import numpy as np

np.random.seed(0)
x = [[1,2,3,2.5], [2.0,5.0,-1.0, 2.0], [-1.5,2.7,3.3,-0.8]]
class Layer_Dense:
    def __init__(self, n_inputs, n_neurons):
        self.weights = 0.10*np.random.randn(n_inputs, n_neurons) #we don't need to do transpose every time
        self.biases = np.zeros((1,n_neurons))
    def forward(self, inputs):
        self.output = np.dot(inputs, self.weights)+self.biases

layer1 = Layer_Dense(4,5)
layer2 = Layer_Dense(5,2)

layer1.forward(x)
layer2.forward(layer1.output)

print(layer1.output)
print(layer2.output)
