p003-Dot-Product.sql

MySQL/p001-Basic-Neuron-3-inputs.sql

@@ -0,0 +1,40 @@
+--
+-- Creates a basic neuron with 3 inputs.
+--
+-- Associated YT NNFS tutorial: https://www.youtube.com/watch?v=Wo5dMEP_BbI
+--
+
+DROP DATABASE IF EXISTS `p001_basic_neuron_3_inputs`;
+CREATE DATABASE `p001_basic_neuron_3_inputs`;
+
+USE `p001_basic_neuron_3_inputs`;
+
+CREATE TABLE `inputs`
+(
+    `0` DOUBLE NOT NULL,
+    `1` DOUBLE NOT NULL,
+    `2` DOUBLE NOT NULL
+);
+
+CREATE TABLE `weights`
+(
+    `0` DOUBLE NOT NULL,
+    `1` DOUBLE NOT NULL,
+    `2` DOUBLE NOT NULL
+);
+
+CREATE TABLE `bias`
+(
+    `0` DOUBLE NOT NULL
+);
+
+INSERT INTO `inputs` (`0`, `1`, `2`) VALUES ( 1.2, 5.1, 2.1 );
+INSERT INTO `weights` (`0`, `1`, `2`) VALUES ( 3.1, 2.1, 8.7 );
+INSERT INTO `bias` (`0`) VALUES ( 3.0 );
+
+SELECT (
+                   ( SELECT `inputs`.`0` FROM inputs ) * ( SELECT `weights`.`0` FROM weights ) +
+                   ( SELECT `inputs`.`1` FROM inputs ) * ( SELECT `weights`.`1` FROM weights ) +
+                   ( SELECT `inputs`.`2` FROM inputs ) * ( SELECT `weights`.`2` FROM weights ) +
+                   ( SELECT `bias`.`0` FROM bias )
+           ) AS output;

MySQL/p002-Basic-Neuron-Layer.sql

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+--
+-- Creates a simple layer of neurons, with 4 inputs.
+--
+-- Associated YT NNFS tutorial: https://www.youtube.com/watch?v=lGLto9Xd7bU
+--
+
+DROP DATABASE IF EXISTS `p002_basic_neuron_layer`;
+CREATE DATABASE `p002_basic_neuron_layer`;
+
+USE `p002_basic_neuron_layer`;
+
+CREATE TABLE `inputs` ( `0` DOUBLE NOT NULL, `1` DOUBLE NOT NULL, `2` DOUBLE NOT NULL, `3` DOUBLE NOT NULL );
+
+CREATE TABLE `weights1` ( `0` DOUBLE NOT NULL, `1` DOUBLE NOT NULL, `2` DOUBLE NOT NULL, `3` DOUBLE NOT NULL );
+CREATE TABLE `weights2` ( `0` DOUBLE NOT NULL, `1` DOUBLE NOT NULL, `2` DOUBLE NOT NULL, `3` DOUBLE NOT NULL );
+CREATE TABLE `weights3` ( `0` DOUBLE NOT NULL, `1` DOUBLE NOT NULL, `2` DOUBLE NOT NULL, `3` DOUBLE NOT NULL );
+
+CREATE TABLE `bias1` ( `0` DOUBLE NOT NULL );
+CREATE TABLE `bias2` ( `0` DOUBLE NOT NULL );
+CREATE TABLE `bias3` ( `0` DOUBLE NOT NULL );
+
+INSERT INTO `inputs` (`0`, `1`, `2`, `3`) VALUES ( 1, 2, 3, 2.5 );
+
+INSERT INTO `weights1` (`0`, `1`, `2`, `3`) VALUES ( 0.2, 0.8, -0.5, 1 );
+INSERT INTO `weights2` (`0`, `1`, `2`, `3`) VALUES ( 0.5, -0.91, 0.26, -0.5 );
+INSERT INTO `weights3` (`0`, `1`, `2`, `3`) VALUES ( -0.26, -0.27, 0.17, 0.87 );
+
+INSERT INTO `bias1` (`0`) VALUES (2);
+INSERT INTO `bias2` (`0`) VALUES (3);
+INSERT INTO `bias3` (`0`) VALUES (0.5);
+
+SELECT (
+   ( SELECT `inputs`.`0` FROM inputs ) * ( SELECT `weights1`.`0` FROM weights1 ) +
+   ( SELECT `inputs`.`1` FROM inputs ) * ( SELECT `weights1`.`1` FROM weights1 ) +
+   ( SELECT `inputs`.`2` FROM inputs ) * ( SELECT `weights1`.`2` FROM weights1 ) +
+   ( SELECT `inputs`.`3` FROM inputs ) * ( SELECT `weights1`.`3` FROM weights1 ) +
+   ( SELECT `bias1`.`0` FROM bias1 )
+) AS `1`,
+(
+   ( SELECT `inputs`.`0` FROM inputs ) * ( SELECT `weights2`.`0` FROM weights2 ) +
+   ( SELECT `inputs`.`1` FROM inputs ) * ( SELECT `weights2`.`1` FROM weights2 ) +
+   ( SELECT `inputs`.`2` FROM inputs ) * ( SELECT `weights2`.`2` FROM weights2 ) +
+   ( SELECT `inputs`.`3` FROM inputs ) * ( SELECT `weights2`.`3` FROM weights2 ) +
+   ( SELECT `bias2`.`0` FROM bias2 )
+) AS `2`,
+(
+   ( SELECT `inputs`.`0` FROM inputs ) * ( SELECT `weights3`.`0` FROM weights3 ) +
+   ( SELECT `inputs`.`1` FROM inputs ) * ( SELECT `weights3`.`1` FROM weights3 ) +
+   ( SELECT `inputs`.`2` FROM inputs ) * ( SELECT `weights3`.`2` FROM weights3 ) +
+   ( SELECT `inputs`.`3` FROM inputs ) * ( SELECT `weights3`.`3` FROM weights3 ) +
+   ( SELECT `bias3`.`0` FROM bias3 )
+) AS `3`

