code: def __init__(self, individual, n_vars, nf, h, c_out, head_dropout=0):
      super().__init__()
  
      self.individual = individual
      self.n_vars = n_vars
      self.c_out = c_out
  
      if self.individual:
          self.linears = nn.ModuleList()
          self.dropouts = nn.ModuleList()
          self.flattens = nn.ModuleList()
          for i in range(self.n_vars):
              self.flattens.append(nn.Flatten(start_dim=-2))
              self.linears.append(nn.Linear(nf, h * c_out))
              self.dropouts.append(nn.Dropout(head_dropout))
      else:
          self.flatten = nn.Flatten(start_dim=-2)
          self.linear = nn.Linear(nf, h * c_out)
          self.dropout = nn.Dropout(head_dropout)
  
imports: import math
  import numpy
  from typing import Optional
  import torch
  import torch.nn
  import torch.nn.functional
  from ..common._base_windows import BaseWindows
  from ..losses.pytorch import MAE
label_desc: Use image node_id 1 to create a new Flatten_Head object from inherited base classes: nn with example: obj = Flatten_Head(individual, n_vars, nf, h, c_out, head_dropout)