/* ---------------------------------------------------------------------*//**
 *
 * 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.
 *
 *//* ---------------------------------------------------------------------*/

\i m4_regexp(MODULE_PATHNAME,
             `\(.*\)libmadlib\.so',
             `\1../../modules/deep_learning/test/madlib_keras_iris.setup.sql_in'
)

\i m4_regexp(MODULE_PATHNAME,
             `\(.*\)libmadlib\.so',
             `\1../../modules/deep_learning/test/madlib_keras_custom_function.setup.sql_in'
)

m4_include(`SQLCommon.m4')

-- Test multi io
DROP TABLE IF EXISTS iris_model, iris_model_summary;
SELECT madlib_keras_fit('iris_mult_packed',
                        'iris_model',
                        'iris_model_arch',
                        3,
                        $$ loss='categorical_crossentropy', optimizer='adam', metrics=['accuracy'] $$::text,
                        $$ batch_size=5, epochs=3 $$::text,
                        2,
                        NULL,
                        'iris_mult_val');

-- Run Evaluate
DROP TABLE IF EXISTS evaluate_out;
SELECT madlib_keras_evaluate(
    'iris_model',
    'iris_mult_val',
    'evaluate_out',
    FALSE);

-- Run Predict
DROP TABLE IF EXISTS iris_predict;
SELECT madlib_keras_predict(
    'iris_model',
    'iris_mult',
    'id',
    'attributes, attributes2',
    'iris_predict',
    0.5,
    FALSE);

-- Warm Start

DROP TABLE IF EXISTS iris_model_first_run;
CREATE TABLE iris_model_first_run AS
SELECT training_loss_final, training_metrics_final
FROM iris_model_summary;

SELECT madlib_keras_fit('iris_mult_packed',
                        'iris_model',
                        'iris_model_arch',
                        3,
                        $$ loss='categorical_crossentropy', optimizer='adam', metrics=['accuracy'] $$::text,
                        $$ batch_size=5, epochs=3 $$::text,
                        2,
                        NULL,
                        'iris_mult_val',
                        1,
                        TRUE);

-- Transfer Learning

DROP TABLE IF EXISTS iris_model_arch_multi;
CREATE TABLE iris_model_arch_multi AS
SELECT * FROM iris_model_arch WHERE model_id = 3;

UPDATE iris_model_arch_multi set model_weights = (select model_weights from iris_model);

DROP TABLE IF EXISTS iris_model_transfer, iris_model_transfer_summary;
SELECT madlib_keras_fit('iris_mult_packed',
                        'iris_model_transfer',
                        'iris_model_arch_multi',
                        3,
                        $$ loss='categorical_crossentropy', optimizer='adam', metrics=['accuracy'] $$::text,
                        $$ batch_size=5, epochs=3 $$::text,
                        2,
                        NULL,
                        'iris_mult_val');

-- Custom Function

DROP TABLE IF EXISTS test_custom_function_table;
SELECT load_custom_function('test_custom_function_table', custom_function_zero_object(), 'test_custom_fn', 'returns test_custom_fn');
SELECT load_custom_function('test_custom_function_table', custom_function_one_object(), 'test_custom_fn1', 'returns test_custom_fn1');

DROP TABLE if exists iris_model, iris_model_summary, iris_model_info;
SELECT madlib_keras_fit(
    'iris_mult_packed',
    'iris_model',
    'iris_model_arch',
    3,
    $$ loss='test_custom_fn', optimizer='adam', metrics=['test_custom_fn1'] $$::text,
    $$ batch_size=5, epochs=3 $$::text,
    2,
    FALSE, NULL, 1, NULL, NULL, NULL,
    'test_custom_function_table'
);

m4_changequote(`<!', `!>')
m4_ifdef(<!__POSTGRESQL__!>, <!!>, <!
-- Multiple models test
DROP TABLE IF EXISTS mst_table_1row, mst_table_1row_summary;
SELECT load_model_selection_table(
    'iris_model_arch',
    'mst_table_1row',
    ARRAY[1],
    ARRAY[
        $$loss='categorical_crossentropy', optimizer='Adam(lr=0.01)', metrics=['accuracy']$$
    ],
    ARRAY[
        $$batch_size=16, epochs=1$$
    ]
);
DROP TABLE if exists iris_model, iris_model_summary, iris_model_info;
SELECT assert(test_error_msg($test$SELECT madlib_keras_fit_multiple_model(
	'iris_mult_packed',
	'iris_model',
	'mst_table_1row',
	3,
	FALSE)$test$, 'Multiple dependent and independent variables not supported'),
	'Failed to assert the correct error message for multi-io not supported');
!>)