merge master

.github/workflows/CI_federate.yml

@@ -39,4 +39,4 @@ jobs:
         run: |
           cd python
           bash tests/test_federate/test_federate.sh
-          echo "Federate example has been tested successfully!"
+          echo "Federate example has been tested successfully!"

.github/workflows/CI_serving.yml

@@ -0,0 +1,42 @@
+# This is a basic workflow to help you get started with Actions
+
+name: CI-serving
+
+# Controls when the workflow will run
+on:
+  # Triggers the workflow on push or pull request events but only for the master branch
+  schedule:
+    # Nightly build at 12:12 A.M.
+    - cron: "0 10 */1 * *"
+  pull_request:
+    branches: [ master,  dev/v0.7.0 ]
+
+  # Allows you to run this workflow manually from the Actions tab
+  workflow_dispatch:
+
+# A workflow run is made up of one or more jobs that can run sequentially or in parallel
+jobs:
+  serving:
+    runs-on: ${{ matrix.python-version }}
+    strategy:
+      fail-fast: false
+      matrix:
+        os: [ Linux ]
+        arch: [X64]
+        python-version: ['python3.8', 'python3.9', 'python3.10', 'python3.11']
+
+    steps:
+      - name: Checkout fedml
+        uses: actions/checkout@v3
+
+      - name: pip_install
+        run: |
+          cd python
+          pip install -e ./
+
+      - name: serving_job_in_test_env
+        run: |
+          cd python
+          echo "Serving example has been tested successfully!" 
+          # python tests/test_launch/test_launch.py
+          

.github/workflows/CI_train.yml

@@ -39,5 +39,4 @@ jobs:
           cd python
           python tests/test_train/test_train.py
           echo "Train example has been tested successfully!" 
-          # cd examples/federate/quick_start/beehive
 

python/fedml/computing/scheduler/comm_utils/network_util.py

@@ -0,0 +1,18 @@
+import os
+from fedml.computing.scheduler.model_scheduler.device_client_constants import ClientConstants
+
+
+def return_this_device_connectivity_type() -> str:
+    """
+    Return -> "http" | "http_proxy" |"mqtt"
+    """
+    # Get the environmental variable's value and convert to lower case.
+    env_conn_type = os.getenv(ClientConstants.ENV_CONNECTION_TYPE_KEY, "").lower()
+    if env_conn_type in [
+        ClientConstants.WORKER_CONNECTIVITY_TYPE_HTTP,
+        ClientConstants.WORKER_CONNECTIVITY_TYPE_HTTP_PROXY,
+        ClientConstants.WORKER_CONNECTIVITY_TYPE_MQTT
+    ]:
+        return env_conn_type
+    else:
+        return ClientConstants.WORKER_CONNECTIVITY_TYPE_DEFAULT

python/fedml/computing/scheduler/model_scheduler/device_client_constants.py

@@ -97,6 +97,12 @@ class ClientConstants(object):
     INFERENCE_INFERENCE_SERVER_VERSION = "v2"
     INFERENCE_REQUEST_TIMEOUT = 30
 
+    ENV_CONNECTION_TYPE_KEY = "FEDML_CONNECTION_TYPE"
+    WORKER_CONNECTIVITY_TYPE_HTTP = "http"
+    WORKER_CONNECTIVITY_TYPE_HTTP_PROXY = "http_proxy"
+    WORKER_CONNECTIVITY_TYPE_MQTT = "mqtt"
+    WORKER_CONNECTIVITY_TYPE_DEFAULT = WORKER_CONNECTIVITY_TYPE_HTTP
+
     MSG_MODELOPS_DEPLOYMENT_STATUS_INITIALIZING = "INITIALIZING"
     MSG_MODELOPS_DEPLOYMENT_STATUS_DEPLOYING = "DEPLOYING"
     MSG_MODELOPS_DEPLOYMENT_STATUS_INFERRING = "INFERRING"

python/fedml/computing/scheduler/model_scheduler/device_model_cache.py

@@ -344,9 +344,13 @@ def get_result_item_info(self, result_item):
             result_payload = result_item_json["result"]
         return device_id, replica_no, result_payload
 
-    def get_idle_device(self, end_point_id, end_point_name,
-                        model_name, model_version,
-                        check_end_point_status=True, limit_specific_model_version=False):
+    def get_idle_device(self,
+                        end_point_id,
+                        end_point_name,
+                        model_name,
+                        model_version,
+                        check_end_point_status=True,
+                        limit_specific_model_version=False):
         # Deprecated the model status logic, query directly from the deployment result list
         idle_device_list = list()
 
@@ -365,7 +369,7 @@ def get_idle_device(self, end_point_id, end_point_name,
                 if "model_status" in result_payload and result_payload["model_status"] == "DEPLOYED":
                     idle_device_list.append({"device_id": device_id, "end_point_id": end_point_id})
 
-        logging.info(f"{len(idle_device_list)} devices this model has on it: {idle_device_list}")
+        logging.debug(f"{len(idle_device_list)} devices this model has on it: {idle_device_list}")
 
         if len(idle_device_list) <= 0:
             return None, None
@@ -394,7 +398,7 @@ def get_idle_device(self, end_point_id, end_point_name,
             logging.info("Inference Device selection Failed:")
             logging.info(e)
 
-        logging.info(f"Using Round Robin, the device index is {selected_device_index}")
+        logging.debug(f"Using Round Robin, the device index is {selected_device_index}")
         idle_device_dict = idle_device_list[selected_device_index]
 
         # Note that within the same endpoint_id, there could be one device with multiple same models
@@ -407,7 +411,7 @@ def get_idle_device(self, end_point_id, end_point_name,
         # Find deployment result from the target idle device.
         try:
             for result_item in result_list:
-                logging.info("enter the for loop")
+                logging.debug("enter the for loop")
                 device_id, _, result_payload = self.get_result_item_info(result_item)
                 found_end_point_id = result_payload["end_point_id"]
                 found_end_point_name = result_payload["end_point_name"]
@@ -421,7 +425,7 @@ def get_idle_device(self, end_point_id, end_point_name,
                     if same_model_device_rank > 0:
                         same_model_device_rank -= 1
                         continue
-                    logging.info(f"The chosen device is {device_id}")
+                    logging.debug(f"The chosen device is {device_id}")
                     return result_payload, device_id
         except Exception as e:
             logging.info(str(e))

python/fedml/computing/scheduler/model_scheduler/device_model_cards.py

@@ -14,7 +14,6 @@
 
 from fedml.core.common.singleton import Singleton
 from fedml.computing.scheduler.model_scheduler.modelops_configs import ModelOpsConfigs
-from fedml.computing.scheduler.model_scheduler.device_model_deployment import get_model_info
 from fedml.computing.scheduler.model_scheduler.device_server_constants import ServerConstants
 from fedml.computing.scheduler.model_scheduler.device_model_object import FedMLModelList, FedMLEndpointDetail
 from fedml.computing.scheduler.model_scheduler.device_client_constants import ClientConstants