class renaming

docs/programming_guide/fed_job_api.rst

@@ -366,7 +366,7 @@ The FedAvgJob automatically adds the FedAvg controller, PTFileModelPersistor and
 
 For more examples of job patterns, see:
 
-* :class:`BaseFedJob<nvflare.job_config.base_fed_job.BaseFedJob>`
+* :class:`CommonJob<nvflare.job_config.common_job.CommonJob>`
 * :class:`FedAvgJob<nvflare.app_opt.pt.job_config.fed_avg.FedAvgJob>` (pytorch)
 * :class:`FedAvgJob<nvflare.app_opt.tf.job_config.fed_avg.FedAvgJob>` (tensorflow)
 * :class:`CCWFJob<nvflare.app_common.ccwf.ccwf_job.CCWFJob>`

examples/getting_started/pt/nvflare_lightning_getting_started.ipynb

@@ -321,8 +321,8 @@
     "#### 2. Define a FedJob\n",
     "The `FedJob` is used to define how controllers and executors are placed within a federated job using the `to(object, target)` routine.\n",
     "\n",
-    "Here we use a PyTorch `PTBaseFedJob`, where we can define the job name and the initial global model.\n",
-    "The `PTBaseFedJob` automatically configures components for model persistence, model selection, and TensorBoard streaming for convenience."
+    "Here we use a PyTorch `PTJob`, where we can define the job name and the initial global model.\n",
+    "The `PTJob` automatically configures components for model persistence, model selection, and TensorBoard streaming for convenience."
    ]
   },
   {
@@ -335,10 +335,10 @@
     "from src.lit_net import LitNet\n",
     "\n",
     "from nvflare.app_common.workflows.fedavg import FedAvg\n",
-    "from nvflare.app_opt.pt.job_config.base_fed_job import PTBaseFedJob\n",
+    "from nvflare.app_opt.pt.job_config.pt_job import PTJob\n",
     "from nvflare.job_config.script_runner import ScriptRunner\n",
     "\n",
-    "job = PTBaseFedJob(\n",
+    "job = PTJob(\n",
     "    name=\"cifar10_lightning_fedavg\",\n",
     "    initial_model=LitNet(),\n",
     ")"

examples/getting_started/pt/nvflare_pt_getting_started.ipynb

@@ -263,8 +263,8 @@
     "#### 2. Define a FedJob\n",
     "The `FedJob` is used to define how controllers and executors are placed within a federated job using the `to(object, target)` routine.\n",
     "\n",
-    "Here we use a PyTorch `PTBaseFedJob`, where we can define the job name and the initial global model.\n",
-    "The `PTBaseFedJob` automatically configures components for model persistence, model selection, and TensorBoard streaming for convenience."
+    "Here we use a PyTorch `PTJob`, where we can define the job name and the initial global model.\n",
+    "The `PTJob` automatically configures components for model persistence, model selection, and TensorBoard streaming for convenience."
    ]
   },
   {
@@ -277,10 +277,10 @@
     "from src.net import Net\n",
     "\n",
     "from nvflare.app_common.workflows.fedavg import FedAvg\n",
-    "from nvflare.app_opt.pt.job_config.base_fed_job import PTBaseFedJob\n",
+    "from nvflare.app_opt.pt.job_config.pt_job import PTJob\n",
     "from nvflare.job_config.script_runner import ScriptRunner\n",
     "\n",
-    "job = PTBaseFedJob(\n",
+    "job = PTJob(\n",
     "    name=\"cifar10_pt_fedavg\",\n",
     "    initial_model=Net(),\n",
     ")"

examples/getting_started/tf/nvflare_tf_getting_started.ipynb

@@ -253,8 +253,8 @@
     "#### 2. Define a FedJob\n",
     "The `FedJob` is used to define how controllers and executors are placed within a federated job using the `to(object, target)` routine.\n",
     "\n",
-    "Here we use a TensorFlow `TFBaseFedJob`, where we can define the job name and the initial global model.\n",
-    "The `TFBaseFedJob` automatically configures components for model persistence, model selection, and TensorBoard streaming for convenience."
+    "Here we use a TensorFlow `TFJob`, where we can define the job name and the initial global model.\n",
+    "The `TFJob` automatically configures components for model persistence, model selection, and TensorBoard streaming for convenience."
    ]
   },
   {
@@ -267,10 +267,10 @@
     "from src.tf_net import TFNet\n",
     "\n",
     "from nvflare.app_common.workflows.fedavg import FedAvg\n",
-    "from nvflare.app_opt.tf.job_config.base_fed_job import TFBaseFedJob\n",
+    "from nvflare.app_opt.tf.job_config.tf_job import TFJob\n",
     "from nvflare.job_config.script_runner import FrameworkType, ScriptRunner\n",
     "\n",
-    "job = TFBaseFedJob(\n",
+    "job = TFJob(\n",
     "    name=\"cifar10_tf_fedavg\",\n",
     "    initial_model=TFNet(),\n",
     ")"

nvflare/app_opt/pt/job_config/fed_avg.py

@@ -16,10 +16,10 @@
 import torch.nn as nn
 
 from nvflare.app_common.workflows.fedavg import FedAvg
-from nvflare.app_opt.pt.job_config.base_fed_job import PTBaseFedJob
+from nvflare.app_opt.pt.job_config.pt_job import PTJob
 
