[Py] Update to new pytest configuration method (#2520)

python/test/__init__.py

@@ -13,3 +13,8 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 # ******************************************************************************
+
+# test.BACKEND_NAME is a configuration variable determining which
+# nGraph backend tests will use. It's set during pytest configuration time.
+# See `pytest_configure` hook in `conftest.py` for more details.
+BACKEND_NAME = None

python/test/conftest.py

@@ -14,6 +14,7 @@
 # limitations under the License.
 # ******************************************************************************
 import pytest
+import test
 
 
 def pytest_addoption(parser):
@@ -22,13 +23,28 @@ def pytest_addoption(parser):
                      help='Select from available backends')
 
 
-def pass_method(*args, **kwargs):
-    pass
+def pytest_configure(config):
+    backend_name = config.getvalue('backend')
+    test.BACKEND_NAME = backend_name
 
 
-def pytest_configure(config):
-    config.gpu_skip = pytest.mark.skipif(config.getvalue('backend') == 'GPU')
-    config.cpu_skip = pytest.mark.skipif(config.getvalue('backend') == 'CPU')
-    config.nnp_skip = pytest.mark.skipif(config.getvalue('backend') == 'NNP')
-    config.interpreter_skip = pytest.mark.skipif(config.getvalue('backend') == 'INTERPRETER')
-    config.plaidml_skip = pytest.mark.skipif(config.getvalue('backend') == 'PlaidML')
+def pytest_collection_modifyitems(config, items):
+    backend_name = config.getvalue('backend')
+
+    gpu_skip = pytest.mark.skip(reason='Skipping test on the GPU backend.')
+    cpu_skip = pytest.mark.skip(reason='Skipping test on the CPU backend.')
+    nnp_skip = pytest.mark.skip(reason='Skipping test on the NNP backend.')
+    interpreter_skip = pytest.mark.skip(reason='Skipping test on the INTERPRETER backend.')
+    plaidml_skip = pytest.mark.skip(reason='Skipping test on the PlaidML backend.')
+
+    for item in items:
+        if backend_name == 'GPU' and 'skip_on_gpu' in item.keywords:
+            item.add_marker(gpu_skip)
+        if backend_name == 'CPU' and 'skip_on_cpu' in item.keywords:
+            item.add_marker(cpu_skip)
+        if backend_name == 'NNP' and 'skip_on_nnp' in item.keywords:
+            item.add_marker(nnp_skip)
+        if backend_name == 'INTERPRETER' and 'skip_on_interpreter' in item.keywords:
+            item.add_marker(interpreter_skip)
+        if backend_name == 'PlaidML' and 'skip_on_plaidml' in item.keywords:
+            item.add_marker(plaidml_skip)

python/test/ngraph/test_basic.py

@@ -18,14 +18,16 @@ import pytest
 import json
 
 import ngraph as ng
-from test.ngraph.util import get_runtime, run_op_node
 from ngraph.exceptions import UserInputError
 
+import test
+from test.ngraph.util import get_runtime, run_op_node
+
 
 @pytest.mark.parametrize('dtype', [np.float32, np.float64,
                                    np.int8, np.int16, np.int32, np.int64,
                                    np.uint8, np.uint16, np.uint32, np.uint64])
-@pytest.config.gpu_skip(reason='Not implemented')
+@pytest.mark.skip_on_gpu
 def test_simple_computation_on_ndarrays(dtype):
     runtime = get_runtime()
 
@@ -51,7 +53,7 @@ def test_simple_computation_on_ndarrays(dtype):
 
 def test_serialization():
     dtype = np.float32
-    backend_name = pytest.config.getoption('backend', default='CPU')
+    backend_name = test.BACKEND_NAME
 
     shape = [2, 2]
     parameter_a = ng.parameter(shape, dtype=dtype, name='A')

python/test/ngraph/test_convolution.py

@@ -21,7 +21,7 @@ import ngraph as ng
 from test.ngraph.util import get_runtime
 
 
-@pytest.config.gpu_skip(reason='Not implemented')
+@pytest.mark.skip_on_gpu
 def test_convolution_2d():
     runtime = get_runtime()
     # input_x should have shape N(batch) x C x H x W
@@ -95,7 +95,7 @@ def test_convolution_2d():
                                 dtype=np.float32))
 
