Update flower examples (#2871)

examples/hello-world/hello-flower/README.md

@@ -33,19 +33,19 @@ pip install ./flwr-pt/
 
 Next, we run 2 Flower clients and Flower Server in parallel using NVFlare's simulator.
 ```bash
-python job.py
+python job.py --job_name "flwr-pt" --content_dir "./flwr-pt"
 ```
 
 ## 2.2 Run a simulation with TensorBoard streaming
 
 To run flwr-pt_tb_streaming job with NVFlare, we first need to install its dependencies.
 ```bash
-pip install ./flwr-pt-metrics/
+pip install ./flwr-pt-tb/
 ```
 
 Next, we run 2 Flower clients and Flower Server in parallel using NVFlare while streaming 
 the TensorBoard metrics to the server at each iteration using NVFlare's metric streaming.
 
 ```bash
-python job_with_metric.py
+python job.py --job_name "flwr-pt-tb" --content_dir "./flwr-pt-tb" --stream_metrics --use_client_api
 ```

examples/hello-world/hello-flower/flwr-pt-metrics/pyproject.toml → examples/hello-world/hello-flower/flwr-pt-tb/pyproject.toml

@@ -3,7 +3,7 @@ requires = ["hatchling"]
 build-backend = "hatchling.build"
 
 [project]
-name = "flwr_pt_tb_streaming"
+name = "flwr_pt_tb"
 version = "1.0.0"
 description = ""
 license = "Apache-2.0"
@@ -12,6 +12,7 @@ dependencies = [
     "nvflare~=2.5.0rc",
     "torch==2.2.1",
     "torchvision==0.17.1",
+    "tensorboard"
 ]
 
 [tool.hatch.build.targets.wheel]
@@ -21,8 +22,8 @@ packages = ["."]
 publisher = "nvidia"
 
 [tool.flwr.app.components]
-serverapp = "flwr_pt_tb_streaming.server:app"
-clientapp = "flwr_pt_tb_streaming.client:app"
+serverapp = "flwr_pt_tb.server:app"
+clientapp = "flwr_pt_tb.client:app"
 
 [tool.flwr.app.config]
 num-server-rounds = 3

examples/hello-world/hello-flower/job.py

@@ -12,10 +12,37 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
+from argparse import ArgumentParser
+
 from nvflare.app_opt.flower.flower_job import FlowerJob
+from nvflare.client.api import ClientAPIType
+from nvflare.client.api_spec import CLIENT_API_TYPE_KEY
 
-if __name__ == "__main__":
-    job = FlowerJob(name="flwr-pt", flower_content="./flwr-pt")
 
-    job.export_job("jobs")
-    job.simulator_run("/tmp/nvflare/flwr-pt", gpu="0", n_clients=2)
+def main():
+    parser = ArgumentParser()
+    parser.add_argument("--job_name", type=str, required=True)
+    parser.add_argument("--content_dir", type=str, required=True)
+    parser.add_argument("--stream_metrics", action="store_true")
+    parser.add_argument("--use_client_api", action="store_true")
+    parser.add_argument("--export_dir", type=str, default="jobs")
+    parser.add_argument("--workdir", type=str, default="/tmp/nvflare/hello-flower")
+    args = parser.parse_args()
+
+    env = {}
+    if args.use_client_api:
+        env = {CLIENT_API_TYPE_KEY: ClientAPIType.EX_PROCESS_API.value}
+
+    job = FlowerJob(
+        name=args.job_name,
+        flower_content=args.content_dir,
+        stream_metrics=args.stream_metrics,
+        extra_env=env,
+    )
+
+    job.export_job(args.export_dir)
+    job.simulator_run(args.workdir, gpu="0", n_clients=2)
+
+
+if __name__ == "__main__":
+    main()