 
-class FedAvgJob(PTBaseFedJob):
+class FedAvgJob(PTJob):
     def __init__(
         self,
         initial_model: nn.Module,

nvflare/app_opt/pt/job_config/fed_sag_mlflow.py

@@ -19,12 +19,12 @@
 from nvflare.app_common.aggregators import InTimeAccumulateWeightedAggregator
 from nvflare.app_common.shareablegenerators import FullModelShareableGenerator
 from nvflare.app_common.workflows.scatter_and_gather import ScatterAndGather
-from nvflare.app_opt.pt.job_config.base_fed_job import PTBaseFedJob
+from nvflare.app_opt.pt.job_config.pt_job import PTJob
 from nvflare.app_opt.tracking.mlflow.mlflow_receiver import MLflowReceiver
 from nvflare.app_opt.tracking.mlflow.mlflow_writer import MLflowWriter
 
 
-class SAGMLFlowJob(PTBaseFedJob):
+class SAGMLFlowJob(PTJob):
     def __init__(
         self,
         initial_model: nn.Module,

nvflare/app_opt/pt/job_config/base_fed_job.py → nvflare/app_opt/pt/job_config/pt_job.py

@@ -25,10 +25,10 @@
 from nvflare.app_opt.pt.job_config.model import PTModel
 from nvflare.app_opt.tracking.tb.tb_receiver import TBAnalyticsReceiver
 from nvflare.job_config.api import validate_object_for_job
-from nvflare.job_config.base_fed_job import BaseFedJob
+from nvflare.job_config.common_job import CommonJob
 
 
-class PTBaseFedJob(BaseFedJob):
+class PTJob(CommonJob):
     def __init__(
         self,
         initial_model: nn.Module = None,
@@ -43,7 +43,7 @@ def __init__(
         model_persistor: Optional[ModelPersistor] = None,
         model_locator: Optional[ModelLocator] = None,
     ):
-        """PyTorch BaseFedJob.
+        """PyTorch CommonJob.
 
         Configures ValidationJsonGenerator, IntimeModelSelector, AnalyticsReceiver, ConvertToFedEvent.
 

nvflare/app_opt/tf/job_config/fed_avg.py

@@ -16,10 +16,10 @@
 import tensorflow as tf
 
 from nvflare.app_common.workflows.fedavg import FedAvg
-from nvflare.app_opt.tf.job_config.base_fed_job import TFBaseFedJob
+from nvflare.app_opt.tf.job_config.tf_job import TFJob
 
 
-class FedAvgJob(TFBaseFedJob):
+class FedAvgJob(TFJob):
     def __init__(
         self,
         initial_model: tf.keras.Model,

nvflare/app_opt/tf/job_config/base_fed_job.py → nvflare/app_opt/tf/job_config/tf_job.py

@@ -24,10 +24,10 @@
 from nvflare.app_opt.tf.job_config.model import TFModel
 from nvflare.app_opt.tracking.tb.tb_receiver import TBAnalyticsReceiver
 from nvflare.job_config.api import validate_object_for_job
-from nvflare.job_config.base_fed_job import BaseFedJob
+from nvflare.job_config.common_job import CommonJob
 
 
-class TFBaseFedJob(BaseFedJob):
+class TFJob(CommonJob):
     def __init__(
         self,
         initial_model: tf.keras.Model = None,
@@ -41,7 +41,7 @@ def __init__(
         analytics_receiver: Optional[AnalyticsReceiver] = None,
         model_persistor: Optional[ModelPersistor] = None,
     ):
-        """TensorFlow BaseFedJob.
+        """TensorFlow CommonJob.
 
         Configures ValidationJsonGenerator, IntimeModelSelector, TBAnalyticsReceiver, ConvertToFedEvent.
 

nvflare/job_config/base_fed_job.py → nvflare/job_config/common_job.py

@@ -24,7 +24,7 @@
 from nvflare.job_config.api import FedJob, validate_object_for_job
 
 
-class BaseFedJob(FedJob):
+class CommonJob(FedJob):
     def __init__(
         self,
         name: str = "fed_job",
@@ -38,7 +38,7 @@ def __init__(
         model_persistor: Optional[ModelPersistor] = None,
         model_locator: Optional[ModelLocator] = None,
     ):
-        """BaseFedJob.
+        """CommonJob.
 
