adapt to BundleWorkflow interface

README.md

@@ -72,13 +72,13 @@ 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).
@@ -86,19 +86,19 @@ 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
 ```
 
 #### Export checkpoint to TorchScript file:

configs/evaluate.json

@@ -68,8 +68,10 @@
             "summary_ops": "*"
         }
     ],
-    "evaluating": [
-        "$setattr(torch.backends.cudnn, 'benchmark', True)",
+    "initialize": [
+        "$setattr(torch.backends.cudnn, 'benchmark', True)"
+    ],
+    "run": [
         "$@validate#evaluator.run()"
     ]
 }

configs/inference.json

@@ -3,7 +3,7 @@
         "$import glob",
         "$import os"
     ],
-    "bundle_root": "/workspace/bundle/endoscopic_tool_segmentation",
+    "bundle_root": ".",
     "output_dir": "$@bundle_root + '/eval'",
     "dataset_dir": "/workspace/data/endoscopic_tool_dataset",
     "datalist": "$list(sorted(glob.glob(os.path.join(@dataset_dir,'test', '*', '*[!seg].jpg'))))",
@@ -130,8 +130,10 @@
         "postprocessing": "@postprocessing",
         "val_handlers": "@handlers"
     },
-    "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": "0.4.3",
+    "version": "0.4.4",
     "changelog": {
+        "0.4.4": "adapt to BundleWorkflow interface",
         "0.4.3": "update this bundle to support TensorRT convert",
         "0.4.2": "support monai 1.2 new FlexibleUNet",
         "0.4.1": "add name tag",
@@ -15,8 +16,8 @@
         "0.0.1": "initialize the model package structure"
     },
     "monai_version": "1.2.0rc3",
-    "pytorch_version": "1.13.0",
-    "numpy_version": "1.22.4",
+    "pytorch_version": "1.13.1",
+    "numpy_version": "1.22.2",
     "optional_packages_version": {
         "nibabel": "4.0.1",
         "pytorch-ignite": "0.4.9"

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

@@ -25,16 +25,20 @@
     },
     "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

@@ -5,7 +5,7 @@
         "$import torch",
         "$import numpy as np"
     ],
-    "bundle_root": "/workspace/bundle/endoscopic_tool_segmentation",
+    "bundle_root": ".",
     "ckpt_dir": "$@bundle_root + '/models'",
     "output_dir": "$@bundle_root + '/eval'",
     "dataset_dir": "/workspace/data/endoscopic_tool_dataset",
@@ -274,9 +274,11 @@
             "val_handlers": "@validate#handlers"
         }
     },
-    "training": [
-        "$monai.utils.set_determinism(seed=0)",
-        "$setattr(torch.backends.cudnn, 'benchmark', True)",
+    "initialize": [
+        "$monai.utils.set_determinism(seed=123)",
+        "$setattr(torch.backends.cudnn, 'benchmark', True)"
+    ],
+    "run": [
         "$@train#trainer.run()"
     ]
 }

docs/README.md

@@ -65,13 +65,13 @@ 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).
@@ -79,19 +79,19 @@ 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
 ```
 
 #### Export checkpoint to TorchScript file: