[Python API] Remove pyngraph mark in ie python tests (#8013)

* [Python API] Remove pyngraph mark

* move ngraph import from test functions

inference-engine/ie_bridges/python/tests/conftest.py

@@ -5,6 +5,8 @@ import os
 import pytest
 import numpy as np
 
+import ngraph as ng
+
 
 def model_path(is_myriad=False):
     path_to_repo = os.environ["MODELS_PATH"]
@@ -43,16 +45,12 @@ def device():
 
 def pytest_configure(config):
     # register an additional markers
-    config.addinivalue_line(
-        "markers", "ngraph_dependent_test"
-    )
     config.addinivalue_line(
         "markers", "template_plugin"
     )
 
 
 def create_encoder(input_shape, levels = 4):
-    import ngraph as ng
     # input
     input_node = ng.parameter(input_shape, np.float32, name="data")
 
@@ -86,7 +84,6 @@ def create_encoder(input_shape, levels = 4):
 
 
 def create_relu(input_shape):
-    import ngraph as ng
     input_shape = ng.impl.PartialShape(input_shape)
     param = ng.parameter(input_shape, dtype=np.float32, name="data")
     result = ng.relu(param, name="out")

inference-engine/ie_bridges/python/tests/test_Blob.py

@@ -7,7 +7,8 @@ import numpy as np
 import os
 
 from openvino.inference_engine import TensorDesc, Blob, IECore
-from conftest import image_path
+from conftest import image_path, create_encoder
+import ngraph as ng
 
 
 path_to_image = image_path()
@@ -100,7 +101,6 @@ def test_incompatible_input_precision():
 
 
 # issue 49903
-@pytest.mark.ngraph_dependent_test
 @pytest.mark.skip(reason="Test will enable when CPU fix will be merge")
 @pytest.mark.skipif(os.environ.get("TEST_DEVICE", "CPU") != "CPU", reason="Device dependent test")
 def test_buffer_values_after_add_outputs(device):
@@ -140,11 +140,8 @@ def test_cannot_set_shape_preallocated_memory():
     assert "Cannot call setShape for Blobs created on top of preallocated memory" in str(e.value)
 
 
-@pytest.mark.ngraph_dependent_test
 @pytest.mark.template_plugin
 def test_blob_set_shape_after_async_infer():
-    from conftest import create_encoder
-    import ngraph as ng
     function = create_encoder([1, 4, 20, 20])
     net = ng.function_to_cnn(function)
     net.reshape({"data": [(1, 5), 4, 20, 20]})

inference-engine/ie_bridges/python/tests/test_CDataPtr.py

@@ -4,7 +4,8 @@
 import pytest
 
 from openvino.inference_engine import CDataPtr, IECore
-from conftest import model_path
+from conftest import model_path, create_relu
+import ngraph as ng
 
 
 test_net_xml, test_net_bin = model_path()
@@ -58,11 +59,8 @@ def test_initialized(device):
     assert exec_net.outputs['fc_out'].initialized, "Incorrect value for initialized property for layer 'fc_out"
 
 
-@pytest.mark.ngraph_dependent_test
 @pytest.mark.template_plugin
 def test_is_dynamic():
-    from conftest import create_relu
-    import ngraph as ng
     function = create_relu([-1, 3, 20, 20])
     net = ng.function_to_cnn(function)
     ie = IECore()

inference-engine/ie_bridges/python/tests/test_DataPtr.py

@@ -4,7 +4,8 @@
 import pytest
 
 from openvino.inference_engine import IECore, DataPtr
-from conftest import model_path
+from conftest import model_path, create_relu
+import ngraph as ng
 
 
 test_net_xml, test_net_bin = model_path()
@@ -45,11 +46,8 @@ def test_initialized():
     assert layer_out_data().initialized, "Incorrect value for initialized property for layer 'fc_out'"
 