MySQL/p003-Dot-Product.sql

@@ -0,0 +1,78 @@
+--
+-- Doing dot product with a layer of neurons and multiple inputs
+--
+-- Associated YT NNFS tutorial: https://www.youtube.com/watch?v=tMrbN67U9d4
+--
+
+DROP DATABASE IF EXISTS `p003_dot_product`;
+CREATE DATABASE `p003_dot_product`;
+
+USE `p003_dot_product`;
+
+CREATE TABLE `inputs`
+(
+    `0` DOUBLE NOT NULL,
+    `1` DOUBLE NOT NULL,
+    `2` DOUBLE NOT NULL,
+    `3` DOUBLE NOT NULL
+);
+
+CREATE TABLE `weights`
+(
+    `id` INT(11) NOT NULL AUTO_INCREMENT,
+    `0`  DOUBLE  NOT NULL,
+    `1`  DOUBLE  NOT NULL,
+    `2`  DOUBLE  NOT NULL,
+    `3`  DOUBLE  NOT NULL,
+    PRIMARY KEY (`id`) USING BTREE
+);
+
+CREATE TABLE `biases`
+(
+    `weight_id` INT(11) NOT NULL DEFAULT '0',
+    `bias`      DOUBLE  NOT NULL
+);
+
+INSERT INTO `inputs` (`0`, `1`, `2`, `3`)
+VALUES (1, 2, 3, 2.5);
+
+INSERT INTO `weights` (`id`, `0`, `1`, `2`, `3`)
+VALUES (1, 0.2, 0.8, -0.5, 1),
+       (2, 0.5, -0.91, 0.26, -0.5),
+       (3, -0.26, -0.27, 0.17, 0.87);
+
+INSERT INTO `biases` (`weight_id`, `bias`)
+VALUES (1, 2),
+       (2, 3),
+       (3, 0.5);
+
+DELIMITER $$
+CREATE FUNCTION `dot`(
+    `vector1` JSON,
+    `vector2` JSON
+) RETURNS DOUBLE
+    NO SQL
+    DETERMINISTIC
+    COMMENT 'The dot product of two vectors in json format'
+BEGIN
+
+    DECLARE i INT DEFAULT 0;
+    DECLARE vector_length INT;
+    DECLARE output DOUBLE DEFAULT 0;
+
+    SET vector_length = JSON_LENGTH(vector1);
+
+    WHILE i < vector_length
+        DO
+            SET output = output + JSON_EXTRACT(vector1, CONCAT("$[", i, "]")) * JSON_EXTRACT(vector2, CONCAT("$[", i, "]"));
+            SET i = i + 1;
+        END WHILE;
+
+    RETURN output;
+
+END $$
+DELIMITER ;
+
+SELECT (dot(JSON_ARRAY(i.`0`, i.`1`, i.`2`, i.`3`),JSON_ARRAY(w.`0`, w.`1`, w.`2`, w.`3`)) + b.bias) AS output
+FROM inputs i, weights w, biases b
+WHERE b.weight_id = w.id;