Rename to execution api type, update job command output (NVIDIA#2306)

* rename client category to execution api type

* fix output format

docs/user_guide/nvflare_cli/job_cli.rst

@@ -45,22 +45,42 @@ the job_templates.
 
 The output should be similar to the following:
 
-.. code-block::shell
+.. code-block:: none
 
     The following job templates are available: 
 
-    ------------------------------------------------------------------------------------------------------------------------
-    name                 Description                                                  Controller Type      Client Category     
-    ------------------------------------------------------------------------------------------------------------------------
-    sag_cross_np         scatter & gather and cross-site validation using numpy       server               client executor     
-    sag_pt               scatter & gather workflow using pytorch                      server               client_api          
-    sag_pt_ddp           scatter & gather workflow using pytorch + ddp                server               client_api          
-    sag_pt_deploy_map    SAG workflow with pytorch, deploy_map, site-specific configs server               client_api          
-    sag_tf               scatter & gather workflow using TensorFlow                   server               client_api          
-    stats_df             FedStats: tabular data with pandas                           server               stats executor      
-    stats_image          FedStats: image intensity histogram                          server               stats executor      
-    ------------------------------------------------------------------------------------------------------------------------
-
+    ----------------------------------------------------------------------------------------------------------------------
+    name                 Description                                                  Controller Type   Execution API Type
+    ----------------------------------------------------------------------------------------------------------------------
+    cyclic_cc_pt         client-controlled cyclic workflow with PyTorch ClientAPI tra client            client_api
+    cyclic_pt            server-controlled cyclic workflow with PyTorch ClientAPI tra server            client_api
+    psi_csv              private-set intersection for csv data                        server            Executor
+    sag_cross_np         scatter & gather and cross-site validation using numpy       server            client executor
+    sag_cse_pt           scatter & gather workflow and cross-site evaluation with PyT server            client_api
+    sag_gnn              scatter & gather workflow for gnn learning                   server            client_api
+    sag_nemo             Scatter and Gather Workflow for NeMo                         server            client_api
+    sag_np               scatter & gather workflow using numpy                        server            client_api
+    sag_np_cell_pipe     scatter & gather workflow using numpy                        server            client_api
+    sag_np_metrics       scatter & gather workflow using numpy                        server            client_api
+    sag_pt               scatter & gather workflow using pytorch                      server            client_api
+    sag_pt_deploy_map    SAG workflow with pytorch, deploy_map, site-specific configs server            client_api
+    sag_pt_executor      scatter & gather workflow and cross-site evaluation with PyT server            Executor
+    sag_pt_he            scatter & gather workflow using pytorch and homomorphic encr server            client_api
+    sag_pt_mlflow        scatter & gather workflow using pytorch with MLflow tracking server            client_api
+    sag_pt_model_learner scatter & gather workflow and cross-site evaluation with PyT server            ModelLearner
+    sag_tf               scatter & gather workflow using TensorFlow                   server            client_api
+    sklearn_kmeans       scikit-learn KMeans model                                    server            client_api
+    sklearn_linear       scikit-learn linear model                                    server            client_api
+    sklearn_svm          scikit-learn SVM model                                       server            client_api
+    stats_df             FedStats: tabular data with pandas                           server            stats executor
+    stats_image          FedStats: image intensity histogram                          server            stats executor
+    swarm_cse_pt         Swarm Learning with Cross-Site Evaluation with PyTorch       client            client_api
+    swarm_cse_pt_model_l Swarm Learning with Cross-Site Evaluation with PyTorch Model client            ModelLearner
+    vertical_xgb         vertical federated xgboost                                   server            Executor
+    xgboost_tree         xgboost horizontal tree-based collaboration model            server            client_api
+    ----------------------------------------------------------------------------------------------------------------------
+
+View all the available templates at the :github_nvflare_link:`FLARE Job Template Registry <job_templates>`.
 
