WIP Dev stamp integration

application/jobs/ODELIA_ternary_classification/app/config/config_fed_client.conf

@@ -27,7 +27,7 @@
       tasks = ["swarm_*"]
       executor {
         # client-side controller for training and logic and aggregation management
-        path = "controller.SwarmClientController"
+        path = "nvflare.app_common.ccwf.SwarmClientController"
         args {
           # train task must be implemented by Executor
           learn_task_name = "train"

application/jobs/ODELIA_ternary_classification/app/config/config_fed_server.conf

@@ -13,13 +13,12 @@ workflows = [
   {
     # server-side controller to manage job life cycle
     id = "swarm_controller"
-    path = "controller.SwarmServerController"
+    path = "nvflare.app_common.ccwf.SwarmServerController"
     args {
       # can also set aggregation clients and train clients, see class for all available args
        num_rounds = 20
        start_task_timeout = 360000
        progress_timeout = 360000
-       end_workflow_timeout = 360000
        configure_task_timeout = 360000
        max_status_report_interval = 360000
     }

application/jobs/minimal_training_pytorch_cnn/app/config/config_fed_client.conf

@@ -27,7 +27,7 @@
       tasks = ["swarm_*"]
       executor {
         # client-side controller for training and logic and aggregation management
-        path = "controller.SwarmClientController"
+        path = "nvflare.app_common.ccwf.SwarmClientController"
         args {
           # train task must be implemented by Executor
           learn_task_name = "train"

application/jobs/minimal_training_pytorch_cnn/app/config/config_fed_server.conf

@@ -13,13 +13,13 @@ workflows = [
   {
     # server-side controller to manage job life cycle
     id = "swarm_controller"
-    path = "controller.SwarmServerController"
+    path = "nvflare.app_common.ccwf.SwarmServerController"
     args {
       # can also set aggregation clients and train clients, see class for all available args
        num_rounds = 5
        start_task_timeout = 36000
        progress_timeout = 36000
-       end_workflow_timeout = 36000
+       #end_workflow_timeout = 36000
        configure_task_timeout = 36000
        max_status_report_interval = 36000
     }

application/jobs/minimal_training_pytorch_cnn/app/custom/main.py

@@ -2,14 +2,14 @@
 
 import os
 
-import nvflare.client.lightning as flare
 import nvflare.client as flare_util
+import nvflare.client.lightning as flare
 import torch
 
 import minimal_training
 
 TRAINING_MODE = os.getenv("TRAINING_MODE")
-
+TRAINING_MODE = "swarm"
 if TRAINING_MODE == "swarm":
     flare_util.init()
     SITE_NAME=flare.get_site_name()
@@ -34,7 +34,17 @@ def main():
             logger.info(f"Site name: {SITE_NAME}")
 
             while flare.is_running():
+                logger.info('Waiting for input model from server...')
                 input_model = flare.receive()
+
+                if input_model is not None:
+                    logger.info("==== Swarm model received ====")
+                    logger.info(
+                        f"input_model.params.keys() = {list(input_model.params.keys())[:10]} ... total = {len(input_model.params)}")
+                    logger.info(
+                        f"model.state_dict().keys() = {list(model.state_dict().keys())[:10]} ... total = {len(model.state_dict())}")
+
+
                 logger.info(f"Current round: {input_model.current_round}")
 
                 minimal_training.validate_and_train(logger, data_module, model, trainer)