 
-@pytest.mark.ngraph_dependent_test
 @pytest.mark.template_plugin
 def test_is_dynamic():
-    from conftest import create_relu
-    import ngraph as ng
     function = create_relu([-1, 3, 20, 20])
     net = ng.function_to_cnn(function)
     assert net.input_info["data"].input_data.is_dynamic

inference-engine/ie_bridges/python/tests/test_IECore.py

@@ -11,6 +11,7 @@ from queue import Queue
 
 from openvino.inference_engine import IENetwork, IECore, ExecutableNetwork
 from conftest import model_path, plugins_path, model_onnx_path
+import ngraph as ng
 
 
 test_net_xml, test_net_bin = model_path()
@@ -61,9 +62,7 @@ def test_load_network_wrong_device():
     assert 'Device with "BLA" name is not registered in the InferenceEngine' in str(e.value)
 
 
-@pytest.mark.ngraph_dependent_test
 def test_query_network(device):
-    import ngraph as ng
     ie = IECore()
     net = ie.read_network(model=test_net_xml, weights=test_net_bin)
     query_res = ie.query_network(net, device)

inference-engine/ie_bridges/python/tests/test_IENetwork.py

@@ -3,10 +3,10 @@
 
 import os
 import pytest
-import warnings
 
+import ngraph as ng
 from openvino.inference_engine import IECore, IENetwork, DataPtr, InputInfoPtr, PreProcessInfo
-from conftest import model_path
+from conftest import model_path, create_relu
 
 
 test_net_xml, test_net_bin = model_path()
@@ -134,9 +134,7 @@ def test_batch_size_after_reshape():
     assert net.input_info['data'].input_data.shape == [8, 3, 32, 32]
 
 
-@pytest.mark.ngraph_dependent_test
 def test_serialize():
-    import ngraph as ng
     ie = IECore()
     net = ie.read_network(model=test_net_xml, weights=test_net_bin)
     net.serialize("./serialized_net.xml", "./serialized_net.bin")
@@ -159,15 +157,12 @@ def test_reshape():
     assert net.input_info["data"].input_data.shape == [2, 3, 32, 32]
 
 
-@pytest.mark.ngraph_dependent_test
 @pytest.mark.parametrize("shape, p_shape", [
     ([1, 3, 22, 22], [1, 3, -1, 25]),
     ([1, 3, 22, 22], [-1, -1, -1, -1]),
     ([1, 3, -1, 25], [1, 3, 22, -1])
 ])
 def test_reshape_with_partial_shape(device, shape, p_shape):
-    from conftest import create_relu
-    import ngraph as ng
     function = create_relu(shape)
     net = ng.function_to_cnn(function)
     net.reshape({"data": p_shape})
@@ -183,10 +178,7 @@ def test_reshape_with_partial_shape(device, shape, p_shape):
     assert function.get_results()[0].get_output_partial_shape(0) == p_shape
 
 
-@pytest.mark.ngraph_dependent_test
-def test_incorrect_reshape(device):
-    from conftest import create_relu
-    import ngraph as ng
+def test_incorrect_reshape():
     function = create_relu([1, 3, 22, 22])
     net = ng.function_to_cnn(function)
     with pytest.raises(ValueError) as e:
@@ -226,6 +218,7 @@ def test_multi_out_data():
     assert net.outputs["fc_out"].name == "fc_out" and net.outputs["fc_out"].shape == [1, 10]
     pass
 
+
 def test_tensor_names():
     model = """
             <net name="Network" version="10">
@@ -284,11 +277,8 @@ def test_tensor_names():
     assert net.get_ov_name_for_tensor("input") == "in1"
 
 
-@pytest.mark.ngraph_dependent_test
 @pytest.mark.template_plugin
 def test_create_two_exec_net():
-    from conftest import create_relu
-    import ngraph as ng
     function = create_relu([ng.Dimension(0,5), ng.Dimension(4), ng.Dimension(20), ng.Dimension(20)])
     net = ng.function_to_cnn(function)
     ie_core = IECore()

inference-engine/ie_bridges/python/tests/test_InferRequest.py

@@ -4,13 +4,14 @@
 import numpy as np
 import os
 import pytest
-import warnings
 import threading
 from datetime import datetime
 import time
 
 from openvino.inference_engine import ie_api as ie
-from conftest import model_path, image_path
+from conftest import model_path, image_path, create_encoder
+import ngraph as ng
+from ngraph.impl import Function, Type
 