 Setting job_template path
 -------------------------
@@ -90,20 +110,18 @@ The options for usage are as follows:
 
 .. code-block::
 
-    usage: nvflare job create [-h] [-j [JOB_FOLDER]] [-w [TEMPLATE]] [-s [SCRIPT]] [-sd [SCRIPT_DIR]] [-f [CONFIG_FILE ...]] [-debug] [-force]
+    usage: nvflare job create [-h] [-j [JOB_FOLDER]] [-w [TEMPLATE]] [-sd [SCRIPT_DIR]] [-f [CONFIG_FILE [CONFIG_FILE ...]]] [-debug] [-force]
 
-    options:
+    optional arguments:
     -h, --help            show this help message and exit
     -j [JOB_FOLDER], --job_folder [JOB_FOLDER]
                             job_folder path, default to ./current_job directory
     -w [TEMPLATE], --template [TEMPLATE]
-                            template name or template folder. You can use list_templates to see available jobs from job templates, pick name such as 'sag_pt' as template name. Alternatively, you can use the path to the job template folder, such as
-                            job_templates/sag_pt
-    -s [SCRIPT], --script [SCRIPT]
-                            code script such as train.py
+                            template name or template folder. You can use list_templates to see available jobs from job templates, pick name such as 'sag_pt' as template name. Alternatively, you can use the path to the job
+                            template folder, such as job_templates/sag_pt
     -sd [SCRIPT_DIR], --script_dir [SCRIPT_DIR]
                             script directory contains additional related files. All files or directories under this directory will be copied over to the custom directory.
-    -f [CONFIG_FILE ...], --config_file [CONFIG_FILE ...]
+    -f [CONFIG_FILE [CONFIG_FILE ...]], --config_file [CONFIG_FILE [CONFIG_FILE ...]]
                             Training config file with corresponding optional key=value pairs. If key presents in the preceding config file, the value in the config file will be overwritten by the new value
     -debug, --debug       debug is on
     -force, --force       force create is on, if -force, overwrite existing configuration with newly created configurations
@@ -208,40 +226,3 @@ and change the app_1 batch_size to 4, app_2 batch_size to 6 for sag_pt_deploy_ma
 
     The app names must be defined in the job template being used: in this case ``app_1``, ``app_2``, and ``app_server``,
     are in ``sag_pt_deploy_map``.
-
-***************************
-FLARE Job Template Registry
-***************************
-
-Below is a table of all available :github_nvflare_link:`Job Templates <job_templates>`.
-
-.. csv-table::
-    :header: Example,Execution API Type,Controller Type,Description
-    :widths: 18, 18, 10, 30
-
-    cyclic_cc_pt,client,client_api,client-controlled cyclic workflow with PyTorch ClientAPI trainer
-    cyclic_pt,server,client_api,server-controlled cyclic workflow with PyTorch ClientAPI trainer
-    psi_csv,server,Executor,private-set intersection for csv data
-    sag_cross_np,server,client_executor,scatter & gather and cross-site validation using numpy
-    sag_cse_pt,server,client_api,scatter & gather workflow and cross-site evaluation with PyTorch
-    sag_gnn,server,client_api,scatter & gather workflow for gnn learning
-    sag_nemo,server,client_api,Scatter and Gather Workflow for NeMo
-    sag_np,server,client_api,scatter & gather workflow using numpy
-    sag_np_cell_pipe,server,client_api,scatter & gather workflow using numpy
-    sag_np_metrics,server,client_api,scatter & gather workflow using numpy
-    sag_pt,server,client_api,scatter & gather workflow using pytorch
-    sag_pt_deploy_map,server,client_api,SAG workflow using pytorch with deploy_map & site-specific configs
-    sag_pt_executor,server,Executor,scatter & gather workflow and cross-site evaluation with PyTorch
-    sag_pt_he,server,client_api,scatter & gather workflow using pytorch and homomorphic encryption
-    sag_pt_mlflow,server,client_api,scatter & gather workflow using pytorch with MLflow tracking
-    sag_pt_model_learner,server,ModelLearner,scatter & gather workflow and cross-site evaluation with PyTorch
-    sag_tf,server,client_api,scatter & gather workflow using TensorFlow
-    sklearn_kmeans,server,client_api,scikit-learn KMeans model
-    sklearn_linear,server,client_api,scikit-learn linear model
-    sklearn_svm,server,client_api,scikit-learn SVM model
-    stats_df,server,stats_executor,FedStats: tabular data with pandas
-    stats_image,server,stats_executor,FedStats: image intensity histogram
-    swarm_cse_pt,client,client_api,Swarm Learning with Cross-Site Evaluation with PyTorch
-    swarm_cse_pt_model_learner,client,ModelLearner,Swarm Learning with Cross-Site Evaluation with PyTorch ModelLearner
-    vertical_xgb,server,Executor,vertical federated xgboost
-    xgboost_tree,server,client_api,xgboost horizontal tree-based collaboration model