application/jobs/stamp/README.md

@@ -0,0 +1,97 @@
+# STAMP: A Protocol for Solid Tumor Associative Modeling in Pathology
+
+<img src="docs/STAMP_logo.svg" width="250px" align="right"></img>
+
+![CI](https://github.com/KatherLab/STAMP/actions/workflows/ci.yml/badge.svg)
+
+This repository contains the accompanying code for the steps described in the [Nature Protocols paper][stamp paper]:
+"From Whole Slide Image to Biomarker Prediction:
+A Protocol for End-to-End Deep Learning in Computational Pathology".
+
+> [!NOTE]
+> This repo contains an updated version of the codebase.
+> For a version compatible with the instructions in the paper,
+> please check out [version 1 of STAMP][stamp v1].
+
+[stamp paper]: https://www.nature.com/articles/s41596-024-01047-2 "From whole-slide image to biomarker prediction: end-to-end weakly supervised deep learning in computational pathology"
+
+[stamp v1]: https://github.com/KatherLab/STAMP/tree/v1
+
+## Installing stamp
+
+We recommend installing STAMP with [uv](https://docs.astral.sh/uv/):
+
+```bash
+git clone https://github.com/KatherLab/STAMP.git
+
+cd STAMP/
+
+uv sync --all-extras
+
+source .venv/bin/activate
+```
+
+> [!IMPORTANT]
+> STAMP additionally requires OpenSlide to be installed, as well as OpenCV dependencies.
+>
+> For Ubuntu < 23.10:
+> ```bash
+> apt update && apt install -y openslide-tools libgl1-mesa-glx  # libgl1-mesa-glx is needed for OpenCV
+> ```
+>
+> For Ubuntu >= 23.10:
+> ```bash
+> apt update && apt install -y openslide-tools libgl1 libglx-mesa0 libglib2.0-0  # libgl1, libglx-mesa0, libglib2.0-0 are needed for OpenCV
+> ```
+
+If the installation was successful, running `stamp` in your terminal should yield the following output:
+
+```
+$ stamp
+usage: stamp [-h] [--config CONFIG_FILE_PATH] {init,preprocess,encode_slides,encode_patients,train,crossval,deploy,statistics,config,heatmaps} ...
+
+STAMP: Solid Tumor Associative Modeling in Pathology
+
+positional arguments:
+  {init,preprocess,encode_slides,encode_patients,train,crossval,deploy,statistics,config,heatmaps}
+    init                Create a new STAMP configuration file at the path specified by --config
+    preprocess          Preprocess whole-slide images into feature vectors
+    encode_slides       Encode patch-level features into slide-level embeddings
+    encode_patients     Encode features into patient-level embeddings
+    train               Train a Vision Transformer model
+    crossval            Train a Vision Transformer model with cross validation for modeling.n_splits folds
+    deploy              Deploy a trained Vision Transformer model
+    statistics          Generate AUROCs and AUPRCs with 95%CI for a trained Vision Transformer model
+    config              Print the loaded configuration
+    heatmaps            Generate heatmaps for a trained model
+
+options:
+  -h, --help            show this help message and exit
+  --config CONFIG_FILE_PATH, -c CONFIG_FILE_PATH
+                        Path to config file. Default: config.yaml
+```
+
+## Running stamp
+
+For a quick introduction how to run stamp,
+check out our [getting started guide](getting-started.md).
+
+## Reference
+
+If you find our work useful in your research
+or if you use parts of this code
+please consider citing our [Nature Protocols publication](https://www.nature.com/articles/s41596-024-01047-2):
+
+```
+@Article{ElNahhas2024,
+  author={El Nahhas, Omar S. M. and van Treeck, Marko and W{\"o}lflein, Georg and Unger, Michaela and Ligero, Marta and Lenz, Tim and Wagner, Sophia J. and Hewitt, Katherine J. and Khader, Firas and Foersch, Sebastian and Truhn, Daniel and Kather, Jakob Nikolas},
+  title={From whole-slide image to biomarker prediction: end-to-end weakly supervised deep learning in computational pathology},
+  journal={Nature Protocols},
+  year={2024},
+  month={Sep},
+  day={16},
+  issn={1750-2799},
+  doi={10.1038/s41596-024-01047-2},
+  url={https://doi.org/10.1038/s41596-024-01047-2}
+}
+```

