5648 track bundle config in MLFlow

monai/bundle/reference_resolver.py

@@ -221,21 +221,23 @@ def update_refs_pattern(cls, value: str, refs: Dict) -> str:
         result = cls.id_matcher.findall(value)
         value_is_expr = ConfigExpression.is_expression(value)
         for item in result:
-            ref_id = item[len(cls.ref) :]  # remove the ref prefix "@"
-            if ref_id not in refs:
-                msg = f"can not find expected ID '{ref_id}' in the references."
-                if cls.allow_missing_reference:
-                    warnings.warn(msg)
-                    continue
-                else:
-                    raise KeyError(msg)
-            if value_is_expr:
-                # replace with local code, `{"__local_refs": self.resolved_content}` will be added to
-                # the `globals` argument of python `eval` in the `evaluate`
-                value = value.replace(item, f"{cls._vars}['{ref_id}']")
-            elif value == item:
-                # the whole content is "@XXX", it will avoid the case that regular string contains "@"
-                value = refs[ref_id]
+            # only update reference when string starts with "$" or the whole content is "@XXX"
+            if value_is_expr or value == item:
+                ref_id = item[len(cls.ref) :]  # remove the ref prefix "@"
+                if ref_id not in refs:
+                    msg = f"can not find expected ID '{ref_id}' in the references."
+                    if cls.allow_missing_reference:
+                        warnings.warn(msg)
+                        continue
+                    else:
+                        raise KeyError(msg)
+                if value_is_expr:
+                    # replace with local code, `{"__local_refs": self.resolved_content}` will be added to
+                    # the `globals` argument of python `eval` in the `evaluate`
+                    value = value.replace(item, f"{cls._vars}['{ref_id}']")
+                elif value == item:
+                    # the whole content is "@XXX", it will avoid the case that regular string contains "@"
+                    value = refs[ref_id]
         return value
 
     @classmethod

monai/bundle/scripts.py

@@ -14,6 +14,7 @@
 import os
 import pprint
 import re
+import time
 import warnings
 from logging.config import fileConfig
 from pathlib import Path
@@ -489,6 +490,18 @@ def patch_bundle_tracking(parser: ConfigParser, settings: dict):
                     handlers.append(v)
         elif k not in parser:
             parser[k] = v
+    # save the executed config into file
+    default_name = f"config_{time.strftime('%Y%m%d_%H%M%S')}.json"
+    filepath = parser.get("execute_config", None)
+    if filepath is None:
+        if "output_dir" not in parser:
+            # if no "output_dir" in the bundle config, default to "<bundle root>/eval"
+            parser["output_dir"] = "$@bundle_root + '/eval'"
+        # experiment management tools can refer to this config item to track the config info
+        parser["execute_config"] = parser["output_dir"] + f" + '/{default_name}'"
+        filepath = os.path.join(parser.get_parsed_content("output_dir"), default_name)
+    Path(filepath).parent.mkdir(parents=True, exist_ok=True)
+    parser.export_config_file(parser.get(), filepath)
 
 
 def run(

monai/bundle/utils.py

@@ -104,9 +104,14 @@
 DEFAULT_MLFLOW_SETTINGS = {
     "handlers_id": DEFAULT_HANDLERS_ID,
     "configs": {
-        "tracking_uri": "$@output_dir + '/mlruns'",
+        # if no "output_dir" in the bundle config, default to "<bundle root>/eval"
+        "output_dir": "$@bundle_root + '/eval'",
+        # use URI to support linux, mac and windows os
+        "tracking_uri": "$monai.utils.path_to_uri(@output_dir) + '/mlruns'",
         "experiment_name": "monai_experiment",
         "run_name": None,
+        # may fill it at runtime
+        "execute_config": None,
         "is_not_rank0": (
             "$torch.distributed.is_available() \
                 and torch.distributed.is_initialized() and torch.distributed.get_rank() > 0"
@@ -118,6 +123,7 @@
             "tracking_uri": "@tracking_uri",
             "experiment_name": "@experiment_name",
             "run_name": "@run_name",
+            "artifacts": "@execute_config",
             "iteration_log": True,
             "epoch_log": True,
             "tag_name": "train_loss",
@@ -140,6 +146,7 @@
             "tracking_uri": "@tracking_uri",
             "experiment_name": "@experiment_name",
             "run_name": "@run_name",
+            "artifacts": "@execute_config",
             "iteration_log": False,
             "close_on_complete": True,
         },

monai/utils/__init__.py

@@ -73,6 +73,7 @@
     is_scalar_tensor,
     issequenceiterable,
     list_to_dict,
+    path_to_uri,
     progress_bar,
     sample_slices,
     save_obj,

monai/utils/misc.py

@@ -56,6 +56,7 @@
     "check_parent_dir",
     "save_obj",
     "label_union",
+    "path_to_uri",
 ]
 
