1014-mlflow-handler-tutorial (#1019)

Fixes #1014 .

### Description
A tutorial about how to use mlflow handler in monai engine based
training process by adding one line in code.

### Checks
<!--- Put an `x` in all the boxes that apply, and remove the not
applicable items -->
- [ ] Notebook runs automatically `./runner [-p <regex_pattern>]`

Signed-off-by: binliu <[email protected]>
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>

Author: binliunls

README.md

@@ -150,6 +150,8 @@ This is example walks through using a Triton Server and Python client using MONA
 An example of experiment management with [Aim](https://aimstack.io/aim-monai-tutorial/), using 3D spleen segmentation as an example.
 ##### [MLFlow](./experiment_management/spleen_segmentation_mlflow.ipynb)
 An example of experiment management with [MLFlow](https://www.mlflow.org/docs/latest/tracking.html), using 3D spleen segmentation as an example.
+##### [MONAI bundle integrates MLFlow](./experiment_management/bundle_integrate_mlflow.ipynb)
+An example shows how to easily enable and customize the MLFlow for experiment management in MONAI bundle.
 
 #### <ins>**Federated Learning**</ins>
 ##### [NVFlare](./federated_learning/nvflare)

experiment_management/README.md

@@ -0,0 +1,7 @@
+# Overview
+This directory shows how to do experiment management in MONAI.
+
+## Files
+1. spleen_segmentation_aim.ipynb: an example about how to deploy aim experiment management in pytorch code.
+2. spleen_segmentation_mlflow.ipynb: an example about how to deploy mlflow experiment management in pytorch code.
+3. bundle_integrate_mlflow.ipynb: an example shows how to easily enable and customize the MLFlow for experiment management in MONAI bundle.

experiment_management/bundle_integrate_mlflow.ipynb

@@ -0,0 +1,26 @@
+{
+    "handlers_id": {
+        "trainer": {
+            "id": "train#trainer",
+            "handlers": "train#handlers"
+        }
+    },
+    "configs": {
+        "tracking_uri": "$@output_dir + '/mlruns'",
+        "experiment_name": "monai_experiment",
+        "run_name": "test1",
+        "is_not_rank0": "$torch.distributed.is_available() and torch.distributed.is_initialized() and torch.distributed.get_rank() > 0",
+        "trainer": {
+            "_target_": "MLFlowHandler",
+            "_disabled_": "@is_not_rank0",
+            "tracking_uri": "@tracking_uri",
+            "experiment_name": "@experiment_name",
+            "run_name": "@run_name",
+            "iteration_log": true,
+            "epoch_log": true,
+            "tag_name": "train_loss",
+            "output_transform": "$monai.handlers.from_engine(['loss'], first=True)",
+            "experiment_param": "${'backbone':'unet', 'norm':'Batch'}"
+        }
+    }
+}