application/jobs/stamp/app/config/config_fed_client.conf

@@ -0,0 +1,147 @@
+{
+  format_version = 2
+  app_script = "main.py"
+  app_config = ""
+  executors = [
+    {
+      tasks = [
+        "train"
+      ]
+      executor {
+        path = "nvflare.app_opt.pt.client_api_launcher_executor.PTClientAPILauncherExecutor"
+        args {
+          launcher_id = "launcher"
+          pipe_id = "pipe"
+          last_result_transfer_timeout  = 360000
+          external_pre_init_timeout = 360000
+          peer_read_timeout = 360000
+          heartbeat_timeout = 360000
+          params_exchange_format = "pytorch"
+          params_transfer_type = "DIFF"
+          train_with_evaluation = true
+        }
+      }
+    }
+    {
+      # All tasks prefixed with swarm_ are routed to SwarmClientController
+      tasks = ["swarm_*"]
+      executor {
+        # client-side controller for training and logic and aggregation management
+        path = "nvflare.app_common.ccwf.SwarmClientController"
+        args {
+          # train task must be implemented by Executor
+          learn_task_name = "train"
+          # how long to wait for current learn task before timing out the gathering
+          #learn_task_timeout = 360000
+          #learn_task_abort_timeout = 360000
+          #learn_task_ack_timeout = 360000
+          #final_result_ack_timeout = 360000
+
+          # ids must map to corresponding components
+          persistor_id = "persistor"
+          aggregator_id = "aggregator"
+          shareable_generator_id = "shareable_generator"
+          min_responses_required = 2
+          #wait_time_after_min_resps_received = 360000
+        }
+      }
+    }
+  ]
+  task_data_filters = []
+  task_result_filters = []
+  components = [
+    {
+      id = "launcher"
+      path = "nvflare.app_common.launchers.subprocess_launcher.SubprocessLauncher"
+      args {
+        script = "python3 custom/{app_script}  {app_config} "
+        launch_once = true
+      }
+    }
+        {
+      id = "aggregator"
+      path = "nvflare.app_common.aggregators.intime_accumulate_model_aggregator.InTimeAccumulateWeightedAggregator"
+      args {
+        expected_data_kind = "WEIGHT_DIFF"
+      }
+    }
+    {
+      id = "pipe"
+      path = "nvflare.fuel.utils.pipe.cell_pipe.CellPipe"
+      args {
+        mode = "PASSIVE"
+        site_name = "{SITE_NAME}"
+        token = "{JOB_ID}"
+        root_url = "{ROOT_URL}"
+        secure_mode = "{SECURE_MODE}"
+        workspace_dir = "{WORKSPACE}"
+      }
+    }
+      {
+    id = "persistor"