         By default configures ValidationJsonGenerator, IntimeModelSelector, ConvertToFedEvent.
 

web/src/components/code.astro

@@ -206,16 +206,16 @@ const jobCode_pt = `
 from cifar10_pt_fl import Net
 
 from nvflare.app_common.workflows.fedavg import FedAvg
-from nvflare.app_opt.pt.job_config.base_fed_job import PTBaseFedJob
+from nvflare.app_opt.pt.job_config.pt_job import PTJob
 from nvflare.job_config.script_runner import ScriptRunner
 
 if __name__ == "__main__":
     n_clients = 2
     num_rounds = 2
     train_script = "cifar10_pt_fl.py"
 
-    # Create PTBaseFedJob with initial model
-    job = PTBaseFedJob(
+    # Create PTJob with initial model
+    job = PTJob(
       name="cifar10_pt_fedavg",
       initial_model=Net(),
     )
@@ -425,16 +425,16 @@ const jobCode_lt = `
 from cifar10_lightning_fl import LitNet
 
 from nvflare.app_common.workflows.fedavg import FedAvg
-from nvflare.app_opt.pt.job_config.base_fed_job import PTBaseFedJob
+from nvflare.app_opt.pt.job_config.pt_job import PTJob
 from nvflare.job_config.script_runner import ScriptRunner
 
 if __name__ == "__main__":
     n_clients = 2
     num_rounds = 2
     train_script = "cifar10_lightning_fl.py"
 
-    # Create PTBaseFedJob with initial model
-    job = PTBaseFedJob(
+    # Create PTJob with initial model
+    job = PTJob(
       name="cifar10_lightning_fedavg",
       initial_model=LitNet(),
     )
@@ -587,16 +587,16 @@ const jobCode_tf = `
 from cifar10_tf_fl import TFNet
 
 from nvflare.app_common.workflows.fedavg import FedAvg
-from nvflare.app_opt.tf.job_config.base_fed_job import TFBaseFedJob
+from nvflare.app_opt.tf.job_config.tf_job import TFJob
 from nvflare.job_config.script_runner import FrameworkType, ScriptRunner
 
 if __name__ == "__main__":
     n_clients = 2
     num_rounds = 2
     train_script = "cifar10_tf_fl.py"
 
-    # Create TFBaseFedJob with initial model
-    job = TFBaseFedJob(
+    # Create TFJob with initial model
+    job = TFJob(
       name="cifar10_tf_fedavg",
       initial_model=TFNet(input_shape=(None, 32, 32, 3)),
     )
@@ -665,7 +665,7 @@ const frameworks = [
         framework: "pytorch",
         title: "Job Code (fedavg_cifar10_pt_job.py)",
         description:
-          "Lastly we construct the job with our 'cifar10_pt_fl.py' client script and 'FedAvg' server controller. The PTBaseFedJob automatically configures components for model persistence, model selection, and TensorBoard streaming. We then run the job with the FL simulator.",
+          "Lastly we construct the job with our 'cifar10_pt_fl.py' client script and 'FedAvg' server controller. The PTJob automatically configures components for model persistence, model selection, and TensorBoard streaming. We then run the job with the FL simulator.",
         code: jobCode_pt,
       },
       {
@@ -719,7 +719,7 @@ const frameworks = [
         framework: "lightning",
         title: "Job Code (fedavg_cifar10_lightning_job.py)",
         description:
-          "Lastly we construct the job with our 'cifar10_lightning_fl.py' client script and 'FedAvg' server controller. The PTBaseFedJob automatically configures components for model persistence, model selection, and TensorBoard streaming. We then run the job with the FL simulator.",
+          "Lastly we construct the job with our 'cifar10_lightning_fl.py' client script and 'FedAvg' server controller. The PTJob automatically configures components for model persistence, model selection, and TensorBoard streaming. We then run the job with the FL simulator.",
         code: jobCode_lt,
       },
       {
@@ -773,7 +773,7 @@ const frameworks = [
         framework: "tensorflow",
         title: "Job Code (fedavg_cifar10_tf_job.py)",
         description:
-          "Lastly we construct the job with our 'cifar10_tf_fl.py' client script and 'FedAvg' server controller. The TFBaseFedJob automatically configures components for model persistence, model selection, and TensorBoard streaming. We then run the job with the FL simulator.",
+          "Lastly we construct the job with our 'cifar10_tf_fl.py' client script and 'FedAvg' server controller. The TFJob automatically configures components for model persistence, model selection, and TensorBoard streaming. We then run the job with the FL simulator.",
         code: jobCode_tf,
       },
       {