code: def forward(self, x):
      for i, lin in enumerate(self.linears):
          x = lin(x)
          if i < len(self.linears) - 1:
              x = F.__dict__[self.activation](x)
              if self.dropout > 0:
                  x = F.dropout(x, self.dropout, training=self.training)
      return x
  
imports: import torch
  import torch.nn
  import torch.nn.functional
  from mmf.common.registry import registry
  from mmf.utils.general import get_chunks, get_sizes_list, irfft, rfft
  from mmf.utils.logger import log_class_usage
label_desc: Use image node_id 2 for calling the MLP obj's underlying member method code with example usage: obj.forward(x) and returns: x