[Python API] bind ProfilingInfo (#55)

* bind ProfilingInfo

* Add tests

* Fix code style

* Add property

runtime/bindings/python/src/openvino/__init__.py

@@ -45,6 +45,7 @@
 from openvino.pyopenvino import ColorFormat
 from openvino.pyopenvino import PreProcessChannel
 from openvino.pyopenvino import Tensor
+from openvino.pyopenvino import ProfilingInfo
 
 from openvino import opset1
 from openvino import opset2

runtime/bindings/python/src/pyopenvino/core/infer_request.cpp

@@ -254,6 +254,10 @@ void regclass_InferRequest(py::module m) {
         },
         py::arg("tensor"));
 
+    cls.def("get_profiling_info", [](InferRequestWrapper& self) {
+        return self._request.get_profiling_info();
+    });
+
     cls.def_property_readonly("inputs", [](InferRequestWrapper& self) {
         return self._inputs;
     });
@@ -281,4 +285,9 @@ void regclass_InferRequest(py::module m) {
     cls.def_property_readonly("latency", [](InferRequestWrapper& self) {
         return self.get_latency();
     });
+
+    cls.def_property_readonly("profiling_info", [](InferRequestWrapper& self) {
+        return self._request.get_profiling_info();
+    });
+
 }

runtime/bindings/python/src/pyopenvino/core/profiling_info.cpp

@@ -0,0 +1,28 @@
+// Copyright (C) 2021 Intel Corporation
+// SPDX-License-Identifier: Apache-2.0
+//
+
+#include "pyopenvino/core/profiling_info.hpp"
+
+#include <pybind11/chrono.h>
+
+#include "openvino/runtime/profiling_info.hpp"
+
+namespace py = pybind11;
+
+void regclass_ProfilingInfo(py::module m) {
+    py::class_<ov::runtime::ProfilingInfo, std::shared_ptr<ov::runtime::ProfilingInfo>> cls(m, "ProfilingInfo");
+    cls.def(py::init<>())
+        .def_readwrite("status", &ov::runtime::ProfilingInfo::status)
+        .def_readwrite("real_time", &ov::runtime::ProfilingInfo::real_time)
+        .def_readwrite("cpu_time", &ov::runtime::ProfilingInfo::cpu_time)
+        .def_readwrite("node_name", &ov::runtime::ProfilingInfo::node_name)
+        .def_readwrite("exec_type", &ov::runtime::ProfilingInfo::exec_type)
+        .def_readwrite("node_type", &ov::runtime::ProfilingInfo::node_type);
+
+    py::enum_<ov::runtime::ProfilingInfo::Status>(cls, "Status")
+        .value("NOT_RUN", ov::runtime::ProfilingInfo::Status::NOT_RUN)
+        .value("OPTIMIZED_OUT", ov::runtime::ProfilingInfo::Status::OPTIMIZED_OUT)
+        .value("EXECUTED", ov::runtime::ProfilingInfo::Status::EXECUTED)
+        .export_values();
+}

runtime/bindings/python/src/pyopenvino/core/profiling_info.hpp

@@ -0,0 +1,11 @@
+// Copyright (C) 2021 Intel Corporation
+// SPDX-License-Identifier: Apache-2.0
+//
+
+#pragma once
+
+#include <pybind11/pybind11.h>
+
+namespace py = pybind11;
+
+void regclass_ProfilingInfo(py::module m);

runtime/bindings/python/src/pyopenvino/pyopenvino.cpp

@@ -33,6 +33,7 @@
 #include "pyopenvino/core/ie_preprocess_info.hpp"
 #include "pyopenvino/core/infer_request.hpp"
 #include "pyopenvino/core/offline_transformations.hpp"
+#include "pyopenvino/core/profiling_info.hpp"
 #include "pyopenvino/core/tensor.hpp"
 #include "pyopenvino/core/tensor_description.hpp"
 #include "pyopenvino/core/version.hpp"
@@ -149,6 +150,7 @@ PYBIND11_MODULE(pyopenvino, m) {
     regclass_Parameter(m);
     regclass_InputInfo(m);
     // regclass_InferQueue(m);
+    regclass_ProfilingInfo(m);
     regclass_PreProcessInfo(m);
 
     regmodule_offline_transformations(m);

runtime/bindings/python/tests/test_inference_engine/test_infer_request.py

@@ -4,9 +4,10 @@
 import numpy as np
 import os
 import pytest
+import datetime
 
 from ..conftest import image_path, model_path
-from openvino import Core, Tensor
+from openvino import Core, Tensor, ProfilingInfo
 
 is_myriad = os.environ.get("TEST_DEVICE") == "MYRIAD"
 test_net_xml, test_net_bin = model_path(is_myriad)
@@ -25,7 +26,6 @@ def read_image():
     return image
 
 
-@pytest.mark.skip(reason="ProfilingInfo has to be bound")
 def test_get_profiling_info(device):
     core = Core()
     func = core.read_model(test_net_xml, test_net_bin)
@@ -34,12 +34,13 @@ def test_get_profiling_info(device):
     img = read_image()
     request = exec_net.create_infer_request()
     request.infer({0: img})
-    pc = request.get_profiling_info()
-
-    assert pc["29"]["status"] == "EXECUTED"
-    assert pc["29"]["layer_type"] == "FullyConnected"
-    del exec_net
-    del core
+    prof_info = request.get_profiling_info()
+    soft_max_node = next(node for node in prof_info if node.node_name == "fc_out")
+    assert soft_max_node.node_type == "Softmax"
+    assert soft_max_node.status == ProfilingInfo.Status.OPTIMIZED_OUT
+    assert isinstance(soft_max_node.real_time, datetime.timedelta)
+    assert isinstance(soft_max_node.cpu_time, datetime.timedelta)
+    assert isinstance(soft_max_node.exec_type, str)
 
 
 def test_tensor_setter(device):