TaskRunner E2E: Parameterised input and coverity fix

.github/workflows/task_runner_basic_e2e.yml

@@ -18,26 +18,116 @@ on:
         required: false
         default: "2"
         type: string
+      model_name:
+        description: "Model name"
+        required: false
+        default: "all"
+        type: choice
+        options:
+          - all
+          - torch_cnn_mnist
+          - keras_cnn_mnist
+      python_version:
+        description: "Python version"
+        required: false
+        default: "all"
+        type: choice
+        options:
+          - all
+          - "3.10"
+          - "3.11"
+          - "3.12"
+      jobs_to_run:
+        description: "Jobs to run"
+        type: choice
+        default: "all"
+        options:
+          - all
+          - test_with_tls
+          - test_with_non_tls
+          - test_with_no_client_auth
+          - test_memory_logs
+        required: false
 
 permissions:
   contents: read
 
 # Environment variables common for all the jobs
+# DO NOT use double quotes for the values of the environment variables
 env:
-  NUM_ROUNDS: ${{ inputs.num_rounds || '5' }}
-  NUM_COLLABORATORS: ${{ inputs.num_collaborators || '2' }}
+  NUM_ROUNDS: ${{ inputs.num_rounds || 5 }}
+  NUM_COLLABORATORS: ${{ inputs.num_collaborators || 2 }}
+  MODEL_NAME: ${{ inputs.model_name || 'all' }}
+  PYTHON_VERSION: ${{ inputs.python_version || 'all' }}
+  JOBS_TO_RUN: ${{ inputs.jobs_to_run || 'all' }}
 
