Feature/run jetson e2e tests (#4)

* Run tests

* Run tests

* Run tests

* Run tests

* Added rebuild

* Added files for e2e tests

* Added rebuild

* Added rebuild

* Added biuld TensorRT flag

* Changed to use NumPy 1.x for Jetson

* Make universal invocation

* Make Cython constans

* Changed to prepare onnx

* Changed smoke-test to wait AI conversion

* Added step for model conversion

* Changed to not run step in parallel

* Push model to docker registry

* Push model to docker registry

* Push model to docker registry

src/engines/engine_factory.pyx

@@ -44,6 +44,10 @@ class EngineFactory:
     def build_and_cache(self, bytes source_bytes, LoaderHttpClient loader_client, str models_dir):
         cdef LoadResult res
         engine_bytes, engine_filename = self.build_from_source(source_bytes, loader_client, models_dir)
+        if engine_bytes is None:
+            raise RuntimeError("TensorRT conversion failed: no engine bytes produced")
+        if engine_filename is None:
+            raise RuntimeError("TensorRT conversion failed: engine filename could not be resolved")
         res = loader_client.upload_big_small_resource(engine_bytes, engine_filename, models_dir)
         if res.err is not None:
             constants_inf.log(f"Failed to upload converted model: {res.err}")
@@ -93,6 +97,22 @@ class JetsonTensorRTEngineFactory(TensorRTEngineFactory):
         from engines.jetson_tensorrt_engine import JetsonTensorRTEngine
         return JetsonTensorRTEngine(model_bytes)
 
+    def load_engine(self, LoaderHttpClient loader_client, str models_dir):
+        cdef str filename
+        cdef LoadResult res
+        from engines.tensorrt_engine import TensorRTEngine
+        for precision in ("int8", "fp16"):
+            filename = TensorRTEngine.get_engine_filename(precision)
+            if filename is None:
+                continue
+            try:
+                res = loader_client.load_big_small_resource(filename, models_dir)
+                if res.err is None:
+                    return self.create(res.data)
+            except Exception:
+                pass
+        return None
+
     def _get_ai_engine_filename(self):
         from engines.tensorrt_engine import TensorRTEngine
         return TensorRTEngine.get_engine_filename("int8")
@@ -100,5 +120,5 @@ class JetsonTensorRTEngineFactory(TensorRTEngineFactory):
     def build_from_source(self, onnx_bytes, LoaderHttpClient loader_client, str models_dir):
         from engines.jetson_tensorrt_engine import JetsonTensorRTEngine
         from engines.tensorrt_engine import TensorRTEngine
-        engine_bytes = JetsonTensorRTEngine.convert_from_source(onnx_bytes, loader_client, models_dir)
-        return engine_bytes, TensorRTEngine.get_engine_filename("int8")
+        engine_bytes, precision = JetsonTensorRTEngine.convert_from_source_with_precision(onnx_bytes, loader_client, models_dir)
+        return engine_bytes, TensorRTEngine.get_engine_filename(precision)