import torch
import torch.nn as nn
from typing import List


# --------------------- Basic modules ---------------------
class ConvModule(nn.Module):
    def __init__(self, 
                 in_dim,                   # in channels
                 out_dim,                  # out channels 
                 kernel_size=1,            # kernel size 
                 padding=0,                # padding
                 stride=1,                 # padding
                 dilation=1,               # dilation
                ):
        super(ConvModule, self).__init__()
        self.conv = nn.Conv2d(in_dim, out_dim, kernel_size=kernel_size, stride=stride, padding=padding, dilation=dilation, bias=False)
        self.norm = nn.BatchNorm2d(out_dim)
        self.act  = nn.LeakyReLU(0.1, inplace=True)

    def forward(self, x):
        return self.act(self.norm(self.conv(x)))