/* ---------------------------------------------------------------------*//**
 *
 * Licensed to the Apache Software Foundation (ASF) under one
 * or more contributor license agreements.  See the NOTICE file
 * distributed with this work for additional information
 * regarding copyright ownership.  The ASF licenses this file
 * to you under the Apache License, Version 2.0 (the
 * "License"); you may not use this file except in compliance
 * with the License.  You may obtain a copy of the License at
 *
 *   http://www.apache.org/licenses/LICENSE-2.0
 *
 * Unless required by applicable law or agreed to in writing,
 * software distributed under the License is distributed on an
 * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
 * KIND, either express or implied.  See the License for the
 * specific language governing permissions and limitations
 * under the License.
 *
 *//* ---------------------------------------------------------------------*/

-------------------- IRIS test input tables -----------------

DROP TABLE IF EXISTS iris_data;
CREATE TABLE iris_data(
    id serial,
    attributes numeric[],
    class_text varchar
);
INSERT INTO iris_data(id, attributes, class_text) VALUES
(1,ARRAY[5.1,3.5,1.4,0.2],'Iris-setosa'),
(2,ARRAY[4.9,3.0,1.4,0.2],'Iris-setosa'),
(3,ARRAY[4.7,3.2,1.3,0.2],'Iris-setosa'),
(4,ARRAY[4.6,3.1,1.5,0.2],'Iris-setosa'),
(5,ARRAY[5.0,3.6,1.4,0.2],'Iris-setosa'),
(6,ARRAY[5.4,3.9,1.7,0.4],'Iris-setosa'),
(7,ARRAY[4.6,3.4,1.4,0.3],'Iris-setosa'),
(8,ARRAY[5.0,3.4,1.5,0.2],'Iris-setosa'),
(9,ARRAY[4.4,2.9,1.4,0.2],'Iris-setosa'),
(10,ARRAY[4.9,3.1,1.5,0.1],'Iris-setosa'),
(11,ARRAY[5.4,3.7,1.5,0.2],'Iris-setosa'),
(12,ARRAY[4.8,3.4,1.6,0.2],'Iris-setosa'),
(13,ARRAY[4.8,3.0,1.4,0.1],'Iris-setosa'),
(14,ARRAY[4.3,3.0,1.1,0.1],'Iris-setosa'),
(15,ARRAY[5.8,4.0,1.2,0.2],'Iris-setosa'),
(16,ARRAY[5.7,4.4,1.5,0.4],'Iris-setosa'),
(17,ARRAY[5.4,3.9,1.3,0.4],'Iris-setosa'),
(18,ARRAY[5.1,3.5,1.4,0.3],'Iris-setosa'),
(19,ARRAY[5.7,3.8,1.7,0.3],'Iris-setosa'),
