def test(model, model_type, image):
# Synchronous Test
counter = 0
try:
# Load IE separately to check InferRequest latency
exec_net, input_shape = load_to_IE(model, CPU_EXTENSION)
result = perform_inference(exec_net, "S", image, input_shape)
output_blob = next(iter(exec_net.outputs))
# Check for matching output shape to expected
assert result[output_blob].shape == OUTPUT_SHAPES[model_type][
output_blob]
# Check latency is > 0; i.e. a request occurred
assert exec_net.requests[0].latency > 0.0
counter += 1
except:
print("Synchronous Inference failed for {} Model.".format(model_type))
# Asynchronous Test
try:
# Load IE separately to check InferRequest latency
exec_net, input_shape = load_to_IE(model, CPU_EXTENSION)
exec_net = perform_inference(exec_net, "A", image, input_shape)
output_blob = next(iter(exec_net.outputs))
# Check for matching output shape to expected
assert exec_net.requests[0].outputs[
output_blob].shape == OUTPUT_SHAPES[model_type][output_blob]
# Check latency is > 0; i.e. a request occurred
assert exec_net.requests[0].latency > 0.0
counter += 1
except:
print("Asynchronous Inference failed for {} Model.".format(model_type))
return counter
def main():
args = get_args()
exec_net, input_shape = load_to_IE(args.m, CPU_EXTENSION)
perform_inference(exec_net, args.r, args.i, input_shape)
def main():
args = get_args()
exec_net, input_shape = load_to_IE(args.m, False)
perform_inference(exec_net, args.r, args.i, input_shape)