+    path = "nvflare.app_opt.pt.file_model_persistor.PTFileModelPersistor"
+    args {
+      model {
+        path = "modeling.lightning_model.LitVisionTransformer"
+        args {
+        categories = ['WT', 'MUT']
+        dim_input = 1536
+        category_weights =[0.8676, 0.1324]
+            dim_model = 512
+            dim_feedforward=512
+            n_heads=8
+            n_layers=2
+            dropout=0.25
+use_alibi=False
+            ground_truth_label='isMSIH'
+            train_patients=['TCGA-AH-6644', 'TCGA-AA-3664', 'TCGA-AZ-4614', 'TCGA-D5-5537', 'TCGA-G4-6628', 'TCGA-EI-6882', 'TCGA-AF-2689', 'TCGA-F4-6805', 'TCGA-AZ-4681', 'TCGA-AG-3882', 'TCGA-A6-6648', 'TCGA-AA-A017', 'TCGA-G4-6303', 'TCGA-EI-6508', 'TCGA-AF-6136', 'TCGA-A6-6654', 'TCGA-AD-6895', 'TCGA-CM-5860', 'TCGA-A6-4105', 'TCGA-F5-6810', 'TCGA-QG-A5YV', 'TCGA-DC-6155', 'TCGA-F5-6812', 'TCGA-QL-A97D', 'TCGA-AZ-4615', 'TCGA-CK-6751', 'TCGA-AH-6547', 'TCGA-AA-3980', 'TCGA-CL-5918', 'TCGA-DM-A282', 'TCGA-AA-3514', 'TCGA-EI-6509', 'TCGA-AF-3911', 'TCGA-CL-5917', 'TCGA-A6-2686', 'TCGA-AA-3950', 'TCGA-AA-3549', 'TCGA-AA-3973', 'TCGA-D5-6922', 'TCGA-AG-3887', 'TCGA-CA-6717', 'TCGA-CM-6171', 'TCGA-AD-6964', 'TCGA-A6-6142', 'TCGA-AD-6890', 'TCGA-A6-6138', 'TCGA-AD-A5EK', 'TCGA-D5-6929', 'TCGA-G4-6588', 'TCGA-AZ-4616', 'TCGA-AA-3561', 'TCGA-QG-A5Z2', 'TCGA-DM-A1HA', 'TCGA-CL-4957', 'TCGA-CA-5255', 'TCGA-DC-6158', 'TCGA-G4-6295', 'TCGA-AY-A69D', 'TCGA-DM-A1D6', 'TCGA-AG-3896', 'TCGA-A6-6652', 'TCGA-CM-6680', 'TCGA-AA-3821', 'TCGA-D5-5540', 'TCGA-DC-5869', 'TCGA-AG-4008', 'TCGA-CK-4952', 'TCGA-AA-3875', 'TCGA-AA-A02W', 'TCGA-EI-6514', 'TCGA-DM-A288', 'TCGA-AG-3890', 'TCGA-AA-3979', 'TCGA-NH-A5IV', 'TCGA-G4-6297', 'TCGA-D5-6927', 'TCGA-AA-3680', 'TCGA-NH-A8F8', 'TCGA-A6-5662', 'TCGA-A6-2674', 'TCGA-AG-A01N', 'TCGA-DM-A1D8', 'TCGA-AA-3837', 'TCGA-AA-A01I', 'TCGA-DM-A0XF', 'TCGA-F4-6855', 'TCGA-CA-6715', 'TCGA-AA-3975', 'TCGA-AA-3989', 'TCGA-AG-A016', 'TCGA-A6-5666', 'TCGA-CK-6746', 'TCGA-CM-4752', 'TCGA-CM-6676', 'TCGA-D5-6541', 'TCGA-A6-5667', 'TCGA-AF-2691', 'TCGA-AD-A5EJ', 'TCGA-F5-6864', 'TCGA-AG-3726', 'TCGA-A6-6649', 'TCGA-AA-A03J', 'TCGA-AF-2687', 'TCGA-AA-3858', 'TCGA-G4-6321', 'TCGA-G5-6641', 'TCGA-G4-6309', 'TCGA-D5-5538', 'TCGA-DM-A28K', 'TCGA-AG-3878', 'TCGA-AZ-6598', 'TCGA-AA-3688', 'TCGA-AG-A01W', 'TCGA-AA-3517', 'TCGA-D5-6898', 'TCGA-CM-5341', 'TCGA-CM-6167', 'TCGA-D5-6531', 'TCGA-DC-6683', 'TCGA-AF-2690', 'TCGA-CM-6161', 'TCGA-A6-5660', 'TCGA-NH-A8F7', 'TCGA-CM-6163', 'TCGA-AA-3968', 'TCGA-CM-5868', 'TCGA-AA-3976', 'TCGA-A6-A565', 'TCGA-AM-5821', 'TCGA-AD-6965', 'TCGA-AY-A71X', 'TCGA-AZ-4682', 