(20,ARRAY[5.1,3.8,1.5,0.3],'Iris-setosa'),
(21,ARRAY[5.4,3.4,1.7,0.2],'Iris-setosa'),
(22,ARRAY[5.1,3.7,1.5,0.4],'Iris-setosa'),
(23,ARRAY[4.6,3.6,1.0,0.2],'Iris-setosa'),
(24,ARRAY[5.1,3.3,1.7,0.5],'Iris-setosa'),
(25,ARRAY[4.8,3.4,1.9,0.2],'Iris-setosa'),
(26,ARRAY[5.0,3.0,1.6,0.2],'Iris-setosa'),
(27,ARRAY[5.0,3.4,1.6,0.4],'Iris-setosa'),
(28,ARRAY[5.2,3.5,1.5,0.2],'Iris-setosa'),
(29,ARRAY[5.2,3.4,1.4,0.2],'Iris-setosa'),
(30,ARRAY[4.7,3.2,1.6,0.2],'Iris-setosa'),
(31,ARRAY[4.8,3.1,1.6,0.2],'Iris-setosa'),
(32,ARRAY[5.4,3.4,1.5,0.4],'Iris-setosa'),
(33,ARRAY[5.2,4.1,1.5,0.1],'Iris-setosa'),
(34,ARRAY[5.5,4.2,1.4,0.2],'Iris-setosa'),
(35,ARRAY[4.9,3.1,1.5,0.1],'Iris-setosa'),
(36,ARRAY[5.0,3.2,1.2,0.2],'Iris-setosa'),
(37,ARRAY[5.5,3.5,1.3,0.2],'Iris-setosa'),
(38,ARRAY[4.9,3.1,1.5,0.1],'Iris-setosa'),
(39,ARRAY[4.4,3.0,1.3,0.2],'Iris-setosa'),
(40,ARRAY[5.1,3.4,1.5,0.2],'Iris-setosa'),
(41,ARRAY[5.0,3.5,1.3,0.3],'Iris-setosa'),
(42,ARRAY[4.5,2.3,1.3,0.3],'Iris-setosa'),
(43,ARRAY[4.4,3.2,1.3,0.2],'Iris-setosa'),
(44,ARRAY[5.0,3.5,1.6,0.6],'Iris-setosa'),
(45,ARRAY[5.1,3.8,1.9,0.4],'Iris-setosa'),
(46,ARRAY[4.8,3.0,1.4,0.3],'Iris-setosa'),
(47,ARRAY[5.1,3.8,1.6,0.2],'Iris-setosa'),
(48,ARRAY[4.6,3.2,1.4,0.2],'Iris-setosa'),
(49,ARRAY[5.3,3.7,1.5,0.2],'Iris-setosa'),
(50,ARRAY[5.0,3.3,1.4,0.2],'Iris-setosa'),
(51,ARRAY[7.0,3.2,4.7,1.4],'Iris-versicolor'),
(52,ARRAY[6.4,3.2,4.5,1.5],'Iris-versicolor'),
(53,ARRAY[6.9,3.1,4.9,1.5],'Iris-versicolor'),
(54,ARRAY[5.5,2.3,4.0,1.3],'Iris-versicolor'),
(55,ARRAY[6.5,2.8,4.6,1.5],'Iris-versicolor'),
(56,ARRAY[5.7,2.8,4.5,1.3],'Iris-versicolor'),
(57,ARRAY[6.3,3.3,4.7,1.6],'Iris-versicolor'),
(58,ARRAY[4.9,2.4,3.3,1.0],'Iris-versicolor'),
(59,ARRAY[6.6,2.9,4.6,1.3],'Iris-versicolor'),
(60,ARRAY[5.2,2.7,3.9,1.4],'Iris-versicolor'),
(61,ARRAY[5.0,2.0,3.5,1.0],'Iris-versicolor'),
(62,ARRAY[5.9,3.0,4.2,1.5],'Iris-versicolor'),
(63,ARRAY[6.0,2.2,4.0,1.0],'Iris-versicolor'),
(64,ARRAY[6.1,2.9,4.7,1.4],'Iris-versicolor'),
