I am new to pytorch, not familar with the gradient graph. I just created 2-layers NN, however the weights did not update during training process. Please help me out.
import torch
import torch.nn as nn

torch.set_default_dtype(torch.float64)

class Nets(nn.Module):
    def __init__(self):
        super().__init__()
        self.hidden1 = nn.Linear(26, 15)
        self.hidden2 = nn.Linear(15, 15)
        self.out = nn.Linear(15, 1)
        
    def forward(self, training_sets):
        trained_results = torch.tensor([], requires_grad=True)
        for ts in training_sets:
            x = self.hidden1(ts)
            x = torch.tanh(x)

            # flow to 2nd hidden layer
            x = self.hidden2(x)
            x = torch.tanh(x)

            # flow to output layer
            x = self.out(x)
            e = torch.sum(x)
            trained_results = torch.cat((trained_results, torch.tensor([e])))
        return trained_results

import torch.nn as nn
import numpy as np
from math import sqrt

net = Nets()
# Mean Square Error
loss_func = nn.MSELoss(reduction='mean')
learning_rate = 0.01
optimizer = torch.optim.Adam(net.parameters(), lr=learning_rate)

epochs = 1001
error = []
for i in range(epochs):
    loss = loss_func(net(inputs), target_results)
    if i % 100 == 0:
        print(i, loss, net(inputs))
        error.append(loss)       
    optimizer.zero_grad()
    loss.backward(retain_graph=True)
    optimizer.step()

results outputs:
0 tensor(5629.6088, grad_fn=) tensor([-17.9612, -17.9524, -17.9473], grad_fn=)
100 tensor(5629.6088, grad_fn=) tensor([-17.9612, -17.9524, -17.9473], grad_fn=)
200 tensor(5629.6088, grad_fn=) tensor([-17.9612, -17.9524, -17.9473], grad_fn=)
300 tensor(5629.6088, grad_fn=) tensor([-17.9612, -17.9524, -17.9473], grad_fn=)
400 tensor(5629.6088, grad_fn=) tensor([-17.9612, -17.9524, -17.9473], grad_fn=)
500 tensor(5629.6088, grad_fn=) tensor([-17.9612, -17.9524, -17.9473], grad_fn=)
600 tensor(5629.6088, grad_fn=) tensor([-17.9612, -17.9524, -17.9473], grad_fn=)
700 tensor(5629.6088, grad_fn=) tensor([-17.9612, -17.9524, -17.9473], grad_fn=)
800 tensor(5629.6088, grad_fn=) tensor([-17.9612, -17.9524, -17.9473], grad_fn=)
900 tensor(5629.6088, grad_fn=) tensor([-17.9612, -17.9524, -17.9473], grad_fn=)
1000 tensor(5629.6088, grad_fn=) tensor([-17.9612, -17.9524, -17.9473], grad_fn=)