 _seed = None
@@ -584,3 +585,14 @@ def prob2class(x, sigmoid: bool = False, threshold: float = 0.5, **kwargs):
         threshold: threshold value to activate the sigmoid function.
     """
     return torch.argmax(x, **kwargs) if not sigmoid else (x > threshold).int()
+
+
+def path_to_uri(path: PathLike) -> str:
+    """
+    Convert a file path to URI. if not absolute path, will convert to absolute path first.
+
+    Args:
+        path: input file path to convert, can be a string or `Path` object.
+
+    """
+    return Path(path).absolute().as_uri()

tests/test_fl_monai_algo.py

@@ -13,7 +13,6 @@
 import shutil
 import tempfile
 import unittest
-from pathlib import Path
 
 from parameterized import parameterized
 
@@ -22,6 +21,7 @@
 from monai.fl.client.monai_algo import MonaiAlgo
 from monai.fl.utils.constants import ExtraItems
 from monai.fl.utils.exchange_object import ExchangeObject
+from monai.utils import path_to_uri
 from tests.utils import SkipIfNoModule
 
 _root_dir = os.path.abspath(os.path.join(os.path.dirname(__file__)))
@@ -151,12 +151,13 @@ def test_train(self, input_params):
         input_params["tracking"] = {
             "handlers_id": DEFAULT_HANDLERS_ID,
             "configs": {
+                "execute_config": f"{data_dir}/config_executed.json",
                 "trainer": {
                     "_target_": "MLFlowHandler",
-                    "tracking_uri": Path(data_dir).as_uri() + "/mlflow_override",
+                    "tracking_uri": path_to_uri(data_dir) + "/mlflow_override",
                     "output_transform": "$monai.handlers.from_engine(['loss'], first=True)",
                     "close_on_complete": True,
-                }
+                },
             },
         }
 
@@ -177,6 +178,7 @@ def test_train(self, input_params):
         algo.train(data=data, extra={})
         algo.finalize()
         self.assertTrue(os.path.exists(f"{data_dir}/mlflow_override"))
+        self.assertTrue(os.path.exists(f"{data_dir}/config_executed.json"))
         shutil.rmtree(data_dir)
 
     @parameterized.expand([TEST_EVALUATE_1, TEST_EVALUATE_2, TEST_EVALUATE_3])

tests/test_handler_mlflow.py

@@ -13,12 +13,12 @@
 import os
 import tempfile
 import unittest
-from pathlib import Path
 
 import numpy as np
 from ignite.engine import Engine, Events
 
 from monai.handlers import MLFlowHandler
+from monai.utils import path_to_uri
 
 
 class TestHandlerMLFlow(unittest.TestCase):
@@ -49,7 +49,7 @@ def _update_metric(engine):
             handler = MLFlowHandler(
                 iteration_log=False,
                 epoch_log=True,
-                tracking_uri=Path(test_path).as_uri(),
+                tracking_uri=path_to_uri(test_path),
                 state_attributes=["test"],
                 experiment_param=experiment_param,
                 artifacts=[artifact_path],

tests/test_integration_bundle_run.py

@@ -15,7 +15,7 @@
 import sys
 import tempfile
 import unittest
-from pathlib import Path
+from glob import glob
 
 import nibabel as nib
 import numpy as np
@@ -24,6 +24,7 @@
 from monai.bundle import ConfigParser
 from monai.bundle.utils import DEFAULT_HANDLERS_ID
 from monai.transforms import LoadImage
+from monai.utils import path_to_uri
 from tests.utils import command_line_tests
 