(65,ARRAY[5.6,2.9,3.6,1.3],'Iris-versicolor'),
(66,ARRAY[6.7,3.1,4.4,1.4],'Iris-versicolor'),
(67,ARRAY[5.6,3.0,4.5,1.5],'Iris-versicolor'),
(68,ARRAY[5.8,2.7,4.1,1.0],'Iris-versicolor'),
(69,ARRAY[6.2,2.2,4.5,1.5],'Iris-versicolor'),
(70,ARRAY[5.6,2.5,3.9,1.1],'Iris-versicolor'),
(71,ARRAY[5.9,3.2,4.8,1.8],'Iris-versicolor'),
(72,ARRAY[6.1,2.8,4.0,1.3],'Iris-versicolor'),
(73,ARRAY[6.3,2.5,4.9,1.5],'Iris-versicolor'),
(74,ARRAY[6.1,2.8,4.7,1.2],'Iris-versicolor'),
(75,ARRAY[6.4,2.9,4.3,1.3],'Iris-versicolor'),
(76,ARRAY[6.6,3.0,4.4,1.4],'Iris-versicolor'),
(77,ARRAY[6.8,2.8,4.8,1.4],'Iris-versicolor'),
(78,ARRAY[6.7,3.0,5.0,1.7],'Iris-versicolor'),
(79,ARRAY[6.0,2.9,4.5,1.5],'Iris-versicolor'),
(80,ARRAY[5.7,2.6,3.5,1.0],'Iris-versicolor'),
(81,ARRAY[5.5,2.4,3.8,1.1],'Iris-versicolor'),
(82,ARRAY[5.5,2.4,3.7,1.0],'Iris-versicolor'),
(83,ARRAY[5.8,2.7,3.9,1.2],'Iris-versicolor'),
(84,ARRAY[6.0,2.7,5.1,1.6],'Iris-versicolor'),
(85,ARRAY[5.4,3.0,4.5,1.5],'Iris-versicolor'),
(86,ARRAY[6.0,3.4,4.5,1.6],'Iris-versicolor'),
(87,ARRAY[6.7,3.1,4.7,1.5],'Iris-versicolor'),
(88,ARRAY[6.3,2.3,4.4,1.3],'Iris-versicolor'),
(89,ARRAY[5.6,3.0,4.1,1.3],'Iris-versicolor'),
(90,ARRAY[5.5,2.5,4.0,1.3],'Iris-versicolor'),
(91,ARRAY[5.5,2.6,4.4,1.2],'Iris-versicolor'),
(92,ARRAY[6.1,3.0,4.6,1.4],'Iris-versicolor'),
(93,ARRAY[5.8,2.6,4.0,1.2],'Iris-versicolor'),
(94,ARRAY[5.0,2.3,3.3,1.0],'Iris-versicolor'),
(95,ARRAY[5.6,2.7,4.2,1.3],'Iris-versicolor'),
(96,ARRAY[5.7,3.0,4.2,1.2],'Iris-versicolor'),
(97,ARRAY[5.7,2.9,4.2,1.3],'Iris-versicolor'),
(98,ARRAY[6.2,2.9,4.3,1.3],'Iris-versicolor'),
(99,ARRAY[5.1,2.5,3.0,1.1],'Iris-versicolor'),
(100,ARRAY[5.7,2.8,4.1,1.3],'Iris-versicolor'),
(101,ARRAY[6.3,3.3,6.0,2.5],'Iris-virginica'),
(102,ARRAY[5.8,2.7,5.1,1.9],'Iris-virginica'),
(103,ARRAY[7.1,3.0,5.9,2.1],'Iris-virginica'),
(104,ARRAY[6.3,2.9,5.6,1.8],'Iris-virginica'),
(105,ARRAY[6.5,3.0,5.8,2.2],'Iris-virginica'),
(106,ARRAY[7.6,3.0,6.6,2.1],'Iris-virginica'),
(107,ARRAY[4.9,2.5,4.5,1.7],'Iris-virginica'),