 
-@pytest.config.gpu_skip(reason='Not implemented')
+@pytest.mark.skip_on_gpu
 def test_convolution_backprop_data():
     runtime = get_runtime()
 

python/test/ngraph/test_normalization.py

@@ -21,7 +21,7 @@ import ngraph as ng
 from test.ngraph.util import get_runtime
 
 
-@pytest.config.gpu_skip(reason='Not implemented')
+@pytest.mark.skip_on_gpu
 def test_lrn():
     input_image_shape = (2, 3, 2, 1)
     input_image = np.arange(int(np.prod(input_image_shape))).reshape(input_image_shape).astype('f')

python/test/ngraph/test_ops_matmul.py

@@ -38,7 +38,7 @@ from test.ngraph.util import run_op_node
     ([2, 3, 4, 5], [5, 2, 3], None, 1),
     ([2, 3, 4, 5], [4, 5, 2, 4], 2, 2),
 ])
-@pytest.config.gpu_skip(reason='under investigation, runtime error is: function failed to compile')
+@pytest.mark.skip_on_gpu  # under investigation, runtime error is: function failed to compile
 def test_dot(left_shape, right_shape, reduction_axes_count, numpy_axes):
     np.random.seed(133391)
     left_input = -100.0 + np.random.rand(*left_shape) * 200.0
@@ -49,7 +49,7 @@ def test_dot(left_shape, right_shape, reduction_axes_count, numpy_axes):
     assert np.allclose(result, expected)
 
 
-@pytest.config.gpu_skip(reason='under investigation, runtime error is: function failed to compile')
+@pytest.mark.skip_on_gpu  # under investigation, runtime error is: function failed to compile
 def test_dot_tensor_scalar():
     np.random.seed(133391)
     left_input = 10.0

python/test/ngraph/test_ops_reshape.py

@@ -20,7 +20,7 @@ import ngraph as ng
 from test.ngraph.util import get_runtime, run_op_numeric_data
 
 
-@pytest.config.gpu_skip(reason='Not implemented')
+@pytest.mark.skip_on_gpu
 def test_concat():
     a = np.array([[1, 2], [3, 4]])
     b = np.array([[5, 6]])
@@ -40,7 +40,7 @@ def test_concat():
     (bool, False),
     (bool, np.empty((2, 2), dtype=bool)),
 ])
-@pytest.config.gpu_skip(reason='under investigation, runtime error is: function failed to compile')
+@pytest.mark.skip_on_gpu  # under investigation, runtime error is: function failed to compile
 def test_constant_from_bool(val_type, value):
     expected = np.array(value, dtype=val_type)
     result = run_op_numeric_data(value, ng.constant, val_type)
@@ -59,7 +59,7 @@ def test_constant_from_bool(val_type, value):
     (np.uint32, np.uint32(123456)),
     (np.uint64, np.uint64(1234567)),
 ])
-@pytest.config.gpu_skip(reason='under investigation, runtime error is: function failed to compile')
+@pytest.mark.skip_on_gpu  # under investigation, runtime error is: function failed to compile
 def test_constant_from_scalar(val_type, value):
     expected = np.array(value, dtype=val_type)
     result = run_op_numeric_data(value, ng.constant, val_type)
@@ -70,7 +70,7 @@ def test_constant_from_scalar(val_type, value):
     np.float32,
     np.float64,
 ])
-@pytest.config.gpu_skip(reason='under investigation, runtime error is: function failed to compile')
+@pytest.mark.skip_on_gpu  # under investigation, runtime error is: function failed to compile
 def test_constant_from_float_array(val_type):
     np.random.seed(133391)
     input_data = np.array(-1 + np.random.rand(2, 3, 4) * 2, dtype=val_type)
@@ -88,7 +88,7 @@ def test_constant_from_float_array(val_type):
     (np.uint32, 0, 1024),
     (np.uint64, 0, 16383),
 ])
-@pytest.config.gpu_skip(reason='under investigation, runtime error is: function failed to compile')
+@pytest.mark.skip_on_gpu  # under investigation, runtime error is: function failed to compile
 def test_constant_from_integer_array(val_type, range_start, range_end):
     np.random.seed(133391)
     input_data = np.array(np.random.randint(range_start, range_end, size=(2, 2)), dtype=val_type)