examples/README.md

@@ -83,7 +83,7 @@ When you open a notebook, select the kernel `nvflare_example` using the dropdown
 | [Hello TensorFlow](./hello-world/hello-tf2/README.md)                                                                                  | TensorFlow2  | Example of using an image classifier using [FedAvg](https://arxiv.org/abs/1602.05629) and [TensorFlow](https://tensorflow.org/) as the deep learning training framework. |
 
 ## 2. Step-by-Step Examples
-| Example | Dataset | Controller-Type | Client Category | Framework | Summary |
+| Example | Dataset | Controller-Type | Execution API Type | Framework | Summary |
 |---------|---------|-----------------|-----------------|-----------|---------|
 | [image_stats](./hello-world/step-by-step/cifar10/stats/image_stats.ipynb)                                                        | CIFAR10 | server | Executor | Pandas | Example for federated stats image histogram calculation. |
 | [sag](./hello-world/step-by-step/cifar10/sag/sag.ipynb)                                                                                   | CIFAR10 | server | Client API| PyTorch | Example for FedAvg with [ScatterAndGather](https://nvflare.readthedocs.io/en/main/apidocs/nvflare.app_common.workflows.scatter_and_gather.html) controller workflow using the Client API. |

job_templates/cyclic_cc_pt/info.conf

@@ -1,5 +1,5 @@
 {
     description = "client-controlled cyclic workflow with PyTorch ClientAPI trainer"
-    client_category = "client_api"
+    execution_api_type = "client_api"
     controller_type = "client"
 }

job_templates/cyclic_pt/info.conf

@@ -1,5 +1,5 @@
 {
     description = "server-controlled cyclic workflow with PyTorch ClientAPI trainer"
-    client_category = "client_api"
+    execution_api_type = "client_api"
     controller_type = "server"
 }

job_templates/psi_csv/info.conf

@@ -1,5 +1,5 @@
 {
     description = "private-set intersection for csv data"
-    client_category = "Executor"
+    execution_api_type = "Executor"
     controller_type = "server"
 }

job_templates/sag_cross_np/info.conf

@@ -1,5 +1,5 @@
 {
     description = "scatter & gather and cross-site validation using numpy"
-    client_category = "client executor"
+    execution_api_type = "client executor"
     controller_type = "server"
 }

job_templates/sag_cse_pt/info.conf

@@ -1,5 +1,5 @@
 {
     description = "scatter & gather workflow and cross-site evaluation with PyTorch"
-    client_category = "client_api"
+    execution_api_type = "client_api"
     controller_type = "server"
 }

job_templates/sag_gnn/info.conf

@@ -1,5 +1,5 @@
 {
     description = "scatter & gather workflow for gnn learning"
-    client_category = "client_api"
+    execution_api_type = "client_api"
     controller_type = "server"
 }