(108,ARRAY[7.3,2.9,6.3,1.8],'Iris-virginica'),
(109,ARRAY[6.7,2.5,5.8,1.8],'Iris-virginica'),
(110,ARRAY[7.2,3.6,6.1,2.5],'Iris-virginica'),
(111,ARRAY[6.5,3.2,5.1,2.0],'Iris-virginica'),
(112,ARRAY[6.4,2.7,5.3,1.9],'Iris-virginica'),
(113,ARRAY[6.8,3.0,5.5,2.1],'Iris-virginica'),
(114,ARRAY[5.7,2.5,5.0,2.0],'Iris-virginica'),
(115,ARRAY[5.8,2.8,5.1,2.4],'Iris-virginica'),
(116,ARRAY[6.4,3.2,5.3,2.3],'Iris-virginica'),
(117,ARRAY[6.5,3.0,5.5,1.8],'Iris-virginica'),
(118,ARRAY[7.7,3.8,6.7,2.2],'Iris-virginica'),
(119,ARRAY[7.7,2.6,6.9,2.3],'Iris-virginica'),
(120,ARRAY[6.0,2.2,5.0,1.5],'Iris-virginica'),
(121,ARRAY[6.9,3.2,5.7,2.3],'Iris-virginica'),
(122,ARRAY[5.6,2.8,4.9,2.0],'Iris-virginica'),
(123,ARRAY[7.7,2.8,6.7,2.0],'Iris-virginica'),
(124,ARRAY[6.3,2.7,4.9,1.8],'Iris-virginica'),
(125,ARRAY[6.7,3.3,5.7,2.1],'Iris-virginica'),
(126,ARRAY[7.2,3.2,6.0,1.8],'Iris-virginica'),
(127,ARRAY[6.2,2.8,4.8,1.8],'Iris-virginica'),
(128,ARRAY[6.1,3.0,4.9,1.8],'Iris-virginica'),
(129,ARRAY[6.4,2.8,5.6,2.1],'Iris-virginica'),
(130,ARRAY[7.2,3.0,5.8,1.6],'Iris-virginica'),
(131,ARRAY[7.4,2.8,6.1,1.9],'Iris-virginica'),
(132,ARRAY[7.9,3.8,6.4,2.0],'Iris-virginica'),
(133,ARRAY[6.4,2.8,5.6,2.2],'Iris-virginica'),
(134,ARRAY[6.3,2.8,5.1,1.5],'Iris-virginica'),
(135,ARRAY[6.1,2.6,5.6,1.4],'Iris-virginica'),
(136,ARRAY[7.7,3.0,6.1,2.3],'Iris-virginica'),
(137,ARRAY[6.3,3.4,5.6,2.4],'Iris-virginica'),
(138,ARRAY[6.4,3.1,5.5,1.8],'Iris-virginica'),
(139,ARRAY[6.0,3.0,4.8,1.8],'Iris-virginica'),
(140,ARRAY[6.9,3.1,5.4,2.1],'Iris-virginica'),
(141,ARRAY[6.7,3.1,5.6,2.4],'Iris-virginica'),
(142,ARRAY[6.9,3.1,5.1,2.3],'Iris-virginica'),
(143,ARRAY[5.8,2.7,5.1,1.9],'Iris-virginica'),
(144,ARRAY[6.8,3.2,5.9,2.3],'Iris-virginica'),
(145,ARRAY[6.7,3.3,5.7,2.5],'Iris-virginica'),
(146,ARRAY[6.7,3.0,5.2,2.3],'Iris-virginica'),
(147,ARRAY[6.3,2.5,5.0,1.9],'Iris-virginica'),
(148,ARRAY[6.5,3.0,5.2,2.0],'Iris-virginica'),
(149,ARRAY[6.2,3.4,5.4,2.3],'Iris-virginica'),
(150,ARRAY[5.9,3.0,5.1,1.8],'Iris-virginica');


