import numpy as np 
np.random.seed(0)
from nnfs.datasets import spiral_data

X,y = spiral_data(100,3)

class Layer_Dense:
    def __init__(self,n_inputs,n_neurons):
        self.weights = 0.20 * np.random.randn(n_inputs,n_neurons)
        self.biases = np.zeros((1,n_neurons))


    def forward(self,inputs):
        self.output = np.dot(inputs,self.weights) + self.biases

class Activation_ReLU:
    def forward(self,inputs):
        self.output = np.maximum(0,inputs)


layer1 = Layer_Dense(2,5)
activation1 = Activation_ReLU()

layer1.forward(X)
activation1.forward(layer1.output)
#print (layer1.output)
print (activation1.output)