 TEST_CASE_1 = [os.path.join(os.path.dirname(__file__), "testing_data", "inference.json"), (128, 128, 128)]
@@ -85,7 +86,7 @@ def test_shape(self, config_file, expected_shape):
                 "no_epoch": True,  # test override config in the settings file
                 "evaluator": {
                     "_target_": "MLFlowHandler",
-                    "tracking_uri": "$@output_dir + '/mlflow_override1'",
+                    "tracking_uri": "$monai.utils.path_to_uri(@output_dir) + '/mlflow_override1'",
                     "iteration_log": "@no_epoch",
                 },
             },
@@ -105,14 +106,12 @@ def test_shape(self, config_file, expected_shape):
             json.dump("Dataset", f)
 
         if sys.platform == "win32":
-            outdir = Path(tempdir).as_uri()
             override = "--network $@network_def.to(@device) --dataset#_target_ Dataset"
         else:
-            outdir = tempdir
             override = f"--network %{overridefile1}#move_net --dataset#_target_ %{overridefile2}"
         # test with `monai.bundle` as CLI entry directly
         cmd = "-m monai.bundle run evaluating --postprocessing#transforms#2#output_postfix seg"
-        cmd += f" {override} --no_epoch False --save_dir {tempdir} --output_dir {outdir}"
+        cmd += f" {override} --no_epoch False --output_dir {tempdir}"
         la = ["coverage", "run"] + cmd.split(" ") + ["--meta_file", meta_file] + ["--config_file", config_file]
         test_env = os.environ.copy()
         print(f"CUDA_VISIBLE_DEVICES in {__file__}", test_env.get("CUDA_VISIBLE_DEVICES"))
@@ -121,14 +120,16 @@ def test_shape(self, config_file, expected_shape):
         self.assertTupleEqual(loader(os.path.join(tempdir, "image", "image_seg.nii.gz")).shape, expected_shape)
         self.assertTrue(os.path.exists(f"{tempdir}/mlflow_override1"))
 
-        tracking_uri = outdir + "/mlflow_override2"  # test override experiment management configs
+        tracking_uri = path_to_uri(tempdir) + "/mlflow_override2"  # test override experiment management configs
         # here test the script with `google fire` tool as CLI
         cmd = "-m fire monai.bundle.scripts run --runner_id evaluating --tracking mlflow --evaluator#amp False"
-        cmd += f" --tracking_uri {tracking_uri} {override} --save_dir {tempdir} --output_dir {outdir}"
+        cmd += f" --tracking_uri {tracking_uri} {override} --output_dir {tempdir}"
         la = ["coverage", "run"] + cmd.split(" ") + ["--meta_file", meta_file] + ["--config_file", config_file]
         command_line_tests(la)
         self.assertTupleEqual(loader(os.path.join(tempdir, "image", "image_trans.nii.gz")).shape, expected_shape)
         self.assertTrue(os.path.exists(f"{tempdir}/mlflow_override2"))
+        # test the saved execution configs
+        self.assertTrue(len(glob(f"{tempdir}/config_*.json")), 2)
 
 
 if __name__ == "__main__":

tests/testing_data/inference.json

@@ -1,6 +1,5 @@
 {
     "dataset_dir": "/workspace/data/Task09_Spleen",
-    "save_dir": "need_override",
     "output_dir": "need override",
     "prediction_shape": "prediction shape:",
     "import_glob": "$import glob",
@@ -89,7 +88,7 @@
             {
                 "_target_": "SaveImaged",
                 "keys": "pred",
-                "output_dir": "@save_dir"
+                "output_dir": "@output_dir"
             },
             {
                 "_target_": "Lambdad",

tests/testing_data/inference.yaml

@@ -1,6 +1,5 @@
 ---
 dataset_dir: "/workspace/data/Task09_Spleen"
-save_dir: "need_override"
 output_dir: "need override"
 prediction_shape: "prediction shape:"
 device: "$torch.device('cuda:0' if torch.cuda.is_available() else 'cpu')"
@@ -65,7 +64,7 @@ postprocessing:
     argmax: true
   - _target_: SaveImaged
     keys: pred
-    output_dir: "@save_dir"
+    output_dir: "@output_dir"
   - _target_: Lambdad
     keys: pred
     func: "$lambda x: print(@prediction_shape + str(x.shape))"