DROP TABLE IF EXISTS iris_data_one_hot_encoded;
CREATE TABLE iris_data_one_hot_encoded as select id, attributes, ARRAY[class_text is not distinct from 'Iris-setosa', class_text is not distinct from 'Iris-versicolor', class_text is not distinct from 'Iris-virginica']::int[] as class_one_hot_encoded
from iris_data;


DROP TABLE IF EXISTS iris_data_packed, iris_data_packed_summary;
SELECT training_preprocessor_dl('iris_data',         -- Source table
                                'iris_data_packed',  -- Output table
                                'class_text',        -- Dependent variable
                                'attributes'         -- Independent variable
                                );

DROP TABLE IF EXISTS iris_data_one_hot_encoded_packed, iris_data_one_hot_encoded_packed_summary;
SELECT training_preprocessor_dl('iris_data_one_hot_encoded',         -- Source table
                                'iris_data_one_hot_encoded_packed',  -- Output table
                                'class_one_hot_encoded',        -- Dependent variable
                                'attributes'         -- Independent variable
           );

DROP TABLE IF EXISTS iris_data_val, iris_data_val_summary;
SELECT validation_preprocessor_dl('iris_data',    -- Source table
                                'iris_data_val',  -- Output table
                                'class_text',     -- Dependent variable
                                'attributes',     -- Independent variable
                                'iris_data_packed'-- Training preprocessed table
                                );

DROP TABLE IF EXISTS iris_data_one_hot_encoded_val, iris_data_one_hot_encoded_val_summary;
SELECT validation_preprocessor_dl('iris_data_one_hot_encoded',    -- Source table
                                'iris_data_one_hot_encoded_val',  -- Output table
                                'class_one_hot_encoded',        -- Dependent variable
                                'attributes',         -- Independent variable
                                'iris_data_one_hot_encoded_packed'    -- Training preprocessed table
           );

DROP TABLE IF EXISTS iris_model_arch;
-- NOTE: The seed is set to 0 for every layer.
SELECT load_keras_model('iris_model_arch',  -- Output table,
$$
{
"class_name": "Sequential",
"keras_version": "2.1.6",
"config":
    [{"class_name": "Dense", "config": {"kernel_initializer": {"class_name": "VarianceScaling",
    "config": {"distribution": "uniform", "scale": 1.0, "seed": 0, "mode": "fan_avg"}},
    "name": "dense_1", "kernel_constraint": null, "bias_regularizer": null,
    "bias_constraint": null, "dtype": "float32", "activation": "relu", "trainable": true,
    "kernel_regularizer": null, "bias_initializer": {"class_name": "Zeros",
    "config": {}}, "units": 10, "batch_input_shape": [null, 4], "use_bias": true,
    "activity_regularizer": null}}, {"class_name": "Dense",
    "config": {"kernel_initializer": {"class_name": "VarianceScaling",
    "config": {"distribution": "uniform", "scale": 1.0, "seed": 0, "mode": "fan_avg"}},
    "name": "dense_2", "kernel_constraint": null, "bias_regularizer": null,
    "bias_constraint": null, "activation": "relu", "trainable": true, "kernel_regularizer": null,
    "bias_initializer": {"class_name": "Zeros", "config": {}}, "units": 10, "use_bias": true,
    "activity_regularizer": null}}, {"class_name": "Dense", "config": {"kernel_initializer":
    {"class_name": "VarianceScaling", "config": {"distribution": "uniform", "scale": 1.0,
    "seed": 0, "mode": "fan_avg"}}, "name": "dense_3", "kernel_constraint": null,
    "bias_regularizer": null, "bias_constraint": null, "activation": "softmax",
    "trainable": true, "kernel_regularizer": null, "bias_initializer": {"class_name": "Zeros",
    "config": {}}, "units": 3, "use_bias": true, "activity_regularizer": null}}],
    "backend": "tensorflow"}
$$
);

-- Duplicate the architecture, but note that trainable is set to FALSE.
-- This is to ensure we don't learn anything new, that would help us
-- deterministically assert the accuracy and loss after transfer learning
-- and warm start.
SELECT load_keras_model('iris_model_arch',  -- Output table,
$$
{
"class_name": "Sequential",
"keras_version": "2.1.6",
"config":
    [{"class_name": "Dense", "config": {"kernel_initializer": {"class_name": "VarianceScaling",
    "config": {"distribution": "uniform", "scale": 1.0, "seed": 0, "mode": "fan_avg"}},
    "name": "dense_1", "kernel_constraint": null, "bias_regularizer": null,
    "bias_constraint": null, "dtype": "float32", "activation": "relu",
    "trainable": false,
    "kernel_regularizer": null, "bias_initializer": {"class_name": "Zeros",
    "config": {}}, "units": 10, "batch_input_shape": [null, 4], "use_bias": true,
    "activity_regularizer": null}}, {"class_name": "Dense",
    "config": {"kernel_initializer": {"class_name": "VarianceScaling",
    "config": {"distribution": "uniform", "scale": 1.0, "seed": 0, "mode": "fan_avg"}},
    "name": "dense_2", "kernel_constraint": null, "bias_regularizer": null,
    "bias_constraint": null, "activation": "relu",
    "trainable": false,
    "kernel_regularizer": null, "bias_initializer": {"class_name": "Zeros",
    "config": {}}, "units": 10, "use_bias": true, "activity_regularizer": null}},
    {"class_name": "Dense", "config": {"kernel_initializer":
    {"class_name": "VarianceScaling", "config": {"distribution": "uniform", "scale": 1.0,
    "seed": 0, "mode": "fan_avg"}}, "name": "dense_3", "kernel_constraint": null,
    "bias_regularizer": null, "bias_constraint": null, "activation": "softmax",
    "trainable": false,
    "kernel_regularizer": null, "bias_initializer": {"class_name": "Zeros",
    "config": {}}, "units": 3, "use_bias": true, "activity_regularizer": null}}],
    "backend": "tensorflow"}
$$
);