'TCGA-AG-3892', 'TCGA-A6-2675', 'TCGA-F4-6569', 'TCGA-AG-3893', 'TCGA-CM-5862', 'TCGA-AZ-6606', 'TCGA-CM-6678', 'TCGA-D5-6931', 'TCGA-D5-6923', 'TCGA-AG-3575', 'TCGA-AA-A00Z', 'TCGA-D5-6540', 'TCGA-A6-3808', 'TCGA-CM-4743', 'TCGA-DC-4749', 'TCGA-T9-A92H', 'TCGA-A6-3810', 'TCGA-AD-6889', 'TCGA-G4-6320', 'TCGA-AA-3971', 'TCGA-AZ-4308', 'TCGA-D5-7000', 'TCGA-DM-A28A', 'TCGA-AG-A01L', 'TCGA-EI-6512', 'TCGA-A6-5661', 'TCGA-AG-3599', 'TCGA-AG-3902', 'TCGA-AD-6548', 'TCGA-AA-A022', 'TCGA-AG-3580', 'TCGA-A6-A567', 'TCGA-AA-3679', 'TCGA-CA-5256', 'TCGA-F4-6808', 'TCGA-D5-6536', 'TCGA-DM-A1D9', 'TCGA-AG-3885', 'TCGA-DM-A1D0', 'TCGA-CM-6674', 'TCGA-EI-6507', 'TCGA-F4-6459', 'TCGA-A6-6137', 'TCGA-AD-6899', 'TCGA-EI-6885', 'TCGA-WS-AB45', 'TCGA-D5-6930', 'TCGA-AU-6004', 'TCGA-AY-6196', 'TCGA-AA-A010', 'TCGA-AG-A00C', 'TCGA-4T-AA8H', 'TCGA-G4-6302', 'TCGA-AA-3966', 'TCGA-AF-2693', 'TCGA-D5-6926', 'TCGA-DM-A0XD', 'TCGA-AA-3854', 'TCGA-D5-6932', 'TCGA-EI-7004', 'TCGA-AG-3594', 'TCGA-EI-6510', 'TCGA-AA-3715', 'TCGA-AA-A01X', 'TCGA-F4-6570', 'TCGA-EI-6511', 'TCGA-CM-5861', 'TCGA-CA-5254', 'TCGA-G4-6317', 'TCGA-DM-A28M', 'TCGA-EI-6506', 'TCGA-AG-A020', 'TCGA-AG-3583', 'TCGA-G4-6294', 'TCGA-CM-6165', 'TCGA-D5-6535', 'TCGA-D5-5541', 'TCGA-DM-A1DB', 'TCGA-AG-A01J', 'TCGA-AG-4001', 'TCGA-AG-A00Y', 'TCGA-AA-3949', 'TCGA-AA-3842', 'TCGA-CA-6716', 'TCGA-CM-5348', 'TCGA-AA-3696', 'TCGA-AA-3833', 'TCGA-NH-A6GC', 'TCGA-CK-4947', 'TCGA-AA-3846', 'TCGA-A6-2677', 'TCGA-A6-2684', 'TCGA-NH-A6GA', 'TCGA-F5-6811', 'TCGA-A6-4107', 'TCGA-F5-6571', 'TCGA-CK-6747', 'TCGA-AA-3666', 'TCGA-CK-5914', 'TCGA-G4-6627', 'TCGA-DC-6681', 'TCGA-AZ-4315', 'TCGA-DT-5265', 'TCGA-CM-4751', 'TCGA-CM-6168', 'TCGA-AY-5543', 'TCGA-AZ-6607', 'TCGA-AG-3901', 'TCGA-AA-3695', 'TCGA-AD-6963', 'TCGA-CK-5913', 'TCGA-AF-2692', 'TCGA-G4-6307', 'TCGA-AA-A01T', 'TCGA-DY-A1DG', 'TCGA-AA-A01C', 'TCGA-AZ-6603', 'TCGA-AG-3727', 'TCGA-AG-3909', 'TCGA-D5-6539', 'TCGA-AZ-5407', 'TCGA-NH-A6GB', 'TCGA-AA-3851', 'TCGA-AF-5654', 'TCGA-AA-3530', 'TCGA-F5-6813', 'TCGA-AA-3845', 'TCGA-AG-3584', 'TCGA-AM-5820', 'TCGA-AA-3982', 'TCGA-D5-6924', 'TCGA-AA-3984', 'TCGA-5M-AATE', 'TCGA-AG-3894', 'TCGA-AU-3779', 'TCGA-A6-2671', 'TCGA-DC-6682', 'TCGA-A6-6653', 'TCGA-DM-A28E', 'TCGA-AZ-5403', 'TCGA-CK-4948', 'TCGA-AF-6655', 'TCGA-AA-A01P', 'TCGA-AA-A024', 'TCGA-F4-6809', 'TCGA-AA-3548', 'TCGA-QG-A5YW', 'TCGA-AA-3818', 'TCGA-EI-6513', 'TCGA-AY-4071', 'TCGA-D5-6532', 'TCGA-AZ-6600', 'TCGA-CM-6172', 'TCGA-AG-A01Y', 'TCGA-AA-3675', 'TCGA-AD-6888', 'TCGA-AH-6897', 'TCGA-AA-3852', 'TCGA-CM-4747', 'TCGA-AG-A02N', 'TCGA-AA-A02F', 'TCGA-DM-A1D7', 'TCGA-AA-3678', 