Add CSE with job api with client api (#2918)

examples/advanced/job_api/pt/cse_script_runner_cifar10.py

@@ -0,0 +1,72 @@
+# Copyright (c) 2024, NVIDIA CORPORATION.  All rights reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+
+from src.net import Net
+
+from nvflare import FedJob
+from nvflare.app_common.aggregators.intime_accumulate_model_aggregator import InTimeAccumulateWeightedAggregator
+from nvflare.app_common.shareablegenerators.full_model_shareable_generator import FullModelShareableGenerator
+from nvflare.app_common.widgets.intime_model_selector import IntimeModelSelector
+from nvflare.app_common.widgets.validation_json_generator import ValidationJsonGenerator
+from nvflare.app_common.workflows.cross_site_model_eval import CrossSiteModelEval
+from nvflare.app_common.workflows.scatter_and_gather import ScatterAndGather
+from nvflare.app_opt.pt.file_model_locator import PTFileModelLocator
+from nvflare.app_opt.pt.file_model_persistor import PTFileModelPersistor
+from nvflare.job_config.script_runner import ScriptRunner
+
+if __name__ == "__main__":
+    n_clients = 2
+    num_rounds = 2
+    train_script = "src/train_eval_submit.py"
+
+    job = FedJob(name="cse_pt")
+
+    shareable_generator_id = job.to_server(FullModelShareableGenerator(), id="shareable_generator")
+    persistor_id = job.to_server(PTFileModelPersistor(model=Net()), id="persistor")
+    aggregator_id = job.to_server(InTimeAccumulateWeightedAggregator(expected_data_kind="WEIGHTS"), id="aggregator")
+    controller = ScatterAndGather(
+        min_clients=n_clients,
+        num_rounds=num_rounds,
+        aggregator_id=aggregator_id,
+        persistor_id=persistor_id,
+        shareable_generator_id=shareable_generator_id,
+        train_task_name="train",
+    )
+    job.to_server(controller)
+    job.to_server(IntimeModelSelector(key_metric="accuracy"))
+
+    model_locator_id = job.to_server(PTFileModelLocator(pt_persistor_id=persistor_id), id="model_locator")
+    controller2 = CrossSiteModelEval(
+        model_locator_id=model_locator_id,
+        submit_model_timeout=600,
+        validation_timeout=6000,
+        cleanup_models=False,
+        validation_task_name="validate",
+        submit_model_task_name="submit_model",
+    )
+
+    job.to_server(controller2)
+    job.to_server(ValidationJsonGenerator())
+
+    # Add clients
+    for i in range(n_clients):
+        executor = ScriptRunner(
+            script=train_script,
+            script_args="",
+        )
+        job.to(executor, f"site-{i+1}")
+
+    # job.export_job("/tmp/nvflare/jobs/job_config")
+    job.simulator_run("/tmp/nvflare/jobs/workdir", gpu="0")