Multi-layer perceptron. Consider the following neural networ…
Multi-layer perceptron. Consider the following neural network defined in PyTorch. import torch.nn as nnclass NeuralNetwork(nn.Module): def __init__(self): super().__init__() self.linear_relu_stack = nn.Sequential( nn.Linear(20, 100), nn.ReLU(), nn.Linear(100, 100), nn.ReLU(), nn.Linear(100, 3), ) def forward(self, x): logits = self.linear_relu_stack(x) return logits (a) (2 pts) How many learnable layers does the neural network have? Count only layers that contain trainable parameters. (b) (2 pts) How many parameters does the neural network have? You may disregard bias/offset terms.