Merge pull request #503 from FedML-AI/test/v0.7.0

Test/v0.7.0

doc/en/cross-silo/examples.md

@@ -4,9 +4,9 @@
 
 - [mqtt_s3_fedavg_mnist_lr_example](./examples/mqtt_s3_fedavg_mnist_lr_example.md): an example to illustrate running horizontal federated learning in data silos (hospitals, banks, etc.)
 
-- [mqtt_s3_fedavg_mnist_lr_example](./examples/mqtt_s3_fedavg_attack_mnist_lr_example.md): an example to illustrate running attackers on horizontal federated learning
+- [mqtt_s3_fedavg_attack_mnist_lr_example](./examples/mqtt_s3_fedavg_attack_mnist_lr_example.md): an example to illustrate running attackers on horizontal federated learning
 
-- [mqtt_s3_fedavg_mnist_lr_example](./examples/mqtt_s3_fedavg_defense_mnist_lr_example.md): an example to illustrate running defense methods on horizontal federated learning
+- [mqtt_s3_fedavg_defense_mnist_lr_example](./examples/mqtt_s3_fedavg_defense_mnist_lr_example.md): an example to illustrate running defense methods on horizontal federated learning
 
 ## Hierarchical Federated Learning
 
@@ -15,3 +15,4 @@ As shown in the figure below, here `hierarchical` implies that each FL Client (d
 
 <img src="./../_static/image/cross-silo-hi.png" alt="parrot" style="width:100%;"/>
 
+

doc/en/feature/fedml_feature_overview.md

@@ -0,0 +1,2 @@
+# Overview
+

python/fedml/cli/edge_deployment/client_runner.py

@@ -789,15 +789,6 @@ def send_agent_active_msg(self):
     def on_agent_mqtt_connected(self, mqtt_client_object):
         # The MQTT message topic format is as follows: <sender>/<receiver>/<action>
 
-        # Init the mlops metrics object
-        if self.mlops_metrics is None:
-            self.mlops_metrics = MLOpsMetrics()
-            self.mlops_metrics.set_messenger(self.mqtt_mgr)
-            self.mlops_metrics.report_client_training_status(self.edge_id, ClientConstants.MSG_MLOPS_CLIENT_STATUS_IDLE)
-            MLOpsStatus.get_instance().set_client_agent_status(
-                self.edge_id, ClientConstants.MSG_MLOPS_CLIENT_STATUS_IDLE
-            )
-
         # Setup MQTT message listener for starting training
         topic_start_train = "flserver_agent/" + str(self.edge_id) + "/start_train"
         self.mqtt_mgr.add_message_listener(topic_start_train, self.callback_start_train)
@@ -872,6 +863,12 @@ def setup_agent_mqtt_connection(self, service_config):
         self.mqtt_mgr.add_disconnected_listener(self.on_agent_mqtt_disconnected)
         self.mqtt_mgr.connect()
 
+        self.setup_client_mqtt_mgr()
+        self.wait_client_mqtt_connected()
+        self.mlops_metrics.report_client_training_status(self.edge_id,
+                                                         ClientConstants.MSG_MLOPS_CLIENT_STATUS_IDLE)
+        self.release_client_mqtt_mgr()
+
     def start_agent_mqtt_loop(self):
         # Start MQTT message loop
         try:

python/fedml/core/distributed/communication/mqtt/mqtt_manager.py

@@ -75,7 +75,7 @@ def send_message(self, topic, message, wait_for_publish=True):
         MLOpsProfilerEvent.log_to_wandb({"Comm/send_delay_mqtt": time.time() - mqtt_send_start_time})
 
     def send_message_json(self, topic, message, wait_for_publish=True):
-        ret_info = self._client.publish(topic, payload=message, qos=2)
+        ret_info = self._client.publish(topic, payload=message)
         if wait_for_publish:
             try:
                 ret_info.wait_for_publish(1)