According to the following simple neural network model, please develop your OWN program function by
using Back Propagation to update weights in the model.
A neural network with:
2 inputs,
3 hidden layer neurons,
3 output neurons.

2. Please include comments to explain your code
3. Please declare a function name as “CustomBPweight()” to accept 5 inputs
4. There are 5 inputs to the functions:
1. Please declare a target output list name as “TargetOutput” (Given)
2. Please declare a current output list name as “CurrentOutput” (Given)
3. Please declare a neuron output list name as “NeuronOutput” (Given)
4. Please declare a current weights list name as “CurrentWeights”(estimate them)
5. Please declare a learning rate variable as “LearningRate” (Given)
5. The function “CustomBPweight()” should return an output (a list with all updated weights).
Please declare the updated weights list name as “UpdateWeights”
6. For all given data, the value of all elements are between 0 and 1
7. Please identify the total number with weights according to the given model

Example:
Input:
TargetOutput = [0, 0, 1]
CurrentOutput = [0.2, 0.85, 0.65]
NeuronOutput = [ n0, n1, n2, n3, n4]
CurrentWeights = [w0, w1, w2, w3, …….., wn]
LearningRate = 0.3
Function:
CustomBPweight(TargetOutput, CurrentOutput, NeuronOutput, CurrentWeights, Learning Rate)
Output:
OldWeights = [w0,w1, w2, w3, …..., wn]
UpdateWeights = [ww0, ww1, ww2, ww3, ……., wwn]
Total number of weights = n
Specification:
1. Only basic and list functions are allowed.
2. You CANNOT use any external library, package or functions in your program.