DROP TABLE IF EXISTS iris_train, iris_test;
-- Set seed so results are reproducible
SELECT setseed(0);
SELECT train_test_split('iris_data',     -- Source table
                        'iris',          -- Output table root name
                        0.8,            -- Train proportion
                        NULL,           -- Test proportion (0.2)
                        NULL,           -- Strata definition
                        NULL,           -- Output all columns
                        NULL,           -- Sample without replacement
                        TRUE            -- Separate output tables
                        );

DROP TABLE IF EXISTS iris_data_15buf_packed, iris_data_15buf_packed_summary;
SELECT training_preprocessor_dl('iris_test',         -- Source table
                                'iris_data_15buf_packed',  -- Output table
                                'class_text',        -- Dependent variable
                                'attributes',        -- Independent variable
                                2                    -- buffer_size  (15 buffers)
                                );

-- Create multi io dataset

DROP TABLE IF EXISTS iris_mult;
CREATE TABLE iris_mult AS
    SELECT  id, attributes, array_square(attributes) AS attributes2,
            class_text AS class_text, class_text AS class_text2
FROM iris_data;

SELECT load_keras_model('iris_model_arch',  -- Output table,
$$
{"class_name": "Model", "keras_version": "2.2.4-tf", "config": {"layers": [{"class_name": "InputLayer", "config": {"dtype": "float32", "batch_input_shape": [null, 4], "name": "input_1", "sparse": false}, "inbound_nodes": [], "name": "input_1"}, {"class_name": "InputLayer", "config": {"dtype": "float32", "batch_input_shape": [null, 4], "name": "input_2", "sparse": false}, "inbound_nodes": [], "name": "input_2"}, {"class_name": "Dense", "config": {"kernel_initializer": {"class_name": "VarianceScaling", "config": {"dtype": "float32", "distribution": "uniform", "scale": 1.0, "seed": null, "mode": "fan_in"}}, "name": "dense", "kernel_constraint": null, "bias_regularizer": null, "bias_constraint": null, "dtype": "float32", "activation": "relu", "trainable": true, "kernel_regularizer": null, "bias_initializer": {"class_name": "Zeros", "config": {"dtype": "float32"}}, "units": 10, "use_bias": true, "activity_regularizer": null}, "inbound_nodes": [[["input_1", 0, 0, {}]]], "name": "dense"}, {"class_name": "Dense", "config": {"kernel_initializer": {"class_name": "VarianceScaling", "config": {"dtype": "float32", "distribution": "uniform", "scale": 1.0, "seed": null, "mode": "fan_in"}}, "name": "dense_2", "kernel_constraint": null, "bias_regularizer": null, "bias_constraint": null, "dtype": "float32", "activation": "relu", "trainable": true, "kernel_regularizer": null, "bias_initializer": {"class_name": "Zeros", "config": {"dtype": "float32"}}, "units": 10, "use_bias": true, "activity_regularizer": null}, "inbound_nodes": [[["input_2", 0, 0, {}]]], "name": "dense_2"}, {"class_name": "Dense", "config": {"kernel_initializer": {"class_name": "VarianceScaling", "config": {"dtype": "float32", "distribution": "uniform", "scale": 1.0, "seed": null, "mode": "fan_in"}}, "name": "dense_1", "kernel_constraint": null, "bias_regularizer": null, "bias_constraint": null, "dtype": "float32", "activation": "relu", "trainable": true, "kernel_regularizer": null, "bias_initializer": {"class_name": "Zeros", "config": {"dtype": "float32"}}, "units": 