adapt to BundleWorkflow interface

README.md

@@ -82,19 +82,14 @@ 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).
@@ -104,19 +99,13 @@ In addition, if using the 20 samples example dataset, the preprocessing script w
 #### 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
 ```
 The classification result of every images in `test.json` will be printed to the screen.
 

configs/evaluate.json

@@ -41,8 +41,10 @@
             "summary_ops": "*"
         }
     ],
-    "evaluating": [
-        "$setattr(torch.backends.cudnn, 'benchmark', True)",
+    "initialize": [
+        "$setattr(torch.backends.cudnn, 'benchmark', True)"
+    ],
+    "run": [
         "$@validate#evaluator.run()"
     ]
 }

configs/inference.json

@@ -4,7 +4,7 @@
         "$import os",
         "$import torch"
     ],
-    "bundle_root": "/workspace/bundle/endoscopic_inbody_classification",
+    "bundle_root": ".",
     "dataset_dir": "/workspace/data/endoscopic_inbody_classification",
     "test_json": "$@bundle_root+'/label/test_samples.json'",
     "test_fp": "$open(@test_json,'r', encoding='utf8')",
@@ -105,8 +105,10 @@
         "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": "0.3.6",
+    "version": "0.3.7",
     "changelog": {
+        "0.3.7": "adapt to BundleWorkflow interface",
         "0.3.6": "add name tag",
         "0.3.5": "fix a comment issue in the data_process script",
         "0.3.4": "add note for multi-gpu training with example dataset",
@@ -15,9 +16,9 @@
         "0.1.0": "complete the first version model package",
         "0.0.1": "initialize the model package structure"
     },
-    "monai_version": "1.0.1",
-    "pytorch_version": "1.13.0",
-    "numpy_version": "1.22.4",
+    "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"

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

@@ -4,7 +4,7 @@
         "$import json",
         "$import ignite"
     ],
-    "bundle_root": "/workspace/bundle/endoscopic_inbody_classification",
+    "bundle_root": ".",
     "ckpt_dir": "$@bundle_root + '/models'",
     "output_dir": "$@bundle_root + '/eval'",
     "dataset_dir": "/workspace/data/endoscopic_inbody_classification",
@@ -251,9 +251,11 @@
             "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

@@ -75,19 +75,14 @@ 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).
@@ -97,19 +92,13 @@ In addition, if using the 20 samples example dataset, the preprocessing script w
 #### 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
 ```
 The classification result of every images in `test.json` will be printed to the screen.