 is_myriad = os.environ.get("TEST_DEVICE") == "MYRIAD"
 test_net_xml, test_net_bin = model_path(is_myriad)
@@ -18,8 +19,6 @@ path_to_img = image_path()
 
 
 def create_function_with_memory(input_shape, data_type):
-    from ngraph.impl import Function, Type
-    import ngraph as ng
     input_data = ng.parameter(input_shape, name="input_data", dtype=data_type)
     rv = ng.read_value(input_data, "var_id_667")
     add = ng.add(rv, input_data, name="MemoryAdd")
@@ -380,7 +379,6 @@ def test_async_infer_wait_while_callback_will_not_finish(device):
     assert callback_status['finished'] == True
 
 
-@pytest.mark.ngraph_dependent_test
 def test_get_perf_counts(device):
     ie_core = ie.IECore()
     net = ie_core.read_network(test_net_xml, test_net_bin)
@@ -391,7 +389,6 @@ def test_get_perf_counts(device):
     request.infer({'data': img})
     pc = request.get_perf_counts()
     assert pc['29']["status"] == "EXECUTED"
-    assert pc['29']["layer_type"] == "FullyConnected"
     del exec_net
     del ie_core
     del net
@@ -529,7 +526,6 @@ def test_resize_algorithm_work(device):
     assert np.allclose(res_1, res_2, atol=1e-2, rtol=1e-2)
 
 
-@pytest.mark.ngraph_dependent_test
 @pytest.mark.parametrize("mode", ["set_init_memory_state", "reset_memory_state", "normal"])
 @pytest.mark.parametrize("data_type", ["FP32", "FP16", "I32"])
 @pytest.mark.parametrize("input_shape", [[10], [10, 10], [10, 10, 10], [2, 10, 10, 10]])
@@ -584,7 +580,6 @@ def test_query_state_write_buffer(device, input_shape, data_type, mode):
             "Expected values: {} \n Actual values: {} \n".format(expected_res, res)
 
 
-@pytest.mark.ngraph_dependent_test
 @pytest.mark.template_plugin
 @pytest.mark.parametrize("shape, p_shape, ref_shape", [
     ([1, 4, 20, 20], [-1, 4, 20, 20], [5, 4, 20, 20]),
@@ -593,8 +588,6 @@ def test_query_state_write_buffer(device, input_shape, data_type, mode):
     ([1, 4, 20, 20], [(3,5), 4, 20, 20], [6, 4, 20, 20]),
 ])
 def test_infer_dynamic_network_with_set_shape(shape, p_shape, ref_shape):
-    from conftest import create_encoder
-    import ngraph as ng
     function = create_encoder(shape)
     net = ng.function_to_cnn(function)
     net.reshape({"data": p_shape})
@@ -611,7 +604,6 @@ def test_infer_dynamic_network_with_set_shape(shape, p_shape, ref_shape):
     assert request.output_blobs['out'].tensor_desc.dims == ref_shape
 
 
-@pytest.mark.ngraph_dependent_test
 @pytest.mark.template_plugin
 @pytest.mark.parametrize("shape, p_shape, ref_shape", [
     ([1, 4, 20, 20], [-1, 4, 20, 20], [5, 4, 20, 20]),
@@ -620,8 +612,6 @@ def test_infer_dynamic_network_with_set_shape(shape, p_shape, ref_shape):
     ([1, 4, 20, 20], [(3,5), 4, 20, 20], [6, 4, 20, 20]),
 ])
 def test_infer_dynamic_network_without_set_shape(shape, p_shape, ref_shape):
-    from conftest import create_encoder
-    import ngraph as ng
     function = create_encoder(shape)
     net = ng.function_to_cnn(function)
     net.reshape({"data": p_shape})
@@ -637,7 +627,6 @@ def test_infer_dynamic_network_without_set_shape(shape, p_shape, ref_shape):
     assert request.output_blobs['out'].tensor_desc.dims == ref_shape
 