python/test/ngraph/test_ops_unary.py

@@ -42,7 +42,7 @@ from test.ngraph.util import run_op_numeric_data, run_op_node
     (ng.tan, np.tan, -1., 1.),
     (ng.tanh, np.tanh, -100., 100.),
 ])
-@pytest.config.gpu_skip(reason='under investigation, runtime error is: function failed to compile')
+@pytest.mark.skip_on_gpu  # under investigation, runtime error is: function failed to compile
 def test_unary_op_array(ng_api_fn, numpy_fn, range_start, range_end):
     np.random.seed(133391)
     input_data = range_start + np.random.rand(2, 3, 4) * (range_end - range_start)
@@ -77,7 +77,7 @@ def test_unary_op_array(ng_api_fn, numpy_fn, range_start, range_end):
     (ng.tan, np.tan, np.float32(np.pi / 4.0)),
     (ng.tanh, np.tanh, np.float32(0.1234)),
 ])
-@pytest.config.gpu_skip(reason='under investigation, runtime error is: function failed to compile')
+@pytest.mark.skip_on_gpu  # under investigation, runtime error is: function failed to compile
 def test_unary_op_scalar(ng_api_fn, numpy_fn, input_data):
     expected = numpy_fn(input_data)
 

python/test/ngraph/test_pooling.py

@@ -25,7 +25,7 @@ def _ndarray_1x1x4x4():
     return np.arange(11, 27, dtype=np.float32).reshape(1, 1, 4, 4)
 
 
-@pytest.config.gpu_skip(reason='Not implemented')
+@pytest.mark.skip_on_gpu
 def test_avg_pool_2d(_ndarray_1x1x4x4):
     runtime = get_runtime()
     input_data = _ndarray_1x1x4x4
@@ -74,7 +74,7 @@ def test_avg_pool_2d(_ndarray_1x1x4x4):
     assert np.allclose(result, expected)
 
 
-@pytest.config.gpu_skip(reason='Not implemented')
+@pytest.mark.skip_on_gpu
 def test_avg_pooling_3d(_ndarray_1x1x4x4):
     rt = get_runtime()
     data = _ndarray_1x1x4x4

python/test/ngraph/test_reduction.py

@@ -34,7 +34,7 @@ from test.ngraph.util import run_op_node, get_runtime
     (ng.sum, np.sum, (0, 2)),
     (ng.prod, np.prod, (0, 2)),
 ])
-@pytest.config.gpu_skip(reason='Not implemented')
+@pytest.mark.skip_on_gpu
 def test_reduction_ops(ng_api_helper, numpy_function, reduction_axes):
     shape = [2, 4, 3, 2]
     np.random.seed(133391)
@@ -45,7 +45,7 @@ def test_reduction_ops(ng_api_helper, numpy_function, reduction_axes):
     assert np.allclose(result, expected)
 
 
-@pytest.config.gpu_skip(reason='Not implemented')
+@pytest.mark.skip_on_gpu
 def test_argmax():
     runtime = get_runtime()
     input_x = ng.constant(np.array([[9, 2, 10],
@@ -58,7 +58,7 @@ def test_argmax():
                        np.array([1, 3, 0], dtype=np.int32))
 
 
-@pytest.config.gpu_skip(reason='Not implemented')
+@pytest.mark.skip_on_gpu
 def test_argmin():
     runtime = get_runtime()
     input_x = ng.constant(np.array([[12, 2, 10],
@@ -71,7 +71,7 @@ def test_argmin():
                        np.array([3, 2, 1], dtype=np.int32))
 
 
-@pytest.config.gpu_skip(reason='Not implemented')
+@pytest.mark.skip_on_gpu
 def test_topk():
     runtime = get_runtime()
     input_x = ng.constant(np.array([[9, 2, 10],

python/test/ngraph/util.py

@@ -15,11 +15,12 @@
 # ******************************************************************************
 
 import numpy as np
-import pytest
 import ngraph as ng
 
 from string import ascii_uppercase
 
+import test
+
 
 def _get_numpy_dtype(scalar):
     return np.array([scalar]).dtype
@@ -27,8 +28,7 @@ def _get_numpy_dtype(scalar):
 
 def get_runtime():
     """Return runtime object."""
-    backend_name = pytest.config.getoption('backend', default='CPU')
-    return ng.runtime(backend_name=backend_name)
+    return ng.runtime(backend_name=test.BACKEND_NAME)
 
 
 def run_op_node(input_data, op_fun, *args):