# Create a standalone file with just the model class import torch import torch.nn as nn class TabularModel(nn.Module): def __init__(self, input_size, hidden_sizes, output_size, dropout_rate=0.2): super(TabularModel, self).__init__() layers = [] prev_size = input_size for hidden_size in hidden_sizes: layers.extend([ nn.Linear(prev_size, hidden_size), nn.BatchNorm1d(hidden_size), nn.ReLU(), nn.Dropout(dropout_rate) ]) prev_size = hidden_size layers.append(nn.Linear(prev_size, output_size)) self.model = nn.Sequential(*layers) def forward(self, x): return self.model(x)