def run_node(onnx_node, data_inputs, **kwargs):
# type: (onnx.NodeProto, List[np.ndarray], Dict[Text, Any]) -> List[np.ndarray]
"""
Convert ONNX node to ngraph node and perform computation on input data.
:param onnx_node: ONNX NodeProto describing a computation node
:param data_inputs: list of numpy ndarrays with input data
:return: list of numpy ndarrays with computed output
"""
NgraphBackend.backend_name = pytest.config.getoption('backend', default='CPU')
if NgraphBackend.supports_ngraph_device(NgraphBackend.backend_name):
return NgraphBackend.run_node(onnx_node, data_inputs, **kwargs)
else:
raise RuntimeError('The requested nGraph backend <' + NgraphBackend.backend_name +
'> is not supported!')
def run_model(onnx_model, data_inputs):
# type: (onnx.ModelProto, List[np.ndarray]) -> List[np.ndarray]
"""
Convert ONNX model to an ngraph model and perform computation on input data.
:param onnx_model: ONNX ModelProto describing an ONNX model
:param data_inputs: list of numpy ndarrays with input data
:return: list of numpy ndarrays with computed output
"""
NgraphBackend.backend_name = BACKEND_NAME
if NgraphBackend.supports_ngraph_device(NgraphBackend.backend_name):
ng_model_function = import_onnx_model(onnx_model)
runtime = get_runtime()
computation = runtime.computation(ng_model_function)
return computation(*data_inputs)
else:
raise RuntimeError('The requested nGraph backend <'
+ NgraphBackend.backend_name + '> is not supported!')
def run_model(onnx_model, data_inputs):
# type: (onnx.ModelProto, List[np.ndarray]) -> List[np.ndarray]
"""
Convert ONNX model to an ngraph model and perform computation on input data.
:param onnx_model: ONNX ModelProto describing an ONNX model
:param data_inputs: list of numpy ndarrays with input data
:return: list of numpy ndarrays with computed output
"""
NgraphBackend.backend_name = pytest.config.getoption('backend', default='CPU')
if NgraphBackend.supports_ngraph_device(NgraphBackend.backend_name):
ng_model = import_onnx_model(onnx_model)
runtime = get_runtime()
computations = [runtime.computation(model['output'], *model['inputs']) for
model in ng_model]
return [computation(*data_inputs) for computation in computations]
else:
raise RuntimeError('The requested nGraph backend <' + NgraphBackend.backend_name +
'> is not supported!')
def test_supports_ngraph_device_gpu():
assert NgraphBackend.supports_ngraph_device('GPU')
def test_supports_ngraph_device_nnp():
assert NgraphBackend.supports_ngraph_device('NNP')
def test_supports_ngraph_device_interpreter():
assert NgraphBackend.supports_ngraph_device('INTERPRETER')
def test_supports_ngraph_device_nnp(backend_name):
assert NgraphBackend.supports_ngraph_device(backend_name)