1 files changed, 53 insertions, 0 deletions
diff --git a/src/layer.js b/src/layer.js
new file mode 100644
index 0000000..65b14ec
--- /dev/null
+++ b/src/layer.js
@@ -0,0 +1,53 @@
+console.log('Hello from layer.js');
+
+class Layer {
+	constructor(inputCount, nodeCount, activationFunctionName) {
+		this.gx = activationFunctionList[activationFunctionName].gx;
+		this.dg_dx = activationFunctionList[activationFunctionName].dg_dx;
+		this.weights = math.matrix(math.random([inputCount, nodeCount]));
+		this.weights = math.map(this.weights, (element) => (element - 0.5) * 2);
+		this.biases = math.matrix(math.zeros([nodeCount]));
+		this.z = math.matrix(math.zeros([nodeCount]));
+		this.dc_dw_vectors = math.matrix(math.zeros(this.weights._size));
+		this.dc_db_vectors = math.matrix(math.zeros(this.biases._size));
+		console.log('dc_db_vectors', this.dc_db_vectors);
+	}
+	forwardPropogation(activationInput) {
+		this.ai = activationInput;		
+		let z = math.multiply(activationInput, this.weights);
+		z = math.add(z, this.biases);
+		this.z = z;
+		let ao = this.gx(z);
+		return ao;
+	}
+	backPropogation(dc_dao) {
+		let dao_dz = this.dg_dx(this.z);
+		let dc_db = math.dotMultiply(dao_dz, dc_dao);
+		let dz_dw = math.ones(this.weights._size);
+		dz_dw = math.multiply(this.ai, dz_dw);
+		let dc_dw = math.dotMultiply(dc_db, dz_dw);
+		let dz_dai = this.weights;
+		let dc_dai = math.multiply(dz_dai, dc_db);
+		
+		//store cost vectors for gradient descent		
+		console.log('dc_db_vectors', this.dc_db_vectors);
+		console.log('dc_db', dc_db);
+		this.dc_db_vectors = math.concat(this.dc_db_vectors, dc_db, 0);
+		this.dc_dw_vectors = math.concat(this.dc_dw_vectors, dc_dw, 0);
+		console.log('dc_db_vectors', this.dc_db_vectors);
+		
+		return dc_dai;
+	}
+	gradientDescent(learningRate) {
+		
+		console.log(this.dc_dw_vectors);
+		console.log(this.dc_db_vectors);
+		
+		let dc_dw_avg = math.mean(this.dc_dw_vectors, 0)
+		let dc_db_avg = math.mean(this.dc_db_vectors, 0)
+		this.weights = this.weights - (learningRate * dc_dw_avg);
+		this.biases = this.biases - (learningRate * dc_dw_avg);
+		this.dc_dw_vectors = math.matrix([]);
+		this.dc_db_vectors = math.matrix([]);
+	}
+};