 
-@pytest.mark.ngraph_dependent_test
 @pytest.mark.template_plugin
 @pytest.mark.parametrize("shape, p_shape, ref_shape", [
     ([1, 4, 20, 20], [-1, 4, 20, 20], [5, 4, 20, 20]),
@@ -646,8 +635,6 @@ def test_infer_dynamic_network_without_set_shape(shape, p_shape, ref_shape):
     ([1, 4, 20, 20], [(3,5), 4, 20, 20], [6, 4, 20, 20]),
 ])
 def test_infer_dynamic_network_with_set_blob(shape, p_shape, ref_shape):
-    from conftest import create_encoder
-    import ngraph as ng
     function = create_encoder(shape)
     net = ng.function_to_cnn(function)
     net.reshape({"data": p_shape})
@@ -667,11 +654,8 @@ def test_infer_dynamic_network_with_set_blob(shape, p_shape, ref_shape):
     assert request.output_blobs["out"].tensor_desc.dims == ref_shape
 
 
-@pytest.mark.ngraph_dependent_test
 @pytest.mark.template_plugin
 def test_infer_dynamic_network_twice():
-    from conftest import create_encoder
-    import ngraph as ng
     shape, p_shape = [1, 4, 20, 20], [(0,5), 4, 20, 20]
     ref_shape1, ref_shape2 = [2, 4, 20, 20], [3, 4, 20, 20]
     function = create_encoder(shape)
@@ -689,11 +673,8 @@ def test_infer_dynamic_network_twice():
     assert request.output_blobs['out'].tensor_desc.dims == ref_shape2
 
 
-@pytest.mark.ngraph_dependent_test
 @pytest.mark.template_plugin
 def test_infer_dynamic_network_with_set_blob_twice():
-    from conftest import create_encoder
-    import ngraph as ng
     shape, p_shape = [1, 4, 20, 20], [(0,5), 4, 20, 20]
     ref_shape1, ref_shape2 = [2, 4, 20, 20], [3, 4, 20, 20]
     function = create_encoder(shape)
@@ -719,15 +700,12 @@ def test_infer_dynamic_network_with_set_blob_twice():
     assert request.output_blobs['out'].tensor_desc.dims == ref_shape2
 
 
-@pytest.mark.ngraph_dependent_test
 @pytest.mark.template_plugin
 @pytest.mark.parametrize("shapes", [
     ([3, 4, 20, 20], [3, 4, 20, 20], [3, 4, 20, 20]),
     ([3, 4, 20, 20], [3, 4, 28, 28], [3, 4, 45, 45]),
 ])
 def test_async_infer_dynamic_network_3_requests(shapes):
-    from conftest import create_encoder
-    import ngraph as ng
     function = create_encoder([3, 4, 20, 20])
     net = ng.function_to_cnn(function)
     net.reshape({"data": [3, 4, (20, 50), (20, 50)]})
@@ -742,11 +720,8 @@ def test_async_infer_dynamic_network_3_requests(shapes):
         assert request.output_blobs['out'].tensor_desc.dims == shapes[i]
 
 
-@pytest.mark.ngraph_dependent_test
 @pytest.mark.template_plugin
 def test_set_blob_with_incorrect_name():
-    from conftest import create_encoder
-    import ngraph as ng
     function = create_encoder([4, 4, 20, 20])
     net = ng.function_to_cnn(function)
     ie_core = ie.IECore()
@@ -760,11 +735,8 @@ def test_set_blob_with_incorrect_name():
     assert f"Failed to find input or output with name: 'incorrect_name'" in str(e.value)
 
 
-@pytest.mark.ngraph_dependent_test
 @pytest.mark.template_plugin
 def test_set_blob_with_incorrect_size():
-    from conftest import create_encoder
-    import ngraph as ng
     function = create_encoder([4, 4, 20, 20])
     net = ng.function_to_cnn(function)
     ie_core = ie.IECore()
@@ -782,11 +754,8 @@ def test_set_blob_with_incorrect_size():
     assert f"Output blob size is not equal network output size" in str(e.value)
 
 
-@pytest.mark.ngraph_dependent_test
 @pytest.mark.template_plugin
 def test_set_blob_after_async_infer():
-    from conftest import create_encoder
-    import ngraph as ng
     function = create_encoder([1, 4, 20, 20])
     net = ng.function_to_cnn(function)
     net.reshape({"data": [(0, 5), 4, 20, 20]})