLOCKING=1 python -m monai.bundle run evaluating --meta_file configs/metadata.json --config_file configs/inference.json --logging_file configs/logging.conf
+CUDA_LAUNCH_BLOCKING=1 python -m monai.bundle run --config_file configs/inference.json
 ```
 
 #### Evaluate FROC metric

scripts/lesion_froc.py

@@ -17,7 +17,7 @@ def load_data(ground_truth_dir: str, eval_dir: str, level: int, spacing: float):
     for prob_name in prob_files:
         if prob_name.endswith(".npy"):
             sample = {
-                "tumor_mask": full_path(ground_truth_dir, prob_name[:-4]),
+                "tumor_mask": full_path(ground_truth_dir, prob_name.replace("npy", "tif")),
                 "prob_map": full_path(eval_dir, prob_name),
                 "level": level,
                 "pixel_spacing": spacing,