Check e2e tests

.woodpecker/e2e-convert-jetson.yml

@@ -34,7 +34,11 @@ steps:
           echo "ERROR: fixtures/models/azaion.onnx is missing; cannot convert Jetson engine"
           exit 1
         fi
-        ls -lh fixtures/image_small.jpg fixtures/models/azaion.onnx
+        if [ ! -f fixtures/models/azaion.int8_calib.cache ]; then
+          echo "ERROR: fixtures/models/azaion.int8_calib.cache is missing; cannot verify INT8 Jetson conversion"
+          exit 1
+        fi
+        ls -lh fixtures/image_small.jpg fixtures/models/azaion.onnx fixtures/models/azaion.int8_calib.cache
 
         E2E_PROFILE=jetson \
         E2E_WAIT_FOR_ENGINE_ENABLED=1 \
@@ -42,12 +46,16 @@ steps:
         E2E_LOG_TAIL=300 \
           bash run_test.sh tests/test_health_engine.py::TestHealthEngineStep03Warmed -rs
 
+        if [ ! -f results/report.csv ]; then
+          echo "ERROR: results/report.csv is missing; cannot verify Jetson conversion warm-up result"
+          exit 1
+        fi
         if grep -qi 'skipped' results/report.csv; then
           echo "ERROR: Jetson conversion warm-up tests were skipped; no engine was produced"
           cat results/report.csv
           exit 1
         fi
 
-        bash scripts/publish_jetson_engine.sh
+        REQUIRE_INT8_ENGINE=1 bash scripts/publish_jetson_engine.sh
     volumes:
       - /var/run/docker.sock:/var/run/docker.sock

e2e/docker-compose.test.yml

@@ -65,7 +65,7 @@ services:
       - jetson
     build:
       context: ..
-      dockerfile: Dockerfile.jetson
+      dockerfile: ${JETSON_DOCKERFILE:-Dockerfile.jetson}
     runtime: nvidia
     depends_on:
       - mock-loader

e2e/scripts/publish_jetson_engine.sh

@@ -28,6 +28,15 @@ if [[ "$engine_count" == "0" ]]; then
   exit 1
 fi
 
+if [[ "${REQUIRE_INT8_ENGINE:-0}" == "1" ]]; then
+  int8_engine_count="$(find "$OUT_DIR/models" -maxdepth 1 -type f -name 'azaion*.int8.engine' | wc -l | tr -d ' ')"
+  if [[ "$int8_engine_count" == "0" ]]; then
+    echo "ERROR: INT8 engine is required, but no azaion*.int8.engine file was produced"
+    find "$OUT_DIR/models" -maxdepth 1 -type f -name 'azaion*.engine' -print -exec ls -lh {} \;
+    exit 1
+  fi
+fi
+
 echo "--- Converted TensorRT engine files:"
 find "$OUT_DIR/models" -maxdepth 1 -type f -name 'azaion*.engine' -print -exec ls -lh {} \;
 

e2e/tests/test_video.py

@@ -73,7 +73,7 @@ def video_events(warm_engine, http_client, auth_headers):
             "X-Channel-Id": channel_id,
             "X-Filename": "video_test01.mp4",
             "X-Config": json.dumps(
-                {"model_batch_size": 1, "frame_period_recognition": 100}
+                {"model_batch_size": 1, "frame_period_recognition": 4}
             ),
             "Content-Type": "application/octet-stream",
         },