'TCGA-CM-6677', 'TCGA-AA-A004', 'TCGA-D5-5539', 'TCGA-F5-6861', 'TCGA-AA-3544', 'TCGA-F4-6463', 'TCGA-AG-4015', 'TCGA-AF-3400', 'TCGA-CM-6169', 'TCGA-F4-6461', 'TCGA-AD-6901', 'TCGA-DM-A280', 'TCGA-AA-3819', 'TCGA-DM-A0X9', 'TCGA-G4-6315', 'TCGA-AA-3850', 'TCGA-CA-5797', 'TCGA-AA-3856', 'TCGA-AY-6386', 'TCGA-AG-3598', 'TCGA-CM-5863', 'TCGA-AG-3605', 'TCGA-AZ-6599', 'TCGA-CM-5344', 'TCGA-AA-3693', 'TCGA-G4-6306', 'TCGA-F4-6854', 'TCGA-A6-5656', 'TCGA-DY-A0XA', 'TCGA-A6-2685', 'TCGA-AY-6197', 'TCGA-4N-A93T', 'TCGA-NH-A50U', 'TCGA-A6-2683', 'TCGA-AA-3952', 'TCGA-DC-6160', 'TCGA-A6-3807', 'TCGA-AA-3522', 'TCGA-G4-6304', 'TCGA-AA-3526', 'TCGA-DC-4745', 'TCGA-AA-3877', 'TCGA-CM-6162', 'TCGA-AA-3692', 'TCGA-AA-3524', 'TCGA-AG-3881', 'TCGA-AA-3681', 'TCGA-CK-4951', 'TCGA-AA-3534', 'TCGA-A6-A56B', 'TCGA-DM-A1D4', 'TCGA-5M-AAT5', 'TCGA-AG-4022', 'TCGA-AA-3812', 'TCGA-D5-6529', 'TCGA-AA-3673', 'TCGA-EI-6917', 'TCGA-EI-6884', 'TCGA-AG-A011', 'TCGA-AY-A8YK', 'TCGA-EI-6881', 'TCGA-A6-2678', 'TCGA-AA-3947', 'TCGA-A6-5659', 'TCGA-AA-3994', 'TCGA-D5-6534', 'TCGA-AG-3574', 'TCGA-F5-6465', 'TCGA-CA-6719', 'TCGA-AA-3532', 'TCGA-G4-6322', 'TCGA-AF-A56K', 'TCGA-AA-3864', 'TCGA-AA-3685', 'TCGA-AA-3986']
+            valid_patients=['TCGA-AG-4021', 'TCGA-AG-A02X', 'TCGA-AA-A02H', 'TCGA-F4-6807', 'TCGA-G4-6311', 'TCGA-AF-A56L', 'TCGA-CM-4748', 'TCGA-AZ-6605', 'TCGA-G4-6299', 'TCGA-AA-3667', 'TCGA-5M-AAT4', 'TCGA-5M-AAT6', 'TCGA-F4-6704', 'TCGA-AH-6544', 'TCGA-3L-AA1B', 'TCGA-CK-4950', 'TCGA-AA-3956', 'TCGA-G4-6323', 'TCGA-AA-3831', 'TCGA-AH-6903', 'TCGA-CA-5796', 'TCGA-AA-3684', 'TCGA-EI-7002', 'TCGA-F4-6460', 'TCGA-AA-3844', 'TCGA-AA-3848', 'TCGA-D5-6928', 'TCGA-A6-5665', 'TCGA-AA-A01S', 'TCGA-DM-A28H', 'TCGA-DC-6157', 'TCGA-DY-A1DD', 'TCGA-AA-3519', 'TCGA-AA-3855', 'TCGA-F4-6806', 'TCGA-AA-3520', 'TCGA-CM-6675', 'TCGA-AG-3898', 'TCGA-CK-6748', 'TCGA-G4-6298', 'TCGA-G4-6626', 'TCGA-QG-A5Z1', 'TCGA-DM-A28G', 'TCGA-A6-2681', 'TCGA-DM-A28F', 'TCGA-G4-6586', 'TCGA-CK-5916', 'TCGA-AG-A002', 'TCGA-AG-A026', 'TCGA-AA-A02E', 'TCGA-F5-6464', 'TCGA-EI-6883', 'TCGA-F4-6856', 'TCGA-AG-A015', 'TCGA-CM-5349', 'TCGA-DM-A1DA', 'TCGA-D5-6530', 'TCGA-A6-A566', 'TCGA-NH-A50V', 'TCGA-F5-6814', 'TCGA-CM-6166', 'TCGA-CI-6622', 'TCGA-AA-3977', 'TCGA-CA-6718', 'TCGA-AA-3841', 'TCGA-AA-3521', 'TCGA-NH-A50T', 'TCGA-AA-A01R', 'TCGA-AG-A008', 'TCGA-CM-4746', 'TCGA-AA-A02R', 'TCGA-DC-6154', 'TCGA-AA-3531', 'TCGA-F5-6863', 'TCGA-F4-6703', 'TCGA-AY-A54L', 'TCGA-AA-3811', 'TCGA-AA-3814', 'TCGA-CK-5912', 'TCGA-A6-3809', 'TCGA-A6-5657', 'TCGA-EF-5830', 'TCGA-CM-6164', 'TCGA-SS-A7HO', 'TCGA-CM-5864', 'TCGA-AF-4110', 