def fit():
    for epoch in range(epochs):
        for i in range((n - 1) // bs + 1):
            start_i = i * bs
            end_i = start_i + bs
            [xb](https://docs.pytorch.org/docs/stable/tensors.html#torch.Tensor "torch.Tensor") = [x_train](https://docs.pytorch.org/docs/stable/tensors.html#torch.Tensor "torch.Tensor")[start_i:end_i]
            [yb](https://docs.pytorch.org/docs/stable/tensors.html#torch.Tensor "torch.Tensor") = [y_train](https://docs.pytorch.org/docs/stable/tensors.html#torch.Tensor "torch.Tensor")[start_i:end_i]
            [pred](https://docs.pytorch.org/docs/stable/tensors.html#torch.Tensor "torch.Tensor") = [model](https://docs.pytorch.org/docs/stable/generated/torch.nn.Sequential.html#torch.nn.Sequential "torch.nn.Sequential")([xb](https://docs.pytorch.org/docs/stable/tensors.html#torch.Tensor "torch.Tensor"))
            [loss](https://docs.pytorch.org/docs/stable/tensors.html#torch.Tensor "torch.Tensor") = loss_func([pred](https://docs.pytorch.org/docs/stable/tensors.html#torch.Tensor "torch.Tensor"), [yb](https://docs.pytorch.org/docs/stable/tensors.html#torch.Tensor "torch.Tensor"))

            [loss.backward](https://docs.pytorch.org/docs/stable/generated/torch.Tensor.backward.html#torch.Tensor.backward "torch.Tensor.backward")()
            with [torch.no_grad](https://docs.pytorch.org/docs/stable/generated/torch.no_grad.html#torch.no_grad "torch.no_grad")():
                for p in [model.parameters](https://docs.pytorch.org/docs/stable/generated/torch.nn.Module.html#torch.nn.Module.parameters "torch.nn.Module.parameters")():
                    p -= p.grad * lr
                [model.zero_grad](https://docs.pytorch.org/docs/stable/generated/torch.nn.Module.html#torch.nn.Module.zero_grad "torch.nn.Module.zero_grad")()

fit()