job_templates/sag_nemo/info.conf

@@ -1,5 +1,5 @@
 {
     description = "Scatter and Gather Workflow for NeMo"
-    client_category = "client_api"
+    execution_api_type = "client_api"
     controller_type = "server"
 }

job_templates/sag_np/info.conf

@@ -1,5 +1,5 @@
 {
     description = "scatter & gather workflow using numpy"
-    client_category = "client_api"
+    execution_api_type = "client_api"
     controller_type = "server"
 }

job_templates/sag_np_cell_pipe/info.conf

@@ -1,5 +1,5 @@
 {
     description = "scatter & gather workflow using numpy"
-    client_category = "client_api"
+    execution_api_type = "client_api"
     controller_type = "server"
 }

job_templates/sag_np_metrics/info.conf

@@ -1,5 +1,5 @@
 {
     description = "scatter & gather workflow using numpy"
-    client_category = "client_api"
+    execution_api_type = "client_api"
     controller_type = "server"
 }

job_templates/sag_pt/info.conf

@@ -1,5 +1,5 @@
 {
     description = "scatter & gather workflow using pytorch"
-    client_category = "client_api"
+    execution_api_type = "client_api"
     controller_type = "server"
 }

job_templates/sag_pt_deploy_map/info.conf

@@ -1,5 +1,5 @@
 {
     description = "SAG workflow with pytorch, deploy_map, site-specific configs"
-    client_category = "client_api"
+    execution_api_type = "client_api"
     controller_type = "server"
 }

job_templates/sag_pt_executor/info.conf

@@ -1,5 +1,5 @@
 {
     description = "scatter & gather workflow and cross-site evaluation with PyTorch Executor"
-    client_category = "Executor"
+    execution_api_type = "Executor"
     controller_type = "server"
 }

job_templates/sag_pt_he/info.conf

@@ -1,5 +1,5 @@
 {
     description = "scatter & gather workflow using pytorch and homomorphic encryption"
-    client_category = "client_api"
+    execution_api_type = "client_api"
     controller_type = "server"
 }

job_templates/sag_pt_mlflow/info.conf

@@ -1,5 +1,5 @@
 {
     description = "scatter & gather workflow using pytorch with MLflow tracking"
-    client_category = "client_api"
+    execution_api_type = "client_api"
     controller_type = "server"
 }

job_templates/sag_pt_model_learner/info.conf

@@ -1,5 +1,5 @@
 {
     description = "scatter & gather workflow and cross-site evaluation with PyTorch ModelLearner"
-    client_category = "ModelLearner"
+    execution_api_type = "ModelLearner"
     controller_type = "server"
 }

job_templates/sag_tf/info.conf

@@ -1,5 +1,5 @@
 {
     description = "scatter & gather workflow using TensorFlow"
-    client_category = "client_api"
+    execution_api_type = "client_api"
     controller_type = "server"
 }

job_templates/sklearn_kmeans/info.conf

@@ -1,5 +1,5 @@
 {
     description = "scikit-learn KMeans model"
-    client_category = "client_api"
+    execution_api_type = "client_api"
     controller_type = "server"
 }

job_templates/sklearn_linear/info.conf

@@ -1,5 +1,5 @@
 {
     description = "scikit-learn linear model"
-    client_category = "client_api"
+    execution_api_type = "client_api"
     controller_type = "server"
 }

job_templates/sklearn_svm/info.conf

@@ -1,5 +1,5 @@
 {
     description = "scikit-learn SVM model"
-    client_category = "client_api"
+    execution_api_type = "client_api"
     controller_type = "server"
 }

job_templates/stats_df/info.conf

@@ -1,5 +1,5 @@
 {
     description = "FedStats: tabular data with pandas"
-    client_category = "stats executor"
+    execution_api_type = "stats executor"
     controller_type = "server"
 }

job_templates/stats_image/info.conf

@@ -1,5 +1,5 @@
 {
     description = "FedStats: image intensity histogram"
-    client_category = "stats executor"
+    execution_api_type = "stats executor"
     controller_type = "server"
 }