'TCGA-AF-6672', 'TCGA-AA-3866', 'TCGA-AA-A01V', 'TCGA-AA-A00N', 'TCGA-D5-6538', 'TCGA-CM-6170', 'TCGA-D5-6537', 'TCGA-AA-A02Y', 'TCGA-DY-A1DC', 'TCGA-AG-3883', 'TCGA-AD-5900', 'TCGA-AA-3955', 'TCGA-AG-3581', 'TCGA-A6-5664', 'TCGA-DY-A1DF', 'TCGA-AA-A02O', 'TCGA-AA-3527', 'TCGA-F5-6702', 'TCGA-AH-6643', 'TCGA-G4-6293', 'TCGA-DC-5337', 'TCGA-AA-A03F', 'TCGA-CI-6624', 'TCGA-AG-3602', 'TCGA-AA-3538', 'TCGA-AA-A01Z', 'TCGA-AA-3558', 'TCGA-AA-3560', 'TCGA-AA-3867', 'TCGA-A6-6650', 'TCGA-CK-5915', 'TCGA-A6-6651', 'TCGA-AY-4070', 'TCGA-AF-A56N', 'TCGA-D5-6533', 'TCGA-AA-3529', 'TCGA-AG-A032', 'TCGA-QG-A5YX']
+
+       }
+      }
+    }
+  }
+    {
+    id = "shareable_generator"
+    path = "nvflare.app_common.ccwf.comps.simple_model_shareable_generator.SimpleModelShareableGenerator"
+    args {}
+  }
+    {
+      id = "metrics_pipe"
+      path = "nvflare.fuel.utils.pipe.cell_pipe.CellPipe"
+      args {
+        mode = "PASSIVE"
+        site_name = "{SITE_NAME}"
+        token = "{JOB_ID}"
+        root_url = "{ROOT_URL}"
+        secure_mode = "{SECURE_MODE}"
+        workspace_dir = "{WORKSPACE}"
+      }
+    }
+    {
+      id = "metric_relay"
+      path = "nvflare.app_common.widgets.metric_relay.MetricRelay"
+      args {
+        pipe_id = "metrics_pipe"
+        event_type = "fed.analytix_log_stats"
+        read_interval = 0.1
+      }
+    }
+    {
+      id = "model_selector"
+      path = "nvflare.app_common.widgets.intime_model_selector.IntimeModelSelector"
+      args {
+        key_metric = "accuracy"
+      }
+    }
+    {
+      id = "config_preparer"
+      path = "nvflare.app_common.widgets.external_configurator.ExternalConfigurator"
+      args {
+        component_ids = [
+          "metric_relay"
+        ]
+      }
+    }
+  ]
+}

application/jobs/stamp/app/config/config_fed_server.conf

@@ -0,0 +1,26 @@
+format_version = 2
+task_data_filters = []
+task_result_filters = []
+components = [
+  {
+    # write validation results to json file
+    id = "json_generator"
+    path = "nvflare.app_common.widgets.validation_json_generator.ValidationJsonGenerator"
+    args {}
+  }
+]
+workflows = [
+  {
+    # server-side controller to manage job life cycle
+    id = "swarm_controller"
+    path = "nvflare.app_common.ccwf.SwarmServerController"
+    args {
+      # can also set aggregation clients and train clients, see class for all available args
+       num_rounds = 20
+       #start_task_timeout = 360000
+       #progress_timeout = 360000
+       #configure_task_timeout = 360000
+       #max_status_report_interval = 360000
+    }
+  }
+]