 jobs:
+  input_selection:
+    if: |
+      (github.event_name == 'schedule' && github.repository_owner == 'securefederatedai') ||
+      (github.event_name == 'workflow_dispatch')
+    name: Input value selection
+    runs-on: ubuntu-22.04
+    outputs:
+      # Output all the variables related to models and python versions to be used in the matrix strategy
+      # for different jobs, however their usage depends on the selected job.
+      selected_jobs: ${{ steps.input_selection.outputs.jobs_to_run }}
+      selected_models_for_tls: ${{ steps.input_selection.outputs.models_for_tls }}
+      selected_python_for_tls: ${{ steps.input_selection.outputs.python_for_tls }}
+      selected_models_for_non_tls: ${{ steps.input_selection.outputs.models_for_non_tls }}
+      selected_models_for_no_client_auth: ${{ steps.input_selection.outputs.models_for_no_client_auth }}
+      selected_models_for_memory_logs: ${{ steps.input_selection.outputs.models_for_memory_logs }}
+      selected_python_for_non_tls: ${{ steps.input_selection.outputs.python_for_non_tls }}
+      selected_python_for_no_client_auth: ${{ steps.input_selection.outputs.python_for_no_client_auth }}
+      selected_python_for_memory_logs: ${{ steps.input_selection.outputs.python_for_memory_logs }}
+    steps:
+      - name: Job to select input values
+        id: input_selection
+        run: |
+          # ---------------------------------------------------------------
+          # Models like XGBoost (xgb_higgs) and torch_cnn_histology require runners with higher memory and CPU to run.
+          # Thus these models are excluded from the matrix for now.
+          # Default combination if no input is provided (i.e. 'all' is selected).
+          # * TLS - models [torch_cnn_mnist, keras_cnn_mnist] and python versions [3.10, 3.11, 3.12]
+          # * Non-TLS - models [torch_cnn_mnist] and python version [3.10]
+          # * No client auth - models [keras_cnn_mnist] and python version [3.10]
+          # * Memory logs - models [torch_cnn_mnist] and python version [3.10]
+          # ---------------------------------------------------------------
+          echo "jobs_to_run=${{ env.JOBS_TO_RUN }}" >> "$GITHUB_OUTPUT"
+
+          if [ "${{ env.MODEL_NAME }}" == "all" ]; then
+            echo "models_for_tls=[\"torch_cnn_mnist\", \"keras_cnn_mnist\"]" >> "$GITHUB_OUTPUT"
+            echo "models_for_non_tls=[\"torch_cnn_mnist\"]" >> "$GITHUB_OUTPUT"
+            echo "models_for_no_client_auth=[\"keras_cnn_mnist\"]" >> "$GITHUB_OUTPUT"
+            echo "models_for_memory_logs=[\"torch_cnn_mnist\"]" >> "$GITHUB_OUTPUT"
+          else
+            echo "models_for_tls=[\"${{env.MODEL_NAME}}\"]" >> "$GITHUB_OUTPUT"
+            echo "models_for_non_tls=[\"${{env.MODEL_NAME}}\"]" >> "$GITHUB_OUTPUT"
+            echo "models_for_no_client_auth=[\"${{env.MODEL_NAME}}\"]" >> "$GITHUB_OUTPUT"
+            echo "models_for_memory_logs=[\"${{env.MODEL_NAME}}\"]" >> "$GITHUB_OUTPUT"
+          fi
+          if [ "${{ env.PYTHON_VERSION }}" == "all" ]; then
+            echo "python_for_tls=[\"3.10\", \"3.11\", \"3.12\"]" >> "$GITHUB_OUTPUT"
+            echo "python_for_non_tls=[\"3.10\"]" >> "$GITHUB_OUTPUT"
+            echo "python_for_no_client_auth=[\"3.10\"]" >> "$GITHUB_OUTPUT"
+            echo "python_for_memory_logs=[\"3.10\"]" >> "$GITHUB_OUTPUT"
+          else
+            echo "python_for_tls=[\"${{env.PYTHON_VERSION}}\"]" >> "$GITHUB_OUTPUT"
+            echo "python_for_non_tls=[\"${{env.PYTHON_VERSION}}\"]" >> "$GITHUB_OUTPUT"
+            echo "python_for_no_client_auth=[\"${{env.PYTHON_VERSION}}\"]" >> "$GITHUB_OUTPUT"
+            echo "python_for_memory_logs=[\"${{env.PYTHON_VERSION}}\"]" >> "$GITHUB_OUTPUT"
+          fi
+
   test_with_tls:
-    name: tr_tls
+    name: Test with TLS
+    needs: input_selection
+    if: needs.input_selection.outputs.selected_jobs == 'all' || needs.input_selection.outputs.selected_jobs == 'test_with_tls'
     runs-on: ubuntu-22.04
     timeout-minutes: 30
     strategy:
       matrix:
-        # Models like XGBoost (xgb_higgs) and torch_cnn_histology require runners with higher memory and CPU to run.
-        # Thus these models are excluded from the matrix for now.
-        model_name: ["torch_cnn_mnist", "keras_cnn_mnist"]
-        python_version: ["3.10", "3.11", "3.12"]
+        model_name: ${{ fromJson(needs.input_selection.outputs.selected_models_for_tls) }}
+        python_version: ${{ fromJson(needs.input_selection.outputs.selected_python_for_tls) }}
       fail-fast: false # do not immediately fail if one of the combinations fail
 
     env:
@@ -72,15 +162,15 @@ jobs:
           test_type: "tr_tls"
 
   test_with_non_tls:
-    name: tr_non_tls
+    name: Test without TLS
+    needs: input_selection
+    if: needs.input_selection.outputs.selected_jobs == 'all' || needs.input_selection.outputs.selected_jobs == 'test_with_non_tls'
     runs-on: ubuntu-22.04
     timeout-minutes: 30
     strategy:
       matrix:
-        # Testing this scenario only for torch_cnn_mnist model and python 3.10
-        # If required, this can be extended to other models and python versions
-        model_name: ["torch_cnn_mnist"]
-        python_version: ["3.10"]
+        model_name: ${{ fromJson(needs.input_selection.outputs.selected_models_for_non_tls) }}
+        python_version: ${{ fromJson(needs.input_selection.outputs.selected_python_for_non_tls) }}
       fail-fast: false # do not immediately fail if one of the combinations fail
 
     env:
@@ -115,15 +205,15 @@ jobs:
           test_type: "tr_non_tls"
 
   test_with_no_client_auth:
-    name: tr_no_client_auth
+    name: Test without client auth
+    needs: input_selection
+    if: needs.input_selection.outputs.selected_jobs == 'all' || needs.input_selection.outputs.selected_jobs == 'test_with_no_client_auth'
     runs-on: ubuntu-22.04
     timeout-minutes: 30
     strategy:
       matrix:
-        # Testing this scenario for keras_cnn_mnist model and python 3.10
-        # If required, this can be extended to other models and python versions
-        model_name: ["keras_cnn_mnist"]
-        python_version: ["3.10"]
+        model_name: ${{ fromJson(needs.input_selection.outputs.selected_models_for_no_client_auth) }}
+        python_version: ${{ fromJson(needs.input_selection.outputs.selected_python_for_no_client_auth) }}
       fail-fast: false # do not immediately fail if one of the combinations fail
 
     env:
@@ -155,18 +245,18 @@ jobs:
         uses: ./.github/actions/tr_post_test_run
         if: ${{ always() }}
         with:
-          test_type: "tr_no_client_auth"
+          test_type: 'tr_no_client_auth'
 
   test_memory_logs:
-    name: tr_tls_memory_logs
+    name: Test memory usage
+    needs: input_selection
+    if: needs.input_selection.outputs.selected_jobs == 'all' || needs.input_selection.outputs.selected_jobs == 'test_memory_logs'
     runs-on: ubuntu-22.04
     timeout-minutes: 30
     strategy:
       matrix:
-        # Testing this scenario only for torch_cnn_mnist model and python 3.10
-        # If required, this can be extended to other models and python versions
-        model_name: ["torch_cnn_mnist"]
-        python_version: ["3.10"]
+        model_name: ${{ fromJson(needs.input_selection.outputs.selected_models_for_memory_logs) }}
+        python_version: ${{ fromJson(needs.input_selection.outputs.selected_python_for_memory_logs) }}
       fail-fast: false # do not immediately fail if one of the combinations fail
 
     env:

tests/end_to_end/utils/summary_helper.py

@@ -42,9 +42,13 @@ def get_aggregated_accuracy(agg_log_file):
         return agg_accuracy
 
     agg_accuracy_dict = convert_to_json(agg_log_file)
-    agg_accuracy = agg_accuracy_dict[-1].get(
-        "aggregator/aggregated_model_validation/accuracy", "Not Found"
-    )
+
+    if not agg_accuracy_dict:
+        print(f"Aggregator log file {agg_log_file} is empty. Cannot get aggregated accuracy, returning 'Not Found'")
+    else:
+        agg_accuracy = agg_accuracy_dict[-1].get(
+            "aggregator/aggregated_model_validation/accuracy", "Not Found"
+        )
     return agg_accuracy
 
 
@@ -104,7 +108,7 @@ def get_testcase_result():
 
 def print_task_runner_score():
     """
-    Main function to get the test case results and aggregator logs
+    Function to get the test case results and aggregator logs
     And write the results to GitHub step summary
     IMP: Do not fail the test in any scenario
     """
@@ -129,7 +133,7 @@ def print_task_runner_score():
     num_cols = os.getenv("NUM_COLLABORATORS")
     num_rounds = os.getenv("NUM_ROUNDS")
     model_name = os.getenv("MODEL_NAME")
-    summary_file = os.getenv("GITHUB_STEP_SUMMARY")
+    summary_file = _get_summary_file()
 
     # Validate the model name and create the workspace name
     if not model_name.upper() in constants.ModelName._member_names_:
@@ -169,8 +173,12 @@ def print_task_runner_score():
 
 
 def print_federated_runtime_score():
-    summary_file = os.getenv("GITHUB_STEP_SUMMARY")
-
+    """
+    Function to get the federated runtime score from the director log file
+    And write the results to GitHub step summary
+    IMP: Do not fail the test in any scenario
+    """
+    summary_file = _get_summary_file()
     search_string = "Aggregated model validation score"
 
     last_occurrence = aggregated_model_score = None
@@ -210,6 +218,23 @@ def print_federated_runtime_score():
         print(f"| {aggregated_model_score} |", file=fh)
 
 
+def _get_summary_file():
+    """
+    Function to get the summary file path
+    Returns:
+        summary_file: Path to the summary file
+    """
+    summary_file = os.getenv("GITHUB_STEP_SUMMARY")
+    print(f"Summary file: {summary_file}")
+
+    # Check if the fetched summary file is valid
+    if summary_file and os.path.isfile(summary_file):
+        return summary_file
+    else:
+        print("Invalid summary file. Exiting...")
+        exit(1)
+
+
 def fetch_args():
     """
     Function to fetch the commandline arguments.