# coding=utf-8

import torch.nn as nn


class TestModule(nn.Module):
    def __init__(self, start_layer_index: int, end_layer_index: int, *args, **kwargs):
        super().__init__(*args, **kwargs)
        self.model = DecodeLayer()

    def forward(self, x):
        for module in self.model:
            x = module(x)
        return x


class DecodeLayer(nn.Module):
    def __init__(self, *args, **kwargs):
        super().__init__(*args, **kwargs)
        self.layers = nn.ModuleList()
        for i in range(10):
            self.layers.append(nn.Linear(10, 10))


if __name__ == "__main__":
    test_module = TestModule(0, 3)
    for x in test_module.named_parameters():
        print(x[0])