Added instance compairing for bias and weights

rgbAI/lib/func.py

@@ -53,18 +53,22 @@ class AIlib:
 		dCost = cost2 - cost1
 		return dCost
 
-	def compareInstance( obj, theta, layerIndex, neuronIndex_X=0, neuronIndex_Y=0 ):
-		# Create new instances of the object
-		obj2_w = copy(obj) # annoying way to create a new instance of the object
-		obj2_b = copy(obj)
+	def compareInstanceWeight( obj, theta, layerIndex, neuronIndex_X=0, neuronIndex_Y=0 ):
+		# Create new a instance of the object
+		obj2 = copy(obj) # annoying way to create a new instance of the object
 
-		obj2_w.weights[layerIndex][neuronIndex_X][neuronIndex_Y] += theta # mutate the second objects neuron
-		dCost_weight = AIlib.compareAIobjects( obj, obj2_w ) # compare the two and get the dCost with respect to the weights
+		obj2.weights[layerIndex][neuronIndex_X][neuronIndex_Y] += theta # mutate the second objects neuron
+		dCost = AIlib.compareAIobjects( obj, obj2 ) # compare the two and get the dCost with respect to the weights
 
-		obj2_b.bias[layerIndex][neuronIndex_X][neuronIndex_Y] += theta # do the same thing for the bias
-		dCost_bias = AIlib.compareAIobjects( obj, obj2_b )
+		return dCost
+
+	def compareInstanceBias( obj, theta, layerIndex, biasIndex ):
+		obj2 = copy(obj)
+
+		obj2.bias[layerIndex][biasIndex] += theta # do the same thing for the bias
+		dCost = AIlib.compareAIobjects( obj, obj2 )
 
-		return dCost_weight, dCost_bias
+		return dCost
 
 	def getChangeInCost( obj, theta, layerIndex ):
 		mirrorObj = copy(obj)
@@ -73,6 +77,8 @@ class AIlib:
 		mirrorObj.weights[layerIndex].fill(None)
 		mirrorObj.bias[layerIndex].fill(None)
 
+
+
 	def gradient( inp:np.array, obj, theta:float, maxLayer:int, layerIndex: int=0, grads=None, obj1=None, obj2=None ): # Calculate the gradient for that prop
 		# Check if grads exists, if not create the buffer
 		if( not grads ):