10, "use_bias": true, "activity_regularizer": null}, "inbound_nodes": [[["dense", 0, 0, {}]]], "name": "dense_1"}, {"class_name": "Dense", "config": {"kernel_initializer": {"class_name": "VarianceScaling", "config": {"dtype": "float32", "distribution": "uniform", "scale": 1.0, "seed": null, "mode": "fan_in"}}, "name": "dense_3", "kernel_constraint": null, "bias_regularizer": null, "bias_constraint": null, "dtype": "float32", "activation": "relu", "trainable": true, "kernel_regularizer": null, "bias_initializer": {"class_name": "Zeros", "config": {"dtype": "float32"}}, "units": 10, "use_bias": true, "activity_regularizer": null}, "inbound_nodes": [[["dense_2", 0, 0, {}]]], "name": "dense_3"}, {"class_name": "Concatenate", "config": {"dtype": "float32", "trainable": true, "name": "concatenate", "axis": -1}, "inbound_nodes": [[["dense_1", 0, 0, {}], ["dense_3", 0, 0, {}]]], "name": "concatenate"}, {"class_name": "Dense", "config": {"kernel_initializer": {"class_name": "VarianceScaling", "config": {"dtype": "float32", "distribution": "uniform", "scale": 1.0, "seed": null, "mode": "fan_in"}}, "name": "dense_4", "kernel_constraint": null, "bias_regularizer": null, "bias_constraint": null, "dtype": "float32", "activation": "softmax", "trainable": true, "kernel_regularizer": null, "bias_initializer": {"class_name": "Zeros", "config": {"dtype": "float32"}}, "units": 3, "use_bias": true, "activity_regularizer": null}, "inbound_nodes": [[["concatenate", 0, 0, {}]]], "name": "dense_4"}, {"class_name": "Dense", "config": {"kernel_initializer": {"class_name": "VarianceScaling", "config": {"dtype": "float32", "distribution": "uniform", "scale": 1.0, "seed": null, "mode": "fan_in"}}, "name": "dense_5", "kernel_constraint": null, "bias_regularizer": null, "bias_constraint": null, "dtype": "float32", "activation": "softmax", "trainable": true, "kernel_regularizer": null, "bias_initializer": {"class_name": "Zeros", "config": {"dtype": "float32"}}, "units": 3, "use_bias": true, "activity_regularizer": null}, "inbound_nodes": [[["dense_3", 0, 0, {}]]], "name": "dense_5"}], "input_layers": [["input_1", 0, 0], ["input_2", 0, 0]], "output_layers": [["dense_4", 0, 0], ["dense_5", 0, 0]], "name": "model"}, "backend": "tensorflow"}
$$::json,  NULL,
 'Sophie',
                               'A simple model'
);

DROP TABLE IF EXISTS iris_mult_packed, iris_mult_packed_summary;
SELECT training_preprocessor_dl('iris_mult',
                                'iris_mult_packed',
                                'class_text, class_text2',
                                'attributes, attributes2',
                                NULL,
                                255
                                );

DROP TABLE IF EXISTS iris_mult_val, iris_mult_val_summary;
SELECT validation_preprocessor_dl('iris_mult',    -- Source table
                                'iris_mult_val',  -- Output table
                                'class_text, class_text2',     -- Dependent variable
                                'attributes, attributes2',     -- Independent variable
                                'iris_mult_packed'-- Training preprocessed table
                                );