job_templates/swarm_cse_pt/info.conf

@@ -1,5 +1,5 @@
 {
     description = "Swarm Learning with Cross-Site Evaluation with PyTorch"
-    client_category = "client_api"
+    execution_api_type = "client_api"
     controller_type = "client"
 }

job_templates/swarm_cse_pt_model_learner/info.conf

@@ -1,5 +1,5 @@
 {
     description = "Swarm Learning with Cross-Site Evaluation with PyTorch ModelLearner"
-    client_category = "ModelLearner"
+    execution_api_type = "ModelLearner"
     controller_type = "client"
 }

job_templates/vertical_xgb/info.conf

@@ -1,5 +1,5 @@
 {
     description = "vertical federated xgboost"
-    client_category = "Executor"
+    execution_api_type = "Executor"
     controller_type = "server"
 }

job_templates/xgboost_tree/info.conf

@@ -1,5 +1,5 @@
 {
     description = "xgboost horizontal tree-based collaboration model"
-    client_category = "client_api"
+    execution_api_type = "client_api"
     controller_type = "server"
 }

nvflare/tool/job/job_cli.py

@@ -41,13 +41,13 @@
     JOB_CONFIG_FILE_NAME,
     JOB_CONFIG_VAR_NAME,
     JOB_CONFIG_VAR_VALUE,
-    JOB_INFO_CLIENT_TYPE,
-    JOB_INFO_CLIENT_TYPE_KEY,
     JOB_INFO_CONF,
     JOB_INFO_CONTROLLER_TYPE,
     JOB_INFO_CONTROLLER_TYPE_KEY,
     JOB_INFO_DESC,
     JOB_INFO_DESC_KEY,
+    JOB_INFO_EXECUTION_API_TYPE,
+    JOB_INFO_EXECUTION_API_TYPE_KEY,
     JOB_INFO_KEYS,
     JOB_INFO_MD,
     JOB_META_BASE_NAME,
@@ -318,13 +318,13 @@ def display_available_templates(template_index_conf):
     print("-" * total_length)
     name_fix_length = 20
     description_fix_length = 60
-    controller_type_fix_length = 20
-    client_category_fix_length = 20
+    controller_type_fix_length = 17
+    execution_api_type_fix_length = 23
     name = fix_length_format("name", name_fix_length)
     description = fix_length_format(JOB_INFO_DESC, description_fix_length)
-    client_category = fix_length_format(JOB_INFO_CLIENT_TYPE, client_category_fix_length)
+    execution_api_type = fix_length_format(JOB_INFO_EXECUTION_API_TYPE, execution_api_type_fix_length)
     controller_type = fix_length_format(JOB_INFO_CONTROLLER_TYPE, controller_type_fix_length)
-    print(" " * left_margin, name, description, controller_type, client_category)
+    print(" " * left_margin, name, description, controller_type, execution_api_type)
     print("-" * total_length)
     for file_path in sorted(template_registry.keys()):
         name = os.path.basename(file_path)
@@ -333,9 +333,11 @@ def display_available_templates(template_index_conf):
             template_info = template_registry.get(name)
         name = fix_length_format(name, name_fix_length)
         description = fix_length_format(template_info.get(JOB_INFO_DESC_KEY), description_fix_length)
-        client_category = fix_length_format(template_info.get(JOB_INFO_CLIENT_TYPE_KEY), client_category_fix_length)
+        execution_api_type = fix_length_format(
+            template_info.get(JOB_INFO_EXECUTION_API_TYPE_KEY), execution_api_type_fix_length
+        )
         controller_type = fix_length_format(template_info.get(JOB_INFO_CONTROLLER_TYPE_KEY), controller_type_fix_length)
-        print(" " * left_margin, name, description, controller_type, client_category)
+        print(" " * left_margin, name, description, controller_type, execution_api_type)
     print("-" * total_length)