Add Secaggplus example

examples/secaggplus-mt/README.md

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+# Secure Aggregation with Driver API
+
+This example contains highly experimental code. Please consult the regular PyTorch code examples ([quickstart](https://github.com/adap/flower/tree/main/examples/quickstart_pytorch), [advanced](https://github.com/adap/flower/tree/main/examples/advanced_pytorch)) to learn how to use Flower with PyTorch.
+
+## Installing Dependencies
+
+Project dependencies (such as and `flwr`) are defined in `pyproject.toml`. We recommend [Poetry](https://python-poetry.org/docs/) to install those dependencies and manage your virtual environment ([Poetry installation](https://python-poetry.org/docs/#installation)), but feel free to use a different way of installing dependencies and managing virtual environments if you have other preferences.
+
+### Poetry
+
+```shell
+poetry install
+poetry shell
+```
+
+Poetry will install all your dependencies in a newly created virtual environment. To verify that everything works correctly you can run the following command:
+
+```shell
+poetry run python3 -c "import flwr"
+```
+
+If you don't see any errors you're good to go!
+
+## Run with Driver API
+
+```bash
+./run.sh
+```

examples/secaggplus-mt/client.py

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+import time
+
+import numpy as np
+
+import flwr as fl
+from flwr.common import Status, FitIns, FitRes, Code
+from flwr.common.parameter import ndarrays_to_parameters
+from flwr.client.secure_aggregation import SecAggPlusHandler
+
+
+# Define Flower client with the SecAgg+ protocol
+class FlowerClient(fl.client.Client, SecAggPlusHandler):
+    def fit(self, fit_ins: FitIns) -> FitRes:
+        ret_vec = [np.ones(3)]
+        ret = FitRes(
+            status=Status(code=Code.OK, message="Success"),
+            parameters=ndarrays_to_parameters(ret_vec),
+            num_examples=1,
+            metrics={},
+        )
+        # Force a significant delay for teshing purposes
+        if self._shared_state.sid == 0:
+            print(f"Client {self._shared_state.sid} dropped for testing purposes.")
+            time.sleep(4)
+            return ret
+        print(f"Client {self._shared_state.sid} uploading {ret_vec[0]}...")
+        return ret
+
+
+# Start Flower client
+fl.client.start_client(
+    server_address="0.0.0.0:9092",
+    client=FlowerClient(),
+    transport="grpc-rere",
+)

examples/secaggplus-mt/driver.py

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+import random
+import time
+from typing import Dict, List, Tuple
+
+import numpy as np
+from workflows import get_workflow_factory
+
+from flwr.common import Metrics, ndarrays_to_parameters
+from flwr.driver import Driver
+from flwr.proto import driver_pb2, node_pb2, task_pb2
+from flwr.server import History
+
+
+# Convert instruction/result dict to/from list of TaskIns/TaskRes
+def task_dict_to_task_ins_list(
+    task_dict: Dict[int, task_pb2.Task]
+) -> List[task_pb2.TaskIns]:
+    def merge(_task: task_pb2.Task, _merge_task: task_pb2.Task) -> task_pb2.Task:
+        _task.MergeFrom(_merge_task)
+        return _task
+
+    return [
+        task_pb2.TaskIns(
+            task_id="",  # Do not set, will be created and set by the DriverAPI
+            group_id="",
+            workload_id="",
+            task=merge(
+                task,
+                task_pb2.Task(
+                    producer=node_pb2.Node(
+                        node_id=0,
+                        anonymous=True,
+                    ),
+                    consumer=node_pb2.Node(
+                        node_id=sampled_node_id,
+                        # Must be False for this Secure Aggregation example
+                        anonymous=False,
+                    ),
+                ),
+            ),
+        )
+        for sampled_node_id, task in task_dict.items()
+    ]
+
+
+def task_res_list_to_task_dict(
+    task_res_list: List[task_pb2.TaskRes],
+) -> Dict[int, task_pb2.Task]:
+    return {task_res.task.producer.node_id: task_res.task for task_res in task_res_list}
+
+
+# Define metric aggregation function
+def weighted_average(metrics: List[Tuple[int, Metrics]]) -> Metrics:
+    examples = [num_examples for num_examples, _ in metrics]
+
+    # Multiply accuracy of each client by number of examples used
+    train_losses = [num_examples * m["train_loss"] for num_examples, m in metrics]
+    train_accuracies = [
+        num_examples * m["train_accuracy"] for num_examples, m in metrics
+    ]
+    val_losses = [num_examples * m["val_loss"] for num_examples, m in metrics]
+    val_accuracies = [num_examples * m["val_accuracy"] for num_examples, m in metrics]
+
+    # Aggregate and return custom metric (weighted average)
+    return {
+        "train_loss": sum(train_losses) / sum(examples),
+        "train_accuracy": sum(train_accuracies) / sum(examples),
+        "val_loss": sum(val_losses) / sum(examples),
+        "val_accuracy": sum(val_accuracies) / sum(examples),
+    }
+
+
+# -------------------------------------------------------------------------- Driver SDK
+driver = Driver(driver_service_address="0.0.0.0:9091", certificates=None)
+# -------------------------------------------------------------------------- Driver SDK
+
+anonymous_client_nodes = False
+num_client_nodes_per_round = 5
+sleep_time = 0.5
+time_out = 3.9
+num_rounds = 3
+parameters = ndarrays_to_parameters([np.ones(3)])
+wf_factory = get_workflow_factory()
+
+# -------------------------------------------------------------------------- Driver SDK
+driver.connect()
+# -------------------------------------------------------------------------- Driver SDK
+
+history = History()
+for server_round in range(num_rounds):
+    print(f"Commencing server round {server_round + 1}")
+
+    # List of sampled node IDs in this round
+    sampled_node_ids: List[int] = []
+
+    # Sample node ids
+    if anonymous_client_nodes:
+        # If we're working with anonymous clients, we don't know their identities, and
+        # we don't know how many of them we have. We, therefore, have to assume that
+        # enough anonymous client nodes are available or become available over time.
+        #
+        # To schedule a TaskIns for an anonymous client node, we set the node_id to 0
+        # (and `anonymous` to True)
+        # Here, we create an array with only zeros in it:
+        sampled_node_ids = [0] * num_client_nodes_per_round
+    else:
+        # If our client nodes have identiy (i.e., they are not anonymous), we can get
+        # those IDs from the Driver API using `get_nodes`. If enough clients are
+        # available via the Driver API, we can select a subset by taking a random
+        # sample.
+        #
+        # The Driver API might not immediately return enough client node IDs, so we
+        # loop and wait until enough client nodes are available.
+        while True:
+            # Get a list of node ID's from the server
+            get_nodes_req = driver_pb2.GetNodesRequest()
+
+            # ---------------------------------------------------------------------- Driver SDK
+            get_nodes_res: driver_pb2.GetNodesResponse = driver.get_nodes(
+                req=get_nodes_req
+            )
+            # ---------------------------------------------------------------------- Driver SDK
+
+            all_node_ids: List[int] = get_nodes_res.node_ids
+
+            if len(all_node_ids) >= num_client_nodes_per_round:
+                # Sample client nodes
+                sampled_node_ids = random.sample(
+                    all_node_ids, num_client_nodes_per_round
+                )
+                break
+
+            time.sleep(3)
+
+    # Log sampled node IDs
+    time.sleep(sleep_time)
+
+    workflow = wf_factory(parameters, sampled_node_ids)
+    node_messages = None
+
+    while True:
+        try:
+            instructions: Dict[int, task_pb2.Task] = workflow.send(node_messages)
+            next(workflow)
+        except StopIteration:
+            break
+        # Schedule a task for all sampled nodes
+        task_ins_list: List[task_pb2.TaskIns] = task_dict_to_task_ins_list(instructions)
+
+        push_task_ins_req = driver_pb2.PushTaskInsRequest(task_ins_list=task_ins_list)
+
+        # ---------------------------------------------------------------------- Driver SDK
+        push_task_ins_res: driver_pb2.PushTaskInsResponse = driver.push_task_ins(
+            req=push_task_ins_req
+        )
+        # ---------------------------------------------------------------------- Driver SDK
+
+        time.sleep(sleep_time)
+
+        # Wait for results, ignore empty task_ids
+        start_time = time.time()
+        task_ids: List[str] = [
+            task_id for task_id in push_task_ins_res.task_ids if task_id != ""
+        ]
+        all_task_res: List[task_pb2.TaskRes] = []
+        while True:
+            if time.time() - start_time >= time_out:
+                break
+            pull_task_res_req = driver_pb2.PullTaskResRequest(
+                node=node_pb2.Node(node_id=0, anonymous=True),
+                task_ids=task_ids,
+            )
+
+            # ------------------------------------------------------------------ Driver SDK
+            pull_task_res_res: driver_pb2.PullTaskResResponse = driver.pull_task_res(
+                req=pull_task_res_req
+            )
+            # ------------------------------------------------------------------ Driver SDK
+
+            task_res_list: List[task_pb2.TaskRes] = pull_task_res_res.task_res_list
+
+            time.sleep(sleep_time)
+
+            all_task_res += task_res_list
+            if len(all_task_res) == len(task_ids):
+                break
+
+        # Collect correct results
+        node_messages = task_res_list_to_task_dict(
+            [res for res in all_task_res if res.task.HasField("sa")]
+        )
+    workflow.close()
+
+    # Slow down the start of the next round
+    time.sleep(sleep_time)
+
+# -------------------------------------------------------------------------- Driver SDK
+driver.disconnect()
+# -------------------------------------------------------------------------- Driver SDK
+print("Driver disconnected")

examples/secaggplus-mt/run.sh

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+#!/bin/bash
+# Kill any currently running client.py processes
+pkill -f 'python client.py'
+
+# Kill any currently running flower-server processes with --grpc-rere option
+pkill -f 'flower-server --grpc-rere'
+
+# Start the flower server
+echo "Starting flower server in background..."
+flower-server --grpc-rere > /dev/null 2>&1 &
+sleep 2
+
+# Number of client processes to start
+N=5 # Replace with your desired value
+
+echo "Starting $N clients in background..."
+
+# Start N client processes
+for i in $(seq 1 $N)
+do
+  python client.py > /dev/null 2>&1 &
+  # python client.py &
+  sleep 0.1
+done
+
+echo "Starting driver..."
+python driver.py
+
+echo "Clearing background processes..."
+
+# Kill any currently running client.py processes
+pkill -f 'python client.py'
+
+# Kill any currently running flower-server processes with --grpc-rere option
+pkill -f 'flower-server --grpc-rere'