Update Workflow_Interface_VFL_Two_Party

Added actor related changed to Workflow_Interface_VFL_Two_Party

Signed-off-by: Parth Mandaliya <parthx.mandaliya@intel.com>

openfl-tutorials/experimental/Vertical_FL/Workflow_Interface_VFL_Two_Party.ipynb

@@ -152,21 +152,47 @@
    "source": [
     "# Setup participants\n",
     "aggregator = Aggregator()\n",
-    "aggregator.private_attributes['trainloader'] = trainloader\n",
-    "aggregator.private_attributes['label_model'] = label_model\n",
-    "aggregator.private_attributes['label_model_optimizer'] = label_model_optimizer\n",
     "\n",
-    "# Setup collaborators with private attributes\n",
+    "def callable_to_initialize_aggregator_private_attributes(train_loader,label_model,label_model_optimizer):\n",
+    "        return {\"trainloader\": train_loader,\n",
+    "                \"label_model\" : label_model,\n",
+    "                \"label_model_optimizer\":label_model_optimizer\n",
+    "                }  \n",
+    "\n",
+    "# Setup aggregator private attributes via callable function\n",
+    "aggregator = Aggregator(\n",
+    "    name=\"agg\",\n",
+    "    private_attributes_callable=callable_to_initialize_aggregator_private_attributes,\n",
+    "    train_loader = trainloader,\n",
+    "    label_model=label_model,\n",
+    "    label_model_optimizer=label_model_optimizer\n",
+    ")\n",
+    "\n",
+    "# Setup collaborators private attributes via callable function\n",
     "collaborator_names = ['Portland']\n",
-    "collaborators = [Collaborator(name=name) for name in collaborator_names]\n",
     "\n",
-    "for idx, collaborator in enumerate(collaborators):\n",
-    "    collaborator.private_attributes['data_model'] = data_model\n",
-    "    collaborator.private_attributes['data_model_optimizer'] = data_model_optimizer\n",
-    "    collaborator.private_attributes['trainloader'] = deepcopy(trainloader)\n",
+    "def callable_to_initialize_collaborator_private_attributes(index,data_model,data_model_optimizer,train_loader):\n",
+    "    return {\n",
+    "        \"data_model\": data_model,\n",
+    "        \"data_model_optimizer\": data_model_optimizer,\n",
+    "        \"trainloader\" : deepcopy(train_loader)\n",
+    "    }\n",
+    "\n",
+    "collaborators = []\n",
+    "for idx, collaborator_name in enumerate(collaborator_names):\n",
+    "        collaborators.append(\n",
+    "            Collaborator(\n",
+    "                name=collaborator_name,\n",
+    "                private_attributes_callable=callable_to_initialize_collaborator_private_attributes,\n",
+    "                index=idx,\n",
+    "                data_model = data_model,\n",
+    "                data_model_optimizer = data_model_optimizer,\n",
+    "                train_loader = trainloader\n",
+    "            )\n",
+    "        )\n",
     "\n",
     "local_runtime = LocalRuntime(\n",
-    "    aggregator=aggregator, collaborators=collaborators, backend='single_process')\n",
+    "    aggregator=aggregator, collaborators=collaborators, backend='ray')\n",
     "print(f'Local runtime collaborators = {local_runtime.collaborators}')\n",
     "\n",
     "epochs = 100\n",
@@ -252,7 +278,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.8.13"
+   "version": "3.8.17"
   }
  },
  "nbformat": 4,