def test_retrying_rpc_exception():
first_call = [ True ]
def predict_mock(request, timeout):
inputs = tf.contrib.util.make_ndarray(request.inputs['images'])
assert all([x == y for x, y in zip(inputs[0], [ 1, 2 ])])
if(first_call[0]):
first_call[0] = False
raise grpc.RpcError()
return_data = np.asarray([[ 11, 22 ]])
return_tensor = tf.contrib.util.make_tensor_proto(return_data, types_pb2.DT_FLOAT, return_data.shape)
result = mock.MagicMock()
result.outputs = { "output_alias": return_tensor }
return result
stub_mock = mock.Mock()
stub_mock.Predict = mock.MagicMock(side_effect=predict_mock)
client = PredictionClient("localhost", 50051)
client.stub = stub_mock
result = client.score_numpy_array(np.asarray([[1, 2]], dtype='f'))
assert all([x == y for x, y in zip(result[0], [ 11, 22 ])])
def test_score_numpy_array():
def predict_mock(request, timeout):
inputs = tf.contrib.util.make_ndarray(request.inputs['images'])
assert all([x == y for x, y in zip(inputs[0], [ 1, 2, 3 ])])
assert all([x == y for x, y in zip(inputs[1], [ 4, 5, 6 ])])
return_data = np.asarray([[ 11, 22, 33 ], [ 44, 55, 66 ]])
return_tensor = tf.contrib.util.make_tensor_proto(return_data, types_pb2.DT_FLOAT, return_data.shape)
result = mock.MagicMock()
result.outputs = { "output_alias": return_tensor }
return result
stub_mock = mock.Mock()
stub_mock.Predict = mock.MagicMock(side_effect=predict_mock)
client = PredictionClient("localhost", 50051)
client.stub = stub_mock
result = client.score_numpy_array(np.asarray([[1, 2, 3], [4, 5, 6]], dtype='f'))
assert all([x == y for x, y in zip(result[0], [ 11, 22, 33 ])])
assert all([x == y for x, y in zip(result[1], [ 44, 55, 66 ])])
def test_score_image():
def predict_mock(request, timeout):
inputs = request.inputs['images'].string_val
assert inputs[0].decode('utf-8') == "abc"
return_data = np.asarray([[ 1, 2, 3 ]])
return_tensor = tf.contrib.util.make_tensor_proto(return_data, types_pb2.DT_FLOAT, return_data.shape)
result = mock.MagicMock()
result.outputs = { "output_alias": return_tensor }
return result
stub_mock = mock.Mock()
stub_mock.Predict = mock.MagicMock(side_effect=predict_mock)
image_file_path = os.path.join(tempfile.mkdtemp(), "img.png")
image_file = open(image_file_path, "w")
image_file.write("abc")
image_file.close()
client = PredictionClient("localhost", 50051)
client.stub = stub_mock
result = client.score_image(image_file_path)
assert all([x == y for x, y in zip(